Systemic Infection and Brain Resilience in Patients With Seizures: An Inverse-Model Hypothesis From a Retrospective Cohort Study

Systemic Infection and Brain Resilience in Patients With Seizures: An Inverse-Model Hypothesis From a Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Systemic Infection and Brain Resilience in Patients With Seizures: An Inverse-Model Hypothesis From a Retrospective Cohort Study Yi-Te Huang, Tzu-Hsin Huang, Yu-Shiue Chen, Ting-Rong Chen, Sheng-Hsiang Lin, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9149796/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Introduction : Systemic infection and seizures frequently co-occur in patients. Nevertheless, the association between seizures, its triggers and concurrent systemic infectious diseases (CSIDs) other than central nervous system infections remains unclear. Methods : This retrospective cross-sectional study evaluated 216 inpatients with ongoing seizures at a tertiary center in Taiwan in 2018. Clinical, radiological, and microbiological characteristics were compared between the patients with or without CSIDs. Results : CSIDs were identified in 72.6% of the patients. Those with CSIDs were older (p = 0.0020), and had more dementia (p = 0.0180), hippocampal atrophy (p = 0.0167), chronic brain injury (p = 0.0091), and greater cerebral small vessel disease (CSVD) burden (CT, p = 0.0373; MRI, p = 0.0373). Interestingly, those with severe CSIDs (septic shock, bacteremia) had lower CSVD burden (p = 0.0365, white matter lesion positivity; p = 0.0190, deep white matter Fazekas score) than mild CSIDs.Multivariate logistic regression confirmed this inverse relationship (adjusted OR: 10.2, p = 0.0448) for deep white matter Fazekas score. Additionally, seizures associated with Gram-positive cocci (GPC) infections occurred in patients with lower burden of chronic brain injury (p = 0.0099) and hippocampal atrophy (p = 0.0391) compared to Gram-negative bacilli (GNB)infections. Conclusion : Thesefindings support an “Inverse model” hypothesis where systemic inflammation and diminished brain resilience are linked in seizure manifestation. Consequently, in older adults with chronic brain lesions, seizures may occur even in the setting of mild infections. In contrast, more severe infections tend to be associated with seizures in patients with uncompromised brains. Seizure risk was higher in patients with GPC infections than in those with GNB infections. These results underscore the importance of screening for systemic infections in older patients or those with dementia or higher chronic brain lesion burden who present with seizures, even in the absence of fever. Systemic infection seizure cerebral small vessel disease chronic brain lesion brain resilience neuroinflammation epileptogenesis pneumonia urinary tract infection bacteremia Figures Figure 1 Figure 2 Figure 3 Key summary points 1. Systemic infections are a frequent and underrecognized contributor to seizure occurrence, particularly in older adults with chronic structural brain lesions. However, the complex interplay between systemic infections and preexisting brain pathology in patients with seizures remains to be elucidated. 2. Among patients with concurrent systemic infectious diseases and seizures, an inverse association was observed between infection severity and brain lesion burden, suggesting that milder infections are associated with seizures in structurally vulnerable brains, whereas more severe infections are typically observed in patients with relatively structurally intact brains. 3. We proposed an “Inverse-Model” hypothesis, in which seizures result from the combined effects of systemic inflammation and diminished brain resilience, especially in older patients or those with cognitive impairment. 4. Within the “Inverse-Model” framework, seizure associated with Gram-positive coccal infections occurred under significantly lower brain lesion burdens than those associated with Gram-negative bacilli, suggesting Gram-positive cocci may pose a higher seizure risk. 5. In patients presenting with seizures who have dementia or a higher burden of chronic brain lesions, a more thorough investigation for systemic infections is warranted. Introduction Seizures are a neurological disorder not uncommon among hospitalized patients. Among the various triggers, systemic infections, such as pneumonia, urinary tract infection, cellulitis, or bacteremia, are frequently encountered during seizure evaluation. However, the basic profile and mechanistic influence of these concurrent systemic infectious diseases (CSIDs) on seizure occurrence remain underexplored, especially when central nervous system (CNS) infections are excluded. The literature reports few clinical profiles of patients with CSIDs and seizures [1, 2], and even fewer studies have examined the causal relationships among established seizure-triggering factors. Brain resilience, or the brain’s ability to resist systemic stressors, may provide a framework for interpreting these interactions. Brain resilience may decline because of chronic brain lesions caused by hippocampal atrophy [3], neurosurgical intervention [4] traumatic brain injury (TBI) [5] or cerebral small vessel disease (CSVD) [6, 7]. The present study hypothesized that patients with compromised brain resilience may be at greater risk of experiencing seizures than those with uncompromised brain resilience are. Factors linked to infection may also influence seizure susceptibility. Although fever is a well-documented trigger of seizures [8] and febrile infection-related epilepsy syndrome, a rare acute-onset chronic epilepsy syndrome in children [9], its role in adult seizure susceptibility remains unclear. Additionally, pathogens may generally differ in their epileptogenic potential. For example, Gram-positive cocci (GPC), such as Staphylococcus and Streptococcus, produce superantigens that induce toxic shock syndrome [10], whereas lipopolysaccharides or endotoxins—the principal cell wall components of Gram-negative bacilli (GNB)—are critical to sepsis and systemic inflammation [11]. The present study described the clinical, imaging, and microbiological profiles of patients with seizures and CSIDs, compared patients with and without CSIDs, and analyzed the differences in infection severity, febrile status, and microbiology among patients with CSIDs. The cohort included only patients hospitalized in 2018, with this limited timeframe imposed to mitigate confounding from hospital admission trends linked to COVID-19. Methods This retrospective cross-sectional study included patients admitted to National Cheng Kung University Hospital in Tainan, Taiwan, between January 1 and December 31, 2018, for medical treatment who experienced seizures at admission or during hospitalization. Patient data were retrieved using keywords such as (1) “seizure,” “epilepsy,” “convulsion,” and “status epilepticus.” or (2) International Classification of Diseases ( ICD )- 9 or ICD -10 codes for seizures in nonsurgical wards were employed through electronic medical records to obtain patients (Supplementary Material, Table S1). Initially, 533 patients were identified with profiles matching the keywords or having relevant ICD codes. After a comprehensive review of these patients’ medical records, 318 patients were excluded due to the following reasons: absence of a documented seizure event during hospitalization, a final diagnosis inconsistent with seizure, insufficient clinical information to distinguish seizures from other non-epilpetic movement disorders, or confirmed CNS infection. The final analysis included 216 patient–events (Figure 1). We collected data on the patients’ demographic characteristics, seizure semiology, comorbidities, systemic infection status, and radiological findings. The seizure-specific dataset comprised information on seizure category (acute symptomatic or provoked seizures are defined by the presence of an acute systemic or neurological insult like recent stroke, brain tumor, anoxic brain injury, metabolic imbalance, fever, or ASM withdrawal. In contrast, unprovoked seizures are those occurring in the absence of an identifiable clinical trigger) [12], seizure type (focal preserved or impaired consciousness seizure, focal-to-bilateral tonic-clonic seizure and generalized onset seizure) [13], seizure onset location (before or during emergency room visit or during hospitalization), date and sequence of seizures and CSIDs, and antiseizure medication (ASM) use before and after the hospital visit. The ASMs prescribed were levetiracetam, valproate, carbamazepine, oxcarbazepine, phenytoin, topiramate, vigabatrin, clonazepam, lamotrigine, zonisamide, phenobarbital, perampanel, and clobazam. Infection profiles encompassed information regarding vital signs, arterial blood gas, infection site, and microbiological findings. Brain imaging abnormalities identified through computed tomography (CT) or magnetic resonance imaging (MRI) were recorded, as were seizure-triggering factors such as serum sodium, calcium, magnesium levels, blood glucose levels, and offending antimicrobial agents (Supplementary Material, Table S2). The definition of CSID emphasizes “concurrent” occurrence of systemic infection and seizure which was defined either (1) when systemic infection was detected at the time of seizure onset or (2) within post-ictal 24 hours for not leaving out atypical presentation of infectious diseases especially in geriatric/frail population [14-16], or (3) when seizures occurred during the ongoing treatment of a documented systemic infection. Evidence of infections was confirmed by clinical signs, antibiotic initiation, and microbiologic workup. Infections developing more than 24 hours post-seizure were excluded. (Figure 2). To compare comorbidities across groups, we applied the Charlson Comorbidity Index (CCI) and Epilepsy-Specific Comorbidity Index. Comorbidity presence and scores were determined through a comprehensive electronic medical record examination involving consideration of conditions ranging from hypertension and diabetes mellitus to malignancy, either non-metastatic or metastatic, solid or hematologic malignancies categorized by disease status as in remission, stable, or progressive. Because CNS infection is well established as a cause of seizures, CSIDs were defined as non-CNS infections diagnosed through clinical, laboratory, and imaging findings. They included pneumonia, urinary tract infection, skin or soft-tissue infection (cellulitis, open wound, pressure sore), enteritis/colitis, biliary tract infection, abscess, peritonitis, septic arthritis, bacteremia / septic shock with or without identifiable primary origin. Included patients were stratified into CSID and non-CSID groups. CSID severity was categorized as mild (characterized by the absence of septic shock or bacteremia) or severe (characterized by the presence of septic shock or bacteremia). Seizure-triggering antimicrobial agents, such as carbapenem (imipenem, ertapenem and meropenem) and cefepime, were identified using electronic medical records and assessments made by neurologists or other physicians. We also analyzed the patients’ CT and MRI findings. In an image scoring analysis, we considered the evaluation metrics of medial temporal atrophy score [17], modified visual rating scale for CT CSVD score [18], STRIVE (STandards for Reporting and Imaging of Small Vessel Disease) criteria for MRI CSVD [19] score, Fazekas score for white matter hyperintensity (WMHI) [20], and cerebral microbleed (CM) [19], enlarged perivascular space (EPVS) [21], and lacunar stroke [19] scoring criteria. The inclusion criteria and respective scoring rules for each brain imaging item are provided (Supplementary Material, Table S3). Imaging abnormalities were classified into three categories for seizure association analysis: (1) recent brain injury, such as recent stroke, brain tumor, and anoxic brain injury; (2) chronic brain injury, such as old stroke, encephalomalacia, TBI, and surgical brain injury; and (3) developmental anomalies, such as cortical dysplasia, mesial temporal sclerosis, vascular anomaly, and microcephaly. Statistical Analysis All statistical analyses were conducted using IBM SPSS Statistics (version 24.0, IBM Corp., Armonk, NY). Continuous variables were initially tested for normality using the Shapiro–Wilk test. Variables with normal distributions were presented as means ± standard deviations (SD) and compared using the independent Student’s t test. Variables that did not follow a normal distribution were reported as median (interquartile range, IQR) and analyzed using the Mann–Whitney U test. Categorical variables were expressed as counts and percentages, and between-group comparisons were performed using the Chi-square test or Fisher’s exact test where appropriate (e.g., when expected counts were <5). For subgroup analyses (e.g., mild vs. severe CSID, febrile vs. afebrile, GPC vs. GNB), the same principles were applied: Shapiro–Wilk testing for continuous variables, followed by appropriate parametric or non-parametric tests depending on the data distribution. Statistical significance was defined as a two-tailed p value < 0.05. No adjustments were made for multiple comparisons, as this was an exploratory study aimed at hypothesis generation. Where applicable, missing data were noted, and analysis was conducted on available cases without imputation. Interrater Reliability Cohen’s κ coefficient was used for categorical variables, and intraclass correlation coefficients (ICCs) were used for continuous variables. Two raters (one neurologist, Y.T. Huang and one neuroradiologist, T. R. Chen) scored the images after completing training to do so, and the reliability of their assessments was confirmed by using a random sample comprising 10% of the total imaging studies. The interrater reliability was acceptable for all neuroimaging biomarkers (κ = 0.773 for hippocampal atrophy; ICC = 0.857 for lacune number; ICC = 0.835 for CT CSVD score; ICC = 0.750 for Fazekas score, deep WMHI; ICC = 0.866 for Fazekas score, periventricular WMHI; ICC = 0.833 for deep CMs ; ICC = 0.870 for cortical CMs; ICC = 0.727 for basal ganglion EPVS; and ICC = 0.886 for centrum semiovale EPVS). Results Among the 216 included patients, 210 (97.2%) of the seizures were classified as acute symptomatic seizures. 157 (72.6%) had CSIDs, and 59 did not. The patients with CSIDs were older (65.9 ± 18.7 years vs. 56.3 ± 20.4 years, p = 0.0020), had a higher prevalence of acute symptomatic seizures (100% vs. 89.8%, p = 0.0003) and generalized seizures (55.8% vs. 37.1%, p = 0.0386), had a lower prevalence of malignancy (26.6% vs. 44.5%, p = 0.0056), and were more likely to have dementia (25.3% vs. 9.7%, p = 0.0180) relative to those without CSIDs. Infection-related manifestations, specifically, peri-ictal fever (35.0% vs. 8.5%, p = 0.0001), septic shock (15.3% vs. 1.7%, p = 0.0054), and acid–base imbalance (respiratory acidosis, alkalosis, or metabolic acidosis, 53.9% vs. 23.7%, p = 0.0001) were more frequent in the CSID group. By contrast, recent brain injuries (stroke, brain tumors, and anoxic brain injury) were more common in the non-CSID group (47.5% vs. 27.4%, p = 0.0051). Chronic brain injuries, such as old stroke, encephalomalacia, TBI, and surgical brain injury, were more prevalent in the CSID group (50.3% vs. 30.5%, p = 0.0091). Radiological comparisons revealed that the patients with CSIDs were more likely to exhibit hippocampal atrophy (62.3% vs. 44.1%, p = 0.0167), have higher CT CSVD scores (1.30 ± 1.16 vs. 0.84 ± 1.11, p = 0.0097), and have higher MRI CSVD scores (1.18 ± 1.22 vs. 0.74 ± 1.11, p = 0.0373) than those without CSIDs were. The MRI-specific features that differed significantly between the groups were deep WMHI (1.22 ± 1.07 vs. 0.81 ± 0.99, p = 0.0265), periventricular WMHI (1.63 ± 1.14 vs. 1.09 ± 1.16, p = 0.0093), and basal ganglion EPVS (1.07 ± 0.84 vs. 0.77 ± 0.76, p = 0.0310). No significant differences were observed between the groups in survival rates and ASM prescriptions (Table 1). To investigate the observed pattern of more frequent recent brain injury in the non-CSID group and more frequent chronic brain injury in the CSID group, we stratified the patients with CSIDs into mild (characterized by the absence of septic shock or bacteremia) and severe (characterized by the presence of septic shock or bacteremia) subgroups. This classification enabled us to assess whether infection severity was correlated, positively or negatively, with the extent of neuroimaging abnormalities. The conventional perspective regarding CSIDs and seizures suggests that patients with frailty experience more severe infections and more extensive brain pathology, whereas more robust patients have milder infections and exhibit fewer imaging abnormalities. However, the present study proposed an alternative perspective: In patients with more resilient brains and fewer structural abnormalities, seizures tended to be associated with more severe systemic inflammation; conversely, in those with more vulnerable brains, seizures were observed even in the presence of mild infections. This inverse association suggests that cumulated brain pathologies weaken brain resilience and predispose individuals to seizures (Figure 3). Among the patients with CSIDs, those with severe infections (septic shock or bacteremia, n = 49) had higher CCI values (7.5 ± 3.6 vs. 6.3 ± 3.2, p = 0.0398) and a higher prevalence of heart failure or pulmonary hypertension (53.1% vs. 30.6%, p = 0.0070). Additionally, these patients had a lower burden of deep WMHI than the mild CSID group did (0.85 ± 0.78 vs. 1.34 ± 1.13, p = 0.0190), as well as less WMHI overall (19.2% vs. 42.3%, p = 0.0365) (Table 2), indicating an inverse association between infection severity and chronic brain lesion burden. To adjust for potential confounding effects from multiple variables showing significance in univariate analysis, variables from Table 2 with p < 0.1—including CCI, ESCI, HF/pulmonary HTN, recent fever, respiratory alkalosis burden, WMHI positivity, and Fazekas score-Deep—were entered into a multivariable logistic regression model. The analysis revealed that only recent fever (adjusted OR: 0.25, p = 0.0143) and severe Fazekas score-Deep scoring 2-3 (adjusted OR: 10.2, p = 0.0448) remained independently associated with mild CSID (Table 3). These findings reinforce that among seizure patients with comorbid infections, more severe chronic brain changes are associated with milder infection severity, and vice-versa. To explore the association between CSIDs and seizure occurrence noted in the radiological findings, we investigated the underlying factors contributing to the seizures experienced by the patients with CSIDs to find the driving factors behind. We speculate that infection may precipitate seizures through either host immune response or pathogen-derived antigens or toxins, and fevers reflect a host immune response. And Gram stain classification can be employed as an objective and practical approach to evaluating the ictogenic potential of different pathogen classes. As an expression of host immune, in febrile status analysis, mild CSID patients were divided into afebrile ( N = 76) and febrile ( N = 32) subgroups. The patients with severe CSIDs were excluded to avoid confounding effects from septic shock and bacteremia. The patients with fever had lower rates of heart failure and pulmonary hypertension (15.6% vs. 36.8%, p = 0.0288) and reduced major electrolyte or glucose imbalance (18.8% vs. 38.2%, p = 0.0491) than those without fever did. However, no significant differences in neuroimaging markers were observed (Table 4), suggesting that fever had a neutral effect when mediated by radiological abnormality burden on seizure risk in this adult cohort. But still, an analogous inverse relationship existed between febrile status and major electrolyte / glucose imbalance severity. We further compared the subgroups of patients with CSIDs with positive cultures for GPC and GNB. The GNB subgroup had a significantly higher incidence of urinary tract infections (49.1% vs. 22.2%, p = 0.0465) and lower extreme blood urea nitrogen/creatinine ratios (15.1% vs. 50.0%, p = 0.0080) than the GPC subgroup did. The patients with GPC infections exhibited a lower burden of chronic brain injury (33.3% vs. 67.9%, p = 0.0099) and less hippocampal atrophy (38.9% vs. 66.7%, p = 0.0391) than did those with GNB infections (Table 5). These findings suggest that seizures linked to GPCs may occur even in the absence of extensive preexisting brain pathology, which supports the present study’s ”Inverse model” of systemic inflammation and seizure susceptibility. Discussion The present study identified a high prevalence of CSIDs among the patients hospitalized with ongoing seizures. This finding indicates that CSIDs may be an independent seizure-precipitating factor rather than a coincidental comorbidity or sequela of seizures, particularly in individuals with reduced brain resilience due to chronic structural abnormalities. To enhance the accuracy of identifying patients with infectious diseases preceding seizures, this study included not only those who showed infectious signs and symptoms at the time of seizure presentation, but also those who developed such features within the first 24 hours postictally. This approach reflects real-world clinical practice, where infectious disease-related signs and symptoms (e.g., fever) often fluctuate and may not perfectly coincide precisely with seizure onset [16]. Some concurrent infectious diseases were noticed shortly after seizure management. Thus, this extended time period is especially crucial for elderly patients, in which population infectious signs and symptoms are often blunted or initially unnoticed [14, 15]. As for the selection of 24-hour window, rather than a narrower (e.g., 12 hours) or broader (e.g., 48-hour) timeframe, it was based on the pathophysiology of postictal complications. Aspiration-related pneumonia, a common sequela following seizures typically manifests with symptoms including cough, fever, purulent sputum, and dyspnea over several days or weeks rather than within hours [22, 23], which were resulted from seizures and poor consciousness in this study setting. This time window was aimed to minimize the potential confounding influence of seizure-induced infections. The patients with CSIDs were older and more frequently had received a diagnosis of dementia, consistent with epidemiological patterns linking aging to increased susceptibility to infection [24], increased prevalence of dementia [25], and increased seizure risk in individuals with neurodegenerative conditions [26]. Although non-CNS systemic infections and dementia are not direct epileptogenic factors, both may reduce seizure thresholds by modulating systemic inflammation and disrupting neural homeostasis [26, 27]. In the patients with CSIDs in the present study, infection-related features such as peri-ictal fever and acid–base imbalance occurred frequently, indicating an ongoing systemic inflammatory response. These patients also presented with fewer recent but more chronic brain injuries and exhibited higher burdens of CSVD and hippocampal atrophy, which are radiological markers associated with diminished brain resilience [3, 6, 7]. By contrast, the patients without CSIDs were more likely to present with seizure triggers such as acute stroke [28] and brain tumors [29]. To evaluate the temporal and causal relationships between infection and seizures, we stratified the patients with CSIDs into mild and severe subgroups. Although the conventional understanding of seizures and CSIDs suggests that more severe systemic illness coincides with more extensive brain pathology, our patients with severe CSIDs (septic shock or bacteremia) had significantly lower CSVD burdens than did those with milder infections. This inverse association suggests that more severe systemic inflammation is associated with seizure occurrence in patients with intact brains, whereas even minor systemic disturbances may be associated with seizure occurrence in patients with substantial brain pathology. These results support the proposed ”Inverse-Model” hypothesis, in which seizures result from the combined effects of systemic inflammatory stress and preexisting brain vulnerability, especially in elderly or patients comorbid with dementia [7, 10, 11, 30-33]. In comparisons of the incidence of comorbidities between the groups, heart failure and pulmonary hypertension occurred more frequently in the severe CSID group than in the mild CSID group. The mechanism by which heart failure induces seizures may involve circulatory anoxia [34] or seizure-induced asystole presenting as syncope, which is often indistinguishable from seizures with impaired awareness [35]. Although heart failure contributes to CSVD, it typically results in cerebral cortical microinfarcts [36], which differ from deep white matter lesions in this study. Additionally, the severe CSID group exhibited a lower CSVD burden than the non-CSVID group did. This finding may be attributable to the lack of an association between pulmonary hypertension and seizures and CSVD: Pulmonary hypertension has only been linked to seizures in isolated case reports [37, 38], and research has documented no association between pulmonary hypertension and CSVD [39]. Therefore, although heart failure and pulmonary hypertension were more prevalent in the severe CSID group in the current study, these conditions are unlikely to confound the observed inverse association between infection severity and chronic brain lesion burden. Notably, the patients with CSIDs linked to GPC exhibited significantly lower chronic brain lesion burden than those with CSIDs linked to GNB did. The literature in this field has primarily addressed Staphylococcal or Streptococcal toxic shock syndrome, which is characterized by multiple organ failure (respiratory, renal, and hepatic failure; skin necrosis; and coagulopathy) due to diffuse capillary leakage. Additionally, because the neurological manifestations of CSIDs have not been well described [40], whether diffuse capillary leakage in the CNS increases susceptibility to inflammatory mediators and the risk of subsequent seizures when brain integrity is uncompromised remains unknown. Nevertheless, our findings support the hypothesis that certain pathogens possess higher intrinsic ictogenic toxicity and epileptogenic potential than others do. However, these observations should be interpreted with caution; due to the relatively small sample size, our analysis may have limited statistical power and an increased risk of type I error. Therefore, these results should be considered preliminary and require validation in larger, multicenter cohorts. We also evaluated the association of fever with seizures. Although fever’s role in childhood seizures is well established [8, 9] and one study indicated that cytokines linked to fever, such as interleukin-1β and interleukin-6, may predispose children to febrile seizures [41], no significant radiological differences were observed between the afebrile and febrile subgroups in the present study. This result suggests that fever may not function as a primary seizure trigger in adults by the proposed “ Inverse model” in the radiological standpoint. But still there found an analogy between febrile status and prevalence of major electrolyte / glucose imbalance, which is beyond the scope of this study. This finding is particularly notable because older adults with dementia or structural brain lesions may not exhibit typical infection symptoms [14-16]. This study has several limitations. First, the retrospective cross-sectional design restricted the conclusions to associations rather than causal relationships. Furthermore, the retrospective nature of the study may affect data precision. This is exemplified by the discrepancy where the recorded number of patients with a known epilepsy history was lower than those already receiving ASMs, suggesting an underestimation of the true prevalence of epilepsy history. Consequently, we did not perform a subgroup analysis based on the presence or absence of a prior epilepsy history. Additionally, a higher proportion of generalized tonic-clonic seizures (GTCS) was observed. We speculate that this is ascribed to the fact that seizure semiology was primarily documented based on witness accounts, most of whom were family members rather than medical professionals, potentially leading to the under-reporting of more subtle seizure types. Second, results in this study were derived from hospitalized patients and focused on non-surgical ward patients with acute symptomatic seizures rather than unprovoked seizures, which may limit the generalizability of the results to the epilepsy population. Only a minority (19.4%) of patients had prior history of epilepsy (18.6% for non-CSID, 19.7% for CSID), raising the potential for selection bias, such as Berkson’s paradox. Third, while considerable effort was made to rigorously define and distinguish cases with CSIDs, challenges remain. The inclusion criteria allowed for infectious signs and diagnoses identified during the pre-ictal, ictal, or within 24 hours post-ictal period, this approach cannot fully eliminate the possibility that some infections may have been triggered or exacerbated by the seizures, such as seizure-induced aspiration pneumonia. Despite this limitation, the 24-hour window was selected as a clinically reasonable approach to enhance diagnostic sensitivity while minimizing reverse causation. Furthermore, due to the retrospective design and the resulting missing data, standard clinical scoring systems such as APACHE II or qSOFA could not be applied for CSID severity grading. Nonetheless, our simplified classification based on septic shock and bacteremia offers greater clinical utility and ease of application in real-world practice. Fourth, missing data and a relatively small sample size may also limit the generalizability of the findings. Finally, the observations from MRIs and microbiological evaluations did not reach significance and remained suggestive, likely because the high cost of MRIs and the low yield rate of current culture techniques render such evaluations difficult to obtain large sample size [42]. Despite these limitations, the current findings support our multiple-hit hypotheses regarding the interaction between systemic inflammation and neuronal vulnerability and its implications for seizure risk assessment and targeted interventions. Future prospective studies are warranted to further clarify the temporal relationship between systemic infections and seizure onset, and to determine whether timely infection recognition and appropriate treatment may help reduce seizure burden in at-risk populations, particularly older adults with underlying brain vulnerability such as cerebral small vessel disease, chronic brain lesion or dementia. Conclusion Systemic infections frequently contribute to seizure occurrence and remain underrecognized, particularly in older adults with chronic brain lesions. Our findings support a multiple-hit hypothesis, in which seizures result from the combined effects of systemic inflammation and diminished brain resilience. The observed inverse association between infection severity and brain lesion burden suggests that milder infections were associated with seizures in patients with vulnerable brains, whereas more severe infections are associated with seizure occurrence in patients with structurally intact brains. GPC may also pose a higher seizure risk than GNB do. These findings underscore the importance of infection screening in older patients and those with cognitive impairment presenting with seizures, even in the absence of fever. Nevertheless, a similar analogy was also found between febrile status and prevalence of major electrolyte / glucose imbalance, rather than radiological abnormality burden. Further studies are required to validate this model and obtain findings that can inform targeted prevention strategies. Abbreviations ASM: antiseizure medication BG: basal ganglion BUN: blood urea nitrogen CCI: Charlson Comorbidity Index CKD: chronic kidney disease CM: cerebral microbleed CNS: central nervous system Crea: creatinine CS: centrum semiovale CSVD: cerebral small vessel disease CT: computed tomography DM: diabetes mellitus ESCI: Epilepsy-Specific Comorbidity Index EPVS: enlarged perivascular space GNB: Gram-negative bacilli GPC: Gram-positive cocci HF: heart failure HTN: hypertension ICC: intraclass correlation coefficient ICD : International Classification of Diseases IQR: interquartile range MRI: magnetic resonance imaging OR: odds ratio SD: standard deviation STRIVE: STandards for Reporting and Imaging of Small Vessel Disease TBI: traumatic brain injury WMHI: white matter hyperintensity Declarations The authors confirm that the manuscript is not being considered for publication by another journal, nor will it be submitted elsewhere while under consideration by this journal, and has not been published previously (partly or in full). Ethics approval and consent to participate This study was approved by the institutional review board of National Cheng Kung University Hospital (Approval number: A-ER-111-475). The requirement to obtain informed consent was not applicable because of the retrospective study design and the use of deidentified medical records and imaging data. For these reasons, the requirement to obtain written informed consent from the patients was waived. Consent for publication Not applicable. This study does not contain any individual person’s data in any form (including individual details, images, or videos). Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported in part by grants from the National Science and Technology Council (112-2314-B-006 -047 -MY2), Taiwan. None of the funding sources had any role in the design, analysis, data interpretation, preparation, review, or manuscript approval of this study. Author s’ c ontributions The corresponding authors of this manuscript had full access to all the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Y.T. Huang, C.M. Chang, and C.W. Huang. Acquisition of data: Y.T. Huang. Manuscript drafting: Y.T. Huang and C.W. Huang. Digital plotting: Y.T. Huang. Image scoring: Y.T. Huang and T.R. Chen. Statistical consultation: S.H. Lin and T.R. Chen. Critical revision of the manuscript for important intellectual content: Y.T. Huang, T.H. Huang, Y.S. Chen, T.R. Chen, S.H. Lin, C.M. Chang, and C.W. Huang. Study supervision: C.W. Huang. All authors read and approved the final manuscript. Acknowledg e ments This manuscript was edited by Wallace Academic Editing. Authors’ information 1. Y.T. Huang, MD: Neurologist and geriatrician Email: [email protected] Address: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan 2. T.H. Huang, MD: Neurologist Email: [email protected] Address: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan 3. Y.S. Chen: Nurse practitioner of Neurology Email: [email protected] Address: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan 4. T. R. Chen, MD: Radiologist with a subspecialty in neuroradiology Email: [email protected] Address: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan 5. S.H. Lin, Professor: Epidemiologist and statistician E-mail: [email protected] Address: No.35, Siao dong Road, North Dist., Tainan 70457, Taiwan 6. C.M. Chang, Associate Professor: Geriatrician and infectious diseases specialist Email: [email protected] Address: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan 7. C.W. 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Tables Table 1. Comparison of Demographic, Clinical, and Radiological Features Between Patients with Seizures with and without CSIDs Non-CSID, N 1 = 59 CSID, N 2 = 157 p value Epidemiology, N = 216 Age, years, range (mean ± SD) 18-96 (56.3 ± 20.4) 18-104 (65.9 ± 18.7) 0.0020* Sex, % male 30 (50.8%) 78 (49.7%) 0.8786 CCI, range (mean ± SD) 0-13 (5.9 ± 3.8) 0-14 (6.6 ± 3.4) 0.2190 ESCI, range (mean ± SD) 0-16 (5.6 ± 4.4) 0-14 (5.6 ± 3.3) 0.9828 Past history of epilepsy (%) 11 (18.6%) 31 (19.7%) 0.8554 Seizure category (%) Acute symptomatic (provoked) 53 (89.8%) 157 (100%) 0.0003*** Unprovoked 6 (10.2%) 0 (0%) 0.0003*** Seizure semiology (%) Generalized 23 (37.1%) 86 (55.8%) 0.0386* Focal-to-bilateral tonic-clonic 6 (9.7%) 13 (8.4%) 0.6623 Focal impaired consciousness 22 (35.5%) 45 (29.2%) 0.2220 Focal preserved consciousness 8 (12.9%) 13 (8.4%) 0.2433 Underlying disease (%) HTN/DM 31 (50.0%) 103 (66.9%) 0.0780 CKD/Liver disease 14 (22.6%) 33 (21.4%) 0.6672 HF/Pulmonary HTN 20 (32.3%) 59 (38.3%) 0.6167 Malignancy 27 (44.5%) 41 (26.6%) 0.0056** Dementia 6 (9.7%) 39 (25.3%) 0.0180* Clinical/laboratory profile (%) Major electrolyte/glucose imbalance 14 (23.7%) 46 (29.3%) 0.4154 Recent fever 5 (8.5%) 55 (35.0%) 0.0001*** Septic shock 1 (1.7%) 24 (15.3%) 0.0054** Acid–base imbalance positivity 14 (23.7%) 83 (53.9%) 0.0001*** Respiratory acidosis burden 3 (5.1%) 26 (16.6%) 0.0275* Respiratory alkalosis burden 5 (8.5%) 38 (24.2%) 0.0099** Metabolic acidosis burden 7 (11.9%) 47 (29.9%) 0.0063** Metabolic alkalosis burden 6 (10.2%) 15 (9.6%) 0.8918 High lactate ≥ 2.0 (mmol/L) 13 (22.0%) 56 (35.7%) 0.0555 Severe azotemia, BUN ≥ 90 (mg/dL) 3 (5.1%) 6 (3.8%) 0.7074 BUN/Crea ratio ≥ 20 29 (49.2%) 77 (49.0%) 0.9887 Brain disease condition (%) Recent brain injury 1 28 (47.5%) 43 (27.4%) 0.0051** Chronic brain injury 2 18 (30.5%) 79 (50.3%) 0.0091** Developmental anomaly 3 5 (8.5%) 9 (5.7%) 0.5362 Radiological profile CT or MRI, N = 210 N1 = 59 (missed = 0) N2 = 151 (missed = 6) Hippocampal atrophy 26 (44.1%) 94 (62.3%) 0.0167* Lacunae positivity (%) 9 (15.3%) 37 (24.7%) 0.1452 Lacunae number, median (Q1–Q3, IQR, range) 0 (0–0, 0, 4) 0 (0–0, 0, 9) 0.2757 CT, N = 204 N1 = 56 (missed = 3) N2 = 148 (missed = 9) CT CSVD score, 0–3, average (SD) 0.84 (1.11) 1.30 (1.16) 0.0097** MRI, N = 144 N1 = 47 (missed = 12) N2 = 97 (missed = 60) MRI total CSVD score, 0–4, average (SD) 0.74 (1.11) 1.18 (1.22) 0.0373* WMHI positivity (%) 13 (27.7%) 36 (37.1%) 0.2616 Fazekas–Deep, 0–3 (SD) 0.81 (0.99) 1.22 (1.07) 0.0265* Fazekas–Periventricular, 0–3 (SD) 1.09 (1.16) 1.63 (1.14) 0.0093** CM positivity (%) 6 (12.8%) 24 (24.7%) 0.0971 CM, deep, median (Q1–Q3, IQR, range) 0 (0–0, 0, 8) 0 (0–0, 0, 68) 0.3271 CM, cortical, median (Q1–Q3, IQR, range) 0 (0–0, 0, 11) 0 (0–0, 0, 13) 0.6171 EPVS positivity if BG 2–4 (%) 7 (14.9%) 25 (25.8%) 0.1409 EPVS, total = BG + CS, average (SD) 1.70 (1.33) 2.18 (1.40) 0.0525 EPVS, BG, 0–4, average (SD) 0.77 (0.76) 1.07 (0.84) 0.0310* EPVS, CS, 0–4, average (SD) 0.94 (0.79) 1.11 (0.80) 0.2128 Outcome Mortality or critical discharge/transfer to other facility (%) 9 (15.3%) 27 (17.2%) 0.7328 ASM status for survivors, N = 180 N1 = 50 N2 = 130 Past history of epilepsy among survivors 9 (18.0%) 29 (22.3%) 0.5259 ASM number (before admission) (%) 0 (Non-user) 38 (76.0%) 87 (66.9%) 0.2364 User 12 (24.0%) 43 (33.1%) 0.2364 1 4 (8.0%) 22 (16.9%) 0.1586 2 4 (8.0%) 15 (11.5%) 0.5960 3 2 (4.0%) 4 (3.1%) 0.6704 4 1 (2.0%) 1 (0.8%) 0.4795 5 0 (0%) 1 (0.8%) 1.0000 6 1 (2%) 0 (0%) 0.2778 Average ASM class number (SD) 0.56 (1.23) 0.56 (0.96) 0.9937 ASM number (discharge) (%) 0 (Non-user) 8 (16.0%) 14 (10.8%) 0.3372 User 42 (84.0%) 116 (89.2%) 0.3372 1 30 (60.0%) 72 (55.4%) 0.5757 2 7 (14.0%) 27 (20.8%) 0.2987 3 3 (6.0%) 9 (6.9%) 1.0000 4 0 (0%) 5 (3.8%) 0.3242 5 0 (0%) 2 (1.5%) 1.0000 6 2 (4.0%) 1 (0.8%) 0.1871 Average ASM class number (SD) 1.30 (1.22) 1.45 (1.09) 0.4363 Added on average ASM class number (SD) 0.74 (0.63) 0.92 (0.85) 0.1355 ASM: antiseizure medication. BG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. IQR: interquartile range. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity. 1 Recent brain injury: recent stroke, brain tumor, or anoxic brain injury 2 Chronic brain injury: old stroke, encephalomalacia, traumatic brain injury, or surgical brain injury 3 Developmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly * p < 0.05, ** p < 0.01, *** p < 0.001 Table legends : Patients with CSIDs had significantly more prevalent hippocampal atrophy, severe CT CSVD scores, and severe MRI CSVD scores than did those without CSIDs. The features that differed significantly on MRI were deep white matter hyperintensity, periventricular white matter hyperintensity, and basal ganglion EPVS. No significant differences were observed between groups in survival rates and ASM prescriptions. Table 2. Clinical and Radiological Profiles of Patients with Seizures with Mild versus Severe CSIDs Without septic shock or bacteremia, N 1 = 108 With septic shock or bacteremia, N 2 = 49 p value Epidemiology, N = 157 Age, years, range (mean ± SD) 22-95 (65.7 ± 18.3) 18-104 (66.3 ± 19.7) 0.8493 Sex, % male 53 (49.1%) 25 (51.0%) 0.8212 CCI, range (mean ± SD) 0-14 (6.3 ± 3.2) 0-14 (7.5 ± 3.6) 0.0398* ESCI, range (mean ± SD) 0-13 (5.2 ± 3.1) 1-14 (6.3 ± 3.6) 0.0722 Past history of epilepsy (%) 23 (21.3%) 8 (16.3%) 0.4686 Seizure semiology (%) Generalized 59 (54.6%) 27 (55.1%) 0.9561 Focal-to-bilateral tonic-clonic 10 (9.3%) 3 (6.1%) 0.7558 Focal impaired consciousness 30 (27.8%) 15 (30.6%) 0.7159 Focal preserved consciousness 9 (8.3%) 4 (8.2%) 1.0000 Underlying disease (%) HTN/DM 74 (68.5%) 29 (59.2%) 0.2539 CKD/Liver disease 20 (18.5%) 14 (28.6%) 0.1565 HF/Pulmonary HTN 33 (30.6%) 26 (53.1%) 0.0070** Malignancy 26 (24.1%) 15 (30.6%) 0.3875 Dementia 30 (27.8%) 9 (18.4%) 0.2061 Clinical/laboratory profile (%) Major electrolyte/glucose imbalance 34 (31.5%) 11 (22.4%) 0.2462 Recent fever 32 (29.6%) 24 (49.0%) 0.0190* Acid–base imbalance positivity 54 (50.0%) 29 (59.2%) 0.2855 Respiratory acidosis burden 20 (18.5%) 6 (12.2%) 0.3272 Respiratory alkalosis burden 21 (19.4%) 17 (34.7%) 0.0387* Metabolic acidosis burden 32 (29.6%) 15 (30.6%) 0.9009 Metabolic alkalosis burden 10 (9.3%) 5 (10.2%) 1.0000 High lactate ≥ 2.0 (mmol/L) 36 (33.3%) 20 (40.8%) 0.3644 Severe azotemia, BUN ≥ 90 (mg/dL) 2 (1.9%) 4 (8.2%) 0.0765 BUN/Crea ratio ≥ 20 50 (46.3%) 27 (55.1%) 0.3065 Brain disease condition (%) Recent brain injury 1 28 (25.9%) 15 (30.6%) 0.5418 Chronic brain injury 2 61 (56.5%) 28 (57.1%) 0.9382 Developmental anomaly 3 6 (5.6%) 3 (6.1%) 1.0000 Radiological profile (%) CT or MRI, N = 151 N1 = 103 (missed = 5) N2 = 48 (missed = 1) Hippocampal atrophy 64 (62.1%) 29 (60.4%) 0.8397 Lacunae positivity (%) 23 (22.3%) 15 (31.3%) 0.2395 Lacunae number, median (Q1–Q3, IQR, range) 0 (0–0, 0, 9) 0 (0–0, 0, 4) 0.2757 CT, N = 148 N1 = 100 (missed = 8) N2 = 48 (missed = 1) 0.9164 CT CSVD score, 0–3, average (SD) 1.41 (1.20) 1.06 (1.06) 0.0767 MRI, N = 97 N1 = 71 (missed = 37) N2 = 26 (missed = 23) MRI total CSVD score, 0–4, average (SD) 1.20 (1.24) 1.19 (1.23) 0.9863 WMHI positivity (%) 30 (42.3%) 5 (19.2%) 0.0365* Fazekas–Deep, 0–3 (SD) 1.34 (1.13) 0.85 (0.78) 0.0190* Fazekas–Periventricular, 0–3 (SD) 1.70 (1.18) 1.38 (1.02) 0.1968 CM positivity (%) 18 (25.4%) 7 (26.9%) 0.8755 CM, deep, median (Q1–Q3, IQR, range) 0 (0–0, 0, 68) 0 (0–0, 0, 2) 0.9283 CM, cortical, median (Q1–Q3, IQR, range) 0 (0–0, 0, 13) 0 (0–0, 0, 3) 0.8572 EPVS positivity if BG 2–4 (%) 19 (26.8%) 7 (26.9%) 0.9872 EPVS, total = BG + CS (SD) 2.20 (1.35) 2.23 (1.66) 0.9266 EPVS, BG, 0–4 (SD) 1.11 (0.85) 1.00 (0.85) 0.5660 EPVS, CS, 0–4 (SD) 1.10 (0.78) 1.23 (0.95) 0.5291 BG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. IQR: interquartile range. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity. 1 Recent brain injury: recent stroke, brain tumor, or anoxic brain injury 2 Chronic brain injury: old stroke, encephalomalacia, traumatic brain injury or surgical brain injury 3 Developmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly * p < 0.05, ** p < 0.01 Table legends : Among the patients with CSIDs, those with severe infections were more likely to have higher comorbidity scores, including higher Charlson Comorbidity Index values and greater heart failure or pulmonary hypertension than those without severe infections were. Additionally, these patients had a lower burden of deep WMHI than did the mild CSID group, as well as less WMHI overall, suggesting an inverse association between infection severity and chronic brain lesion burden. Table 3. Univariate and logistic regression analysis of factors associated with mild CSID among patients with CSID Mild CSID, N 1 = 71 Severe CSID, N 2 = 26 Crude OR (95% CI) Adjusted OR (95% CI) Adjusted p value High CCI, ≥ 7 37 (52.1%) 18 (69.2%) 0.48 (0.19-1.26) 0.57 (0.13- 2.56) 0.4617 High ESCI, ≥ 6 30 (42.3%) 15 (57.7%) 0.54 (0.22-1.33) 1.24 (0.30-5.08) 0.7652 HF/Pulmonary HTN 24 (33.8%) 15 (57.7%) 0.37 (0.15-0.94) 0.32 (0.10-1.02) 0.0534 Recent fever 16 (22.5%) 14 (53.8%) 0.25 (0.10-0.65) 0.25 (0.08-0.76) 0.0143* Respiratory alkalosis burden 13 (18.3%) 12 (46.2%) 0.26 (0.10-0.70) 0.47 (0.15-1.50) 0.2031 WMHI positivity 30 (42.3%) 5 (19.2%) 3.07 (1.04-9.08) 1.11 (0.19-6.39) 0.9071 Fazekas–Deep, severe (2-3) 25 (35.2%) 2 (7.7%) 6.52 (1.42-29.89) 10.2 (1.06-99.4) 0.0448* CCI: Charlson Comorbidity Index. CI: confidence interval. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. OR: odds ratio. WMHI: white matter hyperintensity. * p < 0.05 Table legends : In the multivariable logistic regression analysis, the presence of fever showed a significant negative association with mild CSID, whereas a high Fazekas score-Deep (2–3) was significantly and positively associated with mild CSID, consistent with our earlier observations. Other variables that initially presented with p < 0.1 in Table 2 lost their statistical significance after adjustment. Table 4. Comparison of Patients with and without Fever in the Mild CSID Subgroup Afebrile, N 1 = 76 Febrile, N 2 = 32 p value Epidemiology, N = 108 Age, years, range (mean ± SD) 22-92 (66.7 ± 17.5) 22-95 (63.4 ± 20.2) 0.4336 Sex, % male 34 (44.7%) 19 (59.4%) 0.1647 CCI, range (mean ± SD) 0-12 (6.3 ± 2.9) 0-14 (6.1 ± 3.8) 0.8121 ESCI, range (mean ± SD) 0-13 (5.2 ± 2.9) 0-13 (5.3 ± 3.6) 0.8377 Underlying disease (%) HTN/DM 56 (73.7%) 18 (56.3%) 0.0749 CKD/Liver disease 14 (18.4%) 5 (15.6%) 0.7902 HF/Pulmonary HTN 28 (36.8%) 5 (15.6%) 0.0288* Malignancy 15 (19.7%) 11 (34.4%) 0.1042 Dementia 25 (32.9%) 5 (15.6%) 0.0673 Clinical/laboratory profile (%) Major electrolyte/glucose imbalance 29 (38.2%) 6 (18.8%) 0.0491* Acid–base imbalance positivity 37 (48.7%) 17 (53.1%) 0.6734 Respiratory acidosis burden 12 (15.8%) 8 (25.0%) 0.2605 Respiratory alkalosis burden 14 (18.4%) 7 (21.9%) 0.6231 Metabolic acidosis burden 21 (27.6%) 11 (34.4%) 0.4834 Metabolic alkalosis burden 8 (10.5%) 2 (6.25%) 0.7200 High lactate ≥ 2.0 (mmol/L) 21 (27.6%) 15 (46.9%) 0.0527 Severe azotemia, BUN ≥ 90 (mg/dL) 1 (1.3%) 1 (3.1%) 0.5067 BUN/Crea ratio ≥ 20 34 (44.7%) 16 (50.0%) 0.6165 Brain disease condition (%) Recent brain injury 1 19 (25.0%) 9 (28.1%) 0.7351 Chronic brain injury 2 42 (55.3%) 14 (43.8%) 0.2742 Developmental anomaly 3 3 (3.9%) 3 (9.4%) 0.3585 Radiological profile (%) CT or MRI, N = 103 N1 = 74 (missed = 2) N2 = 29 (missed = 3) Hippocampal atrophy 47 (61.8%) 17 (58.6%) 0.3999 Lacunae positivity (%) 16 (21.6%) 7 (24.1%) 0.6452 Lacunae number, median (Q1–Q3, IQR, range) 0 (0–0, 0, 9) 0 (0–0.5, 0.5, 6) 0.8808 CT, N = 101 N1 = 72 (missed = 4) N2 = 29 (missed = 3) CT CSVD score, 0–3, average (SD) 1.47 (1.22) 1.21 (1.15) 0.3062 MRI, N = 71 N1 = 55 (missed = 21) N2 = 16 (missed = 16) MRI total CSVD score, 0–4, average (SD) 1.20 (1.24) 1.19 (1.28) 0.9726 WMHI positivity (%) 23 (41.8%) 7 (43.8%) 0.8905 Fazekas–Deep, 0–3 (SD) 1.35 (1.13) 1.31 (1.20) 0.9225 Fazekas–Periventricular, 0–3 (SD) 1.71 (1.21) 1.69 (1.08) 0.9459 CM positivity (%) 14 (25.5%) 4 (25.0%) 1.0000 CM, deep, median (Q1–Q3, IQR, range) 0 (0–0, 0, 68) 0 (0–0.5, 0.5, 3) 0.9203 CM, cortical, median (Q1–Q3, IQR, range) 0 (0–0, 0, 13) 0 (0–0, 0, 11) 0.8729 EPVS positivity if BG 2–4 (%) 15 (27.3%) 4 (25.0%) 1.0000 EPVS, total = BG + CS (SD) 2.16 (1.36) 2.31 (1.35) 0.7020 EPVS, BG, 0–4 (SD) 1.05 (0.80) 1.31 (1.01) 0.3603 EPVS, CS, 0–4 (SD) 1.13 (0.77) 1.00 (0.82) 0.5838 BG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. IQR: interquartile range. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity. 1 Recent brain injury: recent stroke, brain tumor, or anoxic brain injury 2 Chronic brain injury: old stroke, encephalomalacia, traumatic brain injury, or surgical brain injury 3 Developmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly * p < 0.05 Table legends : Patients with CSID and fever had significantly lower rates of heart failure and pulmonary hypertension and less electrolyte or glucose imbalance than did those without. Nevertheless, no significant differences in neuroimaging markers were observed, suggesting that fever had a neutral effect on seizure risk. Table 5. Clinical and Imaging Differences Between Patients with GPC and GNB Infections with Seizures and CSIDs Pure GPC, N 1 = 18 Pure GNB, N 2 = 53 p value Epidemiology, N = 71 Age, years, range (mean ± SD) 22-104 (66.9 ± 22.1) 25-95 (68.7 ± 16.7) 0.7533 Sex, % male 7 (38.9%) 24 (45.3%) 0.6365 CCI, range (mean ± SD) 0-12 (6.1 ± 3.9) 0-13 (6.8 ± 3.3) 0.5006 ESCI, range (mean ± SD) 0-14 (5.9 ± 4.1) 0-13 (5.3 ± 2.9) 0.5438 Underlying disease (%) HTN/DM 9 (50.0%) 39 (73.6%) 0.0647 CKD/Liver disease 6 (33.3%) 9 (17.0%) 0.1837 HF/Pulmonary HTN 9 (50.0%) 21 (39.6%) 0.4413 Malignancy 5 (27.8%) 12 (22.6%) 0.7514 Dementia 5 (27.8%) 11 (20.8%) 0.5306 Clinical/laboratory profile (%) Major electrolyte/glucose imbalance 3 (16.7%) 15 (28.3%) 0.5313 Recent fever 5 (27.8%) 19 (35.8%) 0.5317 Infection location Pneumonia 11 (61.1%) 25 (47.2%) 0.3067 UTI 4 (22.2%) 26 (49.1%) 0.0465* Septic shock 3 (16.7%) 6 (11.3%) 0.6833 Bacteremia 5 (27.8%) 15 (28.3%) 0.9659 Acid–base imbalance positivity 7 (38.9%) 28 (52.8%) 0.3067 Respiratory acidosis burden 2 (11.1%) 12 (22.6%) 0.4937 Respiratory alkalosis burden 3 (16.7%) 12 (22.6%) 0.7450 Metabolic acidosis burden 6 (33.3%) 14 (26.4%) 0.5729 Metabolic alkalosis burden 0 (0%) 5 (9.4%) 0.3199 High lactate ≥ 2.0 (mmol/L) 4 (22.2%) 18 (34.0%) 0.3521 Severe azotemia, BUN ≥ 90 (mg/dL) 1 (5.56%) 3 (5.7%) 1.0000 BUN/Crea ratio ≥ 20 9 (50.0%) 8 (15.1%) 0.0080** Brain disease condition (%) Recent brain injury 1 6 (33.3%) 11 (20.8%) 0.3414 Chronic brain injury 2 6 (33.3%) 36 (67.9%) 0.0099** Developmental anomaly 3 2 (11.1%) 3 (5.7%) 0.5952 Radiological profile CT or MRI, N = 69 N1 = 18 (missed = 0) N2 = 51 (missed = 2) Hippocampal atrophy 7 (38.9%) 34 (66.7%) 0.0391* Lacunae positivity (%) 4 (22.2%) 19 (37.3%) 0.2448 Lacunae number, median (Q1–Q3, IQR, range) 0 (0–0, 0, 9) 0 (0–1, 1, 6) 0.3628 CT, N = 69 N1 = 18 (missed = 0) N2 = 51 (missed = 2) CT CSVD score, 0–3, average (SD) 1.06 (1.21) 1.47 (1.14) 0.2146 MRI, N = 41 N1 = 10 (missed = 8) N2 = 31 (missed = 22) MRI total CSVD score, 0–4, average (SD) 0.80 (1.32) 1.32 (1.01) 0.2714 WMHI positivity (%) 4 (40.0%) 13 (41.9%) 1.0000 Fazekas–Deep, 0–3 (SD) 1.00 (1.05) 1.48 (1.06) 0.2264 Fazekas–Periventricular, 0–3 (SD) 1.4 (1.35) 1.97 (0.98) 0.2422 CM positivity (%) 1 (10.0%) 8 (25.8%) 0.1274 CM, deep, median (Q1–Q3, IQR, range) 0 (0–0, 0, 12) 0 (0–0, 0, 10) 0.8415 CM, cortical, median (Q1–Q3, IQR, range) 0 (0–0, 0, 1) 0 (0–0, 0, 8) 0.5029 EPVS positivity if BG 2–4 (%) 1 (10.0%) 6 (19.4%) 0.6599 EPVS, total = BG + CS (SD) 1.70 (1.64) 2.23 (1.18) 0.3651 EPVS, BG, 0–4 (SD) 0.70 (0.67) 1.06 (0.68) 0.1585 EPVS, CS, 0–4 (SD) 1.00 (1.05) 1.16 (0.73) 0.6608 Offending antibiotics (Cefepime, imipenem, ertapenem & meropenem) 0 (0%) 6 (11.3%) 0.3072 BG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. GNB: Gram-negative bacillus. GPC: Gram-positive coccus. HF: heart failure. IQR: interquartile range. HTN: hypertension. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity. 1 Recent brain injury: recent stroke, brain tumor, or anoxic brain injury 2 Chronic brain injury: old stroke, encephalomalacia, traumatic brain injury, or surgical brain injury 3 Developmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly * p < 0.05, ** p < 0.01 Table legends : In patients with CSID with positive cultures, the pure GNB subgroup had significantly more UTIs and a less extreme BUN/creatinine ratio than the pure GPC group did. Patients with GPC infections exhibited a significantly lower burden of chronic brain injury and hippocampal atrophy than did those with GNB infections, suggesting that GPC-related seizures may be observed in the setting of less extensive preexisting brain pathology, supporting the proposed “Inverse model” of systemic inflammation and seizure susceptibility. Additional Declarations No competing interests reported. Supplementary Files GraphicalAbstract.jpg SupplementaryMaterial.docx Table 1: Searched medical wards and ICD Codes for seizure inclusion Legends of Supplementary table S1: Supplementary table S1 lists the searched medical wards and ICD codes for seizure inclusion Table 2: Collected Data Legends of Supplementary table S2: Supplementary table S2 lists the detailed items and criteria for collecting data of epidemiology, comorbidity, seizure, epilepsy, infection, brain condition and other seizure triggering related data Table 3: Imaging Study Scoring Legends of Supplementary table S3: Supplementary table S3 lists the detailed items and criteria of imaging study inclusion, hippocampal atrophy scoring, CT CSVD scoring, MRI CSVD scoring and total MRI CSVD scoring Cite Share Download PDF Status: Under Review Version 1 posted Reviewers invited by journal 07 Apr, 2026 Editor invited by journal 18 Mar, 2026 Editor assigned by journal 18 Mar, 2026 Submission checks completed at journal 18 Mar, 2026 First submitted to journal 17 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9149796","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":622534914,"identity":"44e24009-e902-4a53-af3c-1e815f070dee","order_by":0,"name":"Yi-Te Huang","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Yi-Te","middleName":"","lastName":"Huang","suffix":""},{"id":622534919,"identity":"3075205a-9f0e-4ca2-a997-25721614c898","order_by":1,"name":"Tzu-Hsin Huang","email":"","orcid":"","institution":"National Cheng Kung University Hospital, National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Tzu-Hsin","middleName":"","lastName":"Huang","suffix":""},{"id":622534920,"identity":"5fde8f9c-2c1d-4294-8577-410804c7ab77","order_by":2,"name":"Yu-Shiue Chen","email":"","orcid":"","institution":"National Cheng Kung University Hospital, National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Yu-Shiue","middleName":"","lastName":"Chen","suffix":""},{"id":622534923,"identity":"78192419-b850-45db-afdf-389ec4b9a6ec","order_by":3,"name":"Ting-Rong Chen","email":"","orcid":"","institution":"National Cheng Kung University Hospital, National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Ting-Rong","middleName":"","lastName":"Chen","suffix":""},{"id":622534924,"identity":"dccc9915-f02a-454d-8e8a-624e85c8eecd","order_by":4,"name":"Sheng-Hsiang Lin","email":"","orcid":"","institution":"National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Sheng-Hsiang","middleName":"","lastName":"Lin","suffix":""},{"id":622534926,"identity":"99279d45-fe51-46ee-8c13-46c069576bdb","order_by":5,"name":"Chia-Ming Chang","email":"","orcid":"","institution":"National Cheng Kung University Hospital, National Cheng Kung University","correspondingAuthor":false,"prefix":"","firstName":"Chia-Ming","middleName":"","lastName":"Chang","suffix":""},{"id":622534927,"identity":"1b31f14c-0b4b-4341-8b72-ee3aae66318f","order_by":6,"name":"Chin-Wei Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIiWNgGAWjYBACAygtx8DA2HgAJiBBjBZjoJYGZC0GBLUkNgAJ4rSYSyQ/e/il5nD62vbDDQcYd9gZGxxgPnibh+EP2BBswHJGmrmxzLHDudvOJAK1nEk2MzjAlmzNw2CAU4vBjQQzacmG27nbDoC0tB2wMTjAYyYN1JKLW0v6N5CWdLPzD2Fa+L8R0JJjJvmx4XaC2Q2ILUCH8bDh13LmTZk0w7H/httuAG1JbEs2ljzMZmw5x8C4HqeW4+nbJH/UpMmbnU9/+OBjm51h3/HmhzfeVMgZ49ABBsw8MFYCmAs2Cp8GYLT/wC8/CkbBKBgFIx0AACJmXeDl0Ei/AAAAAElFTkSuQmCC","orcid":"","institution":"National Cheng Kung University Hospital, National Cheng Kung University","correspondingAuthor":true,"prefix":"","firstName":"Chin-Wei","middleName":"","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2026-03-17 14:08:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9149796/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9149796/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106901750,"identity":"b077c62a-b3f1-4736-9891-818ddb78ab37","added_by":"auto","created_at":"2026-04-14 15:04:09","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2860686,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Patient Inclusion and Exclusion\u003c/p\u003e\n\u003cp\u003eAfter medical record and \u003cem\u003eInternational Classification of Diseases\u003c/em\u003e code database screening, 533 patients met the inclusion criteria. After manual selection, 169 patients were excluded for having no seizure events, 91 were excluded for having received final diagnoses other than seizure, 48 were excluded for lacking critical information, and 10 were excluded for having received a diagnosis of a central nervous system infection. Ultimately, 216 patient–events were included in the analysis. Figures were created using \u003cem\u003ePowerPoint, Microsoft\u003c/em\u003e for digital illustration\u003c/p\u003e","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9149796/v1/d6c87a8c5e7e1b7ba0bf7a65.jpg"},{"id":106961232,"identity":"5e5fbc96-cb41-4344-b911-ae4d04f83ec1","added_by":"auto","created_at":"2026-04-15 09:24:47","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2134617,"visible":true,"origin":"","legend":"\u003cp\u003eCSID Inclusion and Exclusion Criteria\u003c/p\u003e\n\u003cp\u003eFigure 2 illustrates the inclusion criteria for CSID. The definition emphasizes “concurrent” occurrence of systemic infection and seizure. a. CSID was defined when systemic infection was detected at the time of seizure onset or within 24 hours thereafter, as confirmed by clinical signs, antibiotic initiation, and microbiologic workup. Infections developing more than 24 hours post-seizure were excluded. b. CSID was also defined when seizures occurred during the ongoing treatment of a documented systemic infection. Figures were created using \u003cem\u003ePowerPoint, Microsoft\u003c/em\u003e for digital illustration\u003c/p\u003e\n\u003cp\u003e*Red bar: onset of certain systemic infectious diseases\u003c/p\u003e\n\u003cp\u003e*Green bar: treatment course for certain systemic infectious diseases\u003c/p\u003e\n\u003cp\u003e*Tick mark: systemic infectious disease included as CSID\u003c/p\u003e\n\u003cp\u003e*Cross mark: systemic infectious disease excluded from CSID\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9149796/v1/85d1e55f3d8f89fea51c1f71.jpg"},{"id":106901753,"identity":"e286f530-2039-48f1-9005-67349fd20ebb","added_by":"auto","created_at":"2026-04-14 15:04:09","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":3957631,"visible":true,"origin":"","legend":"\u003cp\u003eHypothesis A: Parallel Increase Versus Hypothesis B: Inverse Model\u003c/p\u003e\n\u003cp\u003ea. In the traditional conception of seizures, in the relationship between seizures and systemic infectious diseases, seizures are considered to be antecedents of diseases or coincidences. When presenting at medical institutions with seizure and concurrent systemic infectious diseases,patients with frailty typically experience more severe infections and more extensive brain pathology than those without frailty do, whereas more robust patients present with milder infection and fewer imaging abnormalities (parallel increase). b. In the newer ”Inverse model” conception of seizures advocated for in the present study, in the relationship between seizures and systemic infectious disease, infections are considered antecedents, seizures sequelae, and infection-related inflammatory cytokines or pathogenic toxins mediators through the breaking of the blood–brain barrier. When presenting at medical institutions with seizures and concurrent systemic infectious diseases, patients with more resilient brains and fewer structural abnormalities tend to present with more severe systemic inflammation when seizures occur, whereas those with more vulnerable brains may develop seizures in association with even mild infections (inverse model). Figures were created using \u003cem\u003eFlaticon\u003c/em\u003eand \u003cem\u003ePowerPoint, Microsoft\u003c/em\u003e for digital illustration.\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9149796/v1/f863f9d19d8e78e43b29c612.jpg"},{"id":106963080,"identity":"b5971276-6d58-477c-bf94-c6c71cad1607","added_by":"auto","created_at":"2026-04-15 09:41:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":10196412,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9149796/v1/4231716f-ba5a-4889-82a4-d29a55c4c212.pdf"},{"id":106960520,"identity":"ffdd3c8f-51a2-4d35-977d-fe77d72cf138","added_by":"auto","created_at":"2026-04-15 09:21:35","extension":"jpg","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":3484142,"visible":true,"origin":"","legend":"","description":"","filename":"GraphicalAbstract.jpg","url":"https://assets-eu.researchsquare.com/files/rs-9149796/v1/065ad5fd735f11f3135cd856.jpg"},{"id":106901752,"identity":"53c37e0c-baa5-4af0-b6f6-9600868afdeb","added_by":"auto","created_at":"2026-04-14 15:04:09","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":44451,"visible":true,"origin":"","legend":"\u003cp\u003eTable 1: Searched medical wards and \u003cem\u003eICD\u003c/em\u003e Codes for seizure inclusion\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLegends of Supplementary table S1:\u003c/strong\u003e Supplementary table S1 lists the searched medical wards and \u003cem\u003eICD\u003c/em\u003e codes for seizure inclusion\u003c/p\u003e\n\u003cp\u003eTable 2: Collected Data\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLegends of Supplementary table S2:\u003c/strong\u003e Supplementary table S2 lists the detailed items and criteria for collecting data of epidemiology, comorbidity, seizure, epilepsy, infection, brain condition and other seizure triggering related data\u003c/p\u003e\n\u003cp\u003eTable 3: Imaging Study Scoring\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLegends of Supplementary table S3:\u003c/strong\u003e Supplementary table S3 lists the detailed items and criteria of imaging study inclusion, hippocampal atrophy scoring, CT CSVD scoring, MRI CSVD scoring and total MRI CSVD scoring\u003c/p\u003e","description":"","filename":"SupplementaryMaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-9149796/v1/617a73e99cd50c14e07944c4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Systemic Infection and Brain Resilience in Patients With Seizures: An Inverse-Model Hypothesis From a Retrospective Cohort Study","fulltext":[{"header":"Key summary points","content":"\u003cp\u003e1. Systemic infections are a frequent and underrecognized contributor to seizure occurrence, particularly in older adults with chronic structural brain lesions.\u0026nbsp;However, the complex interplay between systemic infections and preexisting brain pathology in patients with seizures remains to be elucidated.\u003c/p\u003e\n\u003cp\u003e2. Among patients with concurrent systemic infectious diseases and seizures, an inverse association was observed between infection severity and brain lesion burden, suggesting that milder infections are associated with seizures in structurally vulnerable brains, whereas more severe infections are typically observed in patients with relatively structurally intact brains.\u003c/p\u003e\n\u003cp\u003e3. We proposed an\u0026nbsp;\u0026ldquo;Inverse-Model\u0026rdquo;\u0026nbsp;hypothesis, in which seizures result from the combined effects of systemic inflammation and diminished brain resilience, especially in older patients or those with cognitive impairment.\u003c/p\u003e\n\u003cp\u003e4. Within the\u0026nbsp;\u0026ldquo;Inverse-Model\u0026rdquo;\u0026nbsp;framework, seizure associated with Gram-positive coccal infections occurred under significantly lower brain lesion burdens than those associated with Gram-negative bacilli, suggesting Gram-positive cocci may pose a higher seizure risk.\u003c/p\u003e\n\u003cp\u003e5. In patients presenting with seizures who have dementia or a higher burden of chronic brain lesions, a more thorough investigation for systemic infections is warranted.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eSeizures are a neurological disorder not uncommon among hospitalized patients. Among the various triggers, systemic infections, such as pneumonia, urinary tract infection, cellulitis, or bacteremia, are frequently encountered during seizure evaluation. However, the basic profile and mechanistic influence of these concurrent systemic infectious diseases (CSIDs) on seizure occurrence remain underexplored, especially when central nervous system (CNS) infections are excluded. The literature reports few clinical profiles of patients with CSIDs and seizures [1, 2], and even fewer studies have examined the causal relationships among established seizure-triggering factors. Brain resilience, or the brain\u0026rsquo;s ability to resist systemic stressors, may provide a framework for interpreting these interactions. Brain resilience may decline because of chronic brain lesions caused by hippocampal atrophy [3], neurosurgical intervention [4] traumatic brain injury (TBI) [5] or cerebral small vessel disease (CSVD) [6, 7]. The present study hypothesized that patients with compromised brain resilience may be at greater risk of experiencing seizures than those with uncompromised brain resilience are.\u003c/p\u003e\n\u003cp\u003eFactors linked to infection may also influence seizure susceptibility. Although fever is a well-documented trigger of seizures [8] and febrile infection-related epilepsy syndrome, a rare acute-onset chronic epilepsy syndrome in children [9], its role in adult seizure susceptibility remains unclear. Additionally, pathogens may generally differ in their epileptogenic potential. For example, Gram-positive cocci (GPC), such as Staphylococcus and Streptococcus, produce superantigens that induce toxic shock syndrome [10], whereas lipopolysaccharides or endotoxins\u0026mdash;the principal cell wall components of Gram-negative bacilli (GNB)\u0026mdash;are critical to sepsis and systemic inflammation [11].\u003c/p\u003e\n\u003cp\u003eThe present study described the clinical, imaging, and microbiological profiles of patients with seizures and CSIDs, compared patients with and without CSIDs, and analyzed the differences in infection severity, febrile status, and microbiology among patients with CSIDs. The cohort included only patients hospitalized in 2018, with this limited timeframe imposed to mitigate confounding from hospital admission trends linked to COVID-19.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis retrospective cross-sectional study included patients admitted to National Cheng Kung University Hospital in Tainan, Taiwan, between January 1 and December 31, 2018, for medical treatment who experienced seizures at admission or during hospitalization. Patient data were retrieved using keywords such as (1) \u0026ldquo;seizure,\u0026rdquo; \u0026ldquo;epilepsy,\u0026rdquo; \u0026ldquo;convulsion,\u0026rdquo; and \u0026ldquo;status epilepticus.\u0026rdquo; or (2) \u003cem\u003eInternational Classification of Diseases\u003c/em\u003e (\u003cem\u003eICD\u003c/em\u003e)-\u003cem\u003e9\u003c/em\u003e or\u003cem\u003e ICD -10\u003c/em\u003e codes for seizures in nonsurgical wards were employed through electronic medical records to obtain patients (Supplementary Material, Table S1). Initially, 533 patients were identified with profiles matching the keywords or having relevant \u003cem\u003eICD\u003c/em\u003e codes. After a comprehensive review of these patients\u0026rsquo; medical records, 318 patients were excluded due to the following reasons: absence of a documented seizure event during hospitalization, a final diagnosis inconsistent with seizure, insufficient clinical information to distinguish seizures from other non-epilpetic movement disorders, or confirmed CNS infection. The final analysis included 216 patient\u0026ndash;events (Figure 1).\u003c/p\u003e\n\u003cp\u003eWe collected data on the patients\u0026rsquo; demographic characteristics, seizure semiology, comorbidities, systemic infection status, and radiological findings. The seizure-specific dataset comprised information on seizure category (acute symptomatic or provoked seizures are defined by the presence of an acute systemic or neurological insult like recent stroke, brain tumor, anoxic brain injury, metabolic imbalance, fever, or ASM withdrawal. In contrast, unprovoked seizures are those occurring in the absence of an identifiable clinical trigger) [12], seizure type (focal preserved or impaired consciousness seizure, focal-to-bilateral tonic-clonic seizure and generalized onset seizure) [13], seizure onset location (before or during emergency room visit or during hospitalization), date and sequence of seizures and CSIDs, and antiseizure medication (ASM) use before and after the hospital visit. The ASMs prescribed were levetiracetam, valproate, carbamazepine, oxcarbazepine, phenytoin, topiramate, vigabatrin, clonazepam, lamotrigine, zonisamide, phenobarbital, perampanel, and clobazam. Infection profiles encompassed information regarding vital signs, arterial blood gas, infection site, and microbiological findings. Brain imaging abnormalities identified through computed tomography (CT) or magnetic resonance imaging (MRI) were recorded, as were seizure-triggering factors such as serum sodium, calcium, magnesium levels, blood glucose levels, and offending antimicrobial agents (Supplementary Material, Table S2).\u003c/p\u003e\n\u003cp\u003eThe definition of CSID emphasizes \u0026ldquo;concurrent\u0026rdquo; occurrence of systemic infection and seizure which was defined either (1) when systemic infection was detected at the time of seizure onset or (2) within post-ictal 24 hours for not leaving out atypical presentation of infectious diseases especially in geriatric/frail population [14-16], or (3) when seizures occurred during the ongoing treatment of a documented systemic infection. Evidence of infections was confirmed by clinical signs, antibiotic initiation, and microbiologic workup. Infections developing more than 24 hours post-seizure were excluded. (Figure 2).\u003c/p\u003e\n\u003cp\u003eTo compare comorbidities across groups, we applied the Charlson Comorbidity Index (CCI) and Epilepsy-Specific Comorbidity Index. Comorbidity presence and scores were determined through a comprehensive electronic medical record examination involving consideration of conditions ranging from hypertension and diabetes mellitus to malignancy, either non-metastatic or metastatic, solid or hematologic malignancies categorized by disease status as in remission, stable, or progressive.\u003c/p\u003e\n\u003cp\u003eBecause CNS infection is well established as a cause of seizures, CSIDs were defined as non-CNS infections diagnosed through clinical, laboratory, and imaging findings. They included pneumonia, urinary tract infection, skin or soft-tissue infection (cellulitis, open wound, pressure sore), enteritis/colitis, biliary tract infection, abscess, peritonitis, septic arthritis, bacteremia / septic shock with or without identifiable primary origin. Included patients were stratified into CSID and non-CSID groups. CSID severity was categorized as mild (characterized by the absence of septic shock or bacteremia) or severe (characterized by the presence of septic shock or bacteremia). Seizure-triggering antimicrobial agents, such as carbapenem (imipenem, ertapenem and meropenem) and cefepime, were identified using electronic medical records and assessments made by neurologists or other physicians.\u003c/p\u003e\n\u003cp\u003eWe also analyzed the patients\u0026rsquo; CT and MRI findings. In an image scoring analysis, we considered the evaluation metrics of medial temporal atrophy score [17], modified visual rating scale for CT CSVD score [18], STRIVE (STandards for Reporting and Imaging of Small Vessel Disease) criteria for MRI CSVD [19] score, Fazekas score for white matter hyperintensity (WMHI) [20], and cerebral microbleed (CM) [19], enlarged perivascular space (EPVS) [21], and lacunar stroke [19] scoring criteria. The inclusion criteria and respective scoring rules for each brain imaging item are provided (Supplementary Material, Table S3). Imaging abnormalities were classified into three categories for seizure association analysis: (1) recent brain injury, such as recent stroke, brain tumor, and anoxic brain injury; (2) chronic brain injury, such as old stroke, encephalomalacia, TBI, and surgical brain injury; and (3) developmental anomalies, such as cortical dysplasia, mesial temporal sclerosis, vascular anomaly, and microcephaly.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll statistical analyses were conducted using IBM SPSS Statistics (version 24.0, IBM Corp., Armonk, NY). Continuous variables were initially tested for normality using the Shapiro\u0026ndash;Wilk test. Variables with normal distributions were presented as means \u0026plusmn; standard deviations (SD) and compared using the independent Student\u0026rsquo;s \u003cem\u003et\u003c/em\u003e test. Variables that did not follow a normal distribution were reported as median (interquartile range, IQR) and analyzed using the Mann\u0026ndash;Whitney U test. Categorical variables were expressed as counts and percentages, and between-group comparisons were performed using the Chi-square test or Fisher\u0026rsquo;s exact test where appropriate (e.g., when expected counts were \u0026lt;5).\u003c/p\u003e\n\u003cp\u003eFor subgroup analyses (e.g., mild vs. severe CSID, febrile vs. afebrile, GPC vs. GNB), the same principles were applied: Shapiro\u0026ndash;Wilk testing for continuous variables, followed by appropriate parametric or non-parametric tests depending on the data distribution. Statistical significance was defined as a two-tailed \u003cem\u003ep\u003c/em\u003e value \u0026lt; 0.05. No adjustments were made for multiple comparisons, as this was an exploratory study aimed at hypothesis generation.\u003c/p\u003e\n\u003cp\u003eWhere applicable, missing data were noted, and analysis was conducted on available cases without imputation.\u003c/p\u003e\n\n\u003cp\u003e\u003cstrong\u003eInterrater Reliability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCohen\u0026rsquo;s \u0026kappa; coefficient was used for categorical variables, and intraclass correlation coefficients (ICCs) were used for continuous variables. Two raters (one neurologist, Y.T. Huang and one neuroradiologist, T. R. Chen) scored the images after completing training to do so, and the reliability of their assessments was confirmed by using a random sample comprising 10% of the total imaging studies. The interrater reliability was acceptable for all neuroimaging biomarkers (\u0026kappa;\u0026thinsp;=\u0026thinsp;0.773 for hippocampal atrophy; ICC\u0026thinsp;=\u0026thinsp;0.857 for lacune number; ICC\u0026thinsp;=\u0026thinsp;0.835 for CT CSVD score; ICC\u0026thinsp;=\u0026thinsp;0.750 for Fazekas score, deep WMHI; ICC\u0026thinsp;=\u0026thinsp;0.866 for Fazekas score, periventricular WMHI; ICC\u0026thinsp;=\u0026thinsp;0.833 for deep CMs ; ICC\u0026thinsp;=\u0026thinsp;0.870 for cortical CMs; ICC = 0.727 for basal ganglion EPVS; and ICC\u0026thinsp;=\u0026thinsp;0.886 for centrum semiovale EPVS).\u003c/p\u003e\n\n"},{"header":"Results","content":"\u003cp\u003eAmong the 216 included patients, 210 (97.2%) of the seizures were classified as acute symptomatic seizures.\u0026nbsp;157 (72.6%) had CSIDs, and 59 did not. The patients with CSIDs were older (65.9 \u0026plusmn; 18.7 years vs.\u0026nbsp;56.3 \u0026plusmn; 20.4\u0026nbsp;years, \u003cem\u003ep\u003c/em\u003e = 0.0020),\u0026nbsp;had a higher prevalence of acute symptomatic seizures (100% vs. 89.8%, \u003cem\u003ep\u003c/em\u003e = 0.0003) and\u0026nbsp;generalized seizures (55.8% vs.\u0026nbsp;37.1%, \u003cem\u003ep\u003c/em\u003e = 0.0386), had a lower prevalence of malignancy (26.6% vs.\u0026nbsp;44.5%, \u003cem\u003ep\u003c/em\u003e = 0.0056), and were more likely to have dementia (25.3% vs.\u0026nbsp;9.7%, \u003cem\u003ep\u003c/em\u003e = 0.0180) relative to those without CSIDs.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp;\u0026nbsp;Infection-related manifestations, specifically, peri-ictal fever (35.0% vs. 8.5%, \u003cem\u003ep\u003c/em\u003e = 0.0001), septic shock (15.3% vs. 1.7%, \u003cem\u003ep\u003c/em\u003e = 0.0054), and acid\u0026ndash;base imbalance (respiratory acidosis, alkalosis, or metabolic acidosis, 53.9% vs. 23.7%, \u003cem\u003ep\u003c/em\u003e = 0.0001) were more frequent in the CSID group. By contrast, recent brain injuries (stroke, brain tumors, and anoxic brain injury) were more common in the non-CSID group (47.5% vs. 27.4%, \u003cem\u003ep\u003c/em\u003e = 0.0051). Chronic brain injuries, such as old stroke, encephalomalacia, TBI, and\u0026nbsp;surgical brain\u0026nbsp;injury, were more prevalent in the CSID group (50.3% vs.\u0026nbsp;30.5%, \u003cem\u003ep\u003c/em\u003e = 0.0091).\u003c/p\u003e\n\u003cp\u003eRadiological comparisons revealed that the patients with CSIDs were more likely to exhibit hippocampal atrophy (62.3% vs. 44.1%, \u003cem\u003ep\u003c/em\u003e = 0.0167), have higher CT CSVD scores (1.30 \u0026plusmn; 1.16 vs. 0.84 \u0026plusmn; 1.11, \u003cem\u003ep\u003c/em\u003e = 0.0097), and have higher MRI CSVD scores (1.18 \u0026plusmn; 1.22 vs. 0.74 \u0026plusmn; 1.11, \u003cem\u003ep\u003c/em\u003e = 0.0373) than those without CSIDs were. The MRI-specific features that differed significantly between the groups were deep WMHI (1.22 \u0026plusmn; 1.07 vs. 0.81 \u0026plusmn; 0.99, \u003cem\u003ep\u003c/em\u003e = 0.0265), periventricular WMHI (1.63 \u0026plusmn; 1.14 vs. 1.09 \u0026plusmn; 1.16, \u003cem\u003ep\u003c/em\u003e = 0.0093), and basal ganglion EPVS (1.07 \u0026plusmn; 0.84 vs. 0.77 \u0026plusmn; 0.76, \u003cem\u003ep\u003c/em\u003e = 0.0310). No significant differences were observed between the groups in survival rates and ASM prescriptions (Table 1).\u003c/p\u003e\n\u003cp\u003eTo investigate the observed pattern of more frequent recent brain injury in the non-CSID group and more frequent chronic brain injury in the CSID group, we stratified the patients with CSIDs into mild (characterized by the absence of septic shock or bacteremia) and severe (characterized by the presence of septic shock or bacteremia) subgroups. This classification enabled us to assess whether infection severity was correlated, positively or negatively, with the extent of neuroimaging abnormalities. The conventional perspective regarding CSIDs and seizures suggests that patients with frailty experience more severe infections and more extensive brain pathology, whereas more robust patients have milder infections and exhibit fewer imaging abnormalities. However, the present study proposed an alternative perspective: In patients with more resilient brains and fewer structural abnormalities, seizures tended to be associated with more severe systemic inflammation; conversely, in those with more vulnerable brains, seizures were observed even in the presence of mild infections.\u0026nbsp;This inverse\u0026nbsp;association\u0026nbsp;suggests that\u0026nbsp;cumulated\u0026nbsp;brain pathologies weaken brain resilience and predispose individuals to seizures (Figure\u0026nbsp;3).\u003c/p\u003e\n\u003cp\u003eAmong the patients with CSIDs, those with severe infections (septic shock or bacteremia, \u003cem\u003en\u003c/em\u003e = 49) had higher CCI values (7.5 \u0026plusmn; 3.6 vs. 6.3 \u0026plusmn; 3.2, \u003cem\u003ep\u003c/em\u003e = 0.0398) and a higher prevalence of heart failure or pulmonary hypertension (53.1% vs. 30.6%, \u003cem\u003ep\u003c/em\u003e = 0.0070). Additionally, these patients had a lower burden of deep WMHI than the mild CSID group did (0.85 \u0026plusmn; 0.78 vs. 1.34 \u0026plusmn; 1.13, \u003cem\u003ep\u003c/em\u003e = 0.0190), as well as less WMHI overall (19.2% vs. 42.3%, \u003cem\u003ep\u003c/em\u003e = 0.0365) (Table 2), indicating an inverse association between infection severity and chronic brain lesion burden. To adjust for potential confounding effects from multiple variables showing significance in univariate analysis, variables from Table 2 with p \u0026lt; 0.1\u0026mdash;including CCI, ESCI, HF/pulmonary HTN, recent fever, respiratory alkalosis burden, WMHI positivity, and Fazekas score-Deep\u0026mdash;were entered into a multivariable logistic regression model. The analysis revealed that only recent fever (adjusted OR: 0.25, \u003cem\u003ep\u003c/em\u003e = 0.0143) and severe Fazekas score-Deep scoring 2-3 (adjusted OR: 10.2, \u003cem\u003ep\u003c/em\u003e = 0.0448) remained independently associated with mild CSID (Table 3). These findings reinforce that among seizure patients with comorbid infections, more severe chronic brain changes are associated with milder infection severity, and vice-versa.\u003c/p\u003e\n\u003cp\u003eTo explore the association between CSIDs\u0026nbsp;and seizure occurrence noted in the radiological findings, we investigated the underlying factors contributing to the seizures experienced by the patients with CSIDs\u0026nbsp;to find the driving factors\u0026nbsp;behind.\u0026nbsp;We speculate that infection may precipitate seizures through either host immune response or pathogen-derived antigens or toxins, and fevers reflect a host immune response.\u0026nbsp;And\u0026nbsp;Gram stain classification can be employed as an objective and practical approach to evaluating the ictogenic potential of different pathogen classes.\u003c/p\u003e\n\u003cp\u003eAs an expression of host immune, in febrile status analysis, mild CSID patients were divided into afebrile (\u003cem\u003eN\u003c/em\u003e = 76) and febrile (\u003cem\u003eN\u003c/em\u003e = 32) subgroups. The patients with severe CSIDs were excluded to avoid confounding effects from septic shock and bacteremia.\u003c/p\u003e\n\u003cp\u003eThe patients with fever had lower rates of heart failure and pulmonary hypertension (15.6% vs. 36.8%, \u003cem\u003ep\u003c/em\u003e = 0.0288) and reduced major electrolyte or glucose imbalance (18.8% vs. 38.2%, \u003cem\u003ep\u003c/em\u003e = 0.0491) than those without fever did. However, no significant differences in neuroimaging markers were observed (Table 4), suggesting that fever had a neutral effect when mediated by radiological abnormality burden on seizure risk in this adult cohort. But still, an analogous inverse relationship existed between febrile status and major electrolyte / glucose imbalance severity.\u003c/p\u003e\n\u003cp\u003eWe further compared the subgroups of patients with CSIDs with positive cultures for GPC and GNB. The GNB subgroup had a significantly higher incidence of urinary tract infections (49.1% vs. 22.2%, \u003cem\u003ep\u003c/em\u003e = 0.0465) and lower extreme blood urea nitrogen/creatinine ratios (15.1% vs. 50.0%, \u003cem\u003ep\u003c/em\u003e = 0.0080) than the GPC subgroup did. The patients with GPC infections exhibited a lower burden of chronic brain injury (33.3% vs. 67.9%, \u003cem\u003ep\u003c/em\u003e = 0.0099) and less hippocampal atrophy (38.9% vs. 66.7%, \u003cem\u003ep\u003c/em\u003e = 0.0391) than did those with GNB infections (Table 5). These findings suggest that seizures linked to GPCs may occur even in the absence of extensive preexisting brain pathology, which supports the present study\u0026rsquo;s \u0026rdquo;Inverse model\u0026rdquo; of systemic inflammation and seizure susceptibility.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study identified a high prevalence of CSIDs among the patients hospitalized with ongoing seizures. This finding indicates that CSIDs may be an independent seizure-precipitating factor rather than a coincidental comorbidity or sequela of seizures, particularly in individuals with reduced brain resilience due to chronic structural abnormalities.\u003c/p\u003e\n\u003cp\u003eTo enhance the accuracy of identifying patients with infectious diseases preceding seizures, this study included not only those who showed infectious signs and symptoms at the time of seizure presentation, but also those who developed such features within the first 24 hours postictally. This approach reflects real-world clinical practice, where infectious disease-related signs and symptoms (e.g., fever) often fluctuate and may not perfectly coincide precisely with seizure onset [16]. Some concurrent infectious diseases were noticed shortly after seizure management. Thus, this extended time period is especially crucial for elderly patients, in which population infectious signs and symptoms are often blunted or initially unnoticed [14, 15]. As for the selection of 24-hour window, rather than a narrower (e.g., 12 hours) or broader (e.g., 48-hour) timeframe, it was based on the pathophysiology of postictal complications. Aspiration-related pneumonia, a common sequela following seizures typically manifests with symptoms including cough, fever, purulent sputum, and dyspnea over several days or weeks rather than within hours [22, 23], which were resulted from seizures and poor consciousness in this study setting. This time window was aimed to minimize the potential confounding influence of seizure-induced infections.\u003c/p\u003e\n\u003cp\u003eThe patients with CSIDs were older and more frequently had received a diagnosis of dementia, consistent with epidemiological patterns linking aging to increased susceptibility to infection [24], increased prevalence of dementia [25], and increased seizure risk in individuals with neurodegenerative conditions [26]. Although non-CNS systemic infections and dementia are not direct epileptogenic factors, both may reduce seizure thresholds by modulating systemic inflammation and disrupting neural homeostasis [26, 27].\u003c/p\u003e\n\u003cp\u003eIn the patients with CSIDs in the present study, infection-related features such as peri-ictal fever and acid\u0026ndash;base imbalance occurred frequently, indicating an ongoing systemic inflammatory response. These patients also presented with fewer recent but more chronic brain injuries and exhibited higher burdens of CSVD and hippocampal atrophy, which are radiological markers associated with diminished brain resilience [3, 6, 7]. By contrast, the patients without CSIDs were more likely to present with seizure triggers such as acute stroke [28] and brain tumors [29].\u003c/p\u003e\n\u003cp\u003eTo evaluate the temporal and causal relationships between infection and seizures, we stratified the patients with CSIDs into mild and severe subgroups. Although the conventional understanding of seizures and CSIDs suggests that more severe systemic illness coincides with more extensive brain pathology, our patients with severe CSIDs (septic shock or bacteremia) had significantly lower CSVD burdens than did those with milder infections. This inverse association suggests that more severe systemic inflammation is associated with seizure occurrence in patients with intact brains, whereas even minor systemic disturbances may be associated with seizure occurrence in patients with substantial brain pathology. These results support the proposed \u0026rdquo;Inverse-Model\u0026rdquo; hypothesis, in which seizures result from the combined effects of systemic inflammatory stress and preexisting brain vulnerability, especially in elderly or patients comorbid with dementia [7, 10, 11, 30-33].\u003c/p\u003e\n\u003cp\u003eIn comparisons of the incidence of comorbidities between the groups, heart failure and pulmonary hypertension occurred more frequently in the severe CSID group than in the mild CSID group. The mechanism by which heart failure induces seizures may involve circulatory anoxia [34] or seizure-induced asystole presenting as syncope, which is often indistinguishable from seizures with impaired awareness [35]. Although heart failure contributes to CSVD, it typically results in cerebral cortical microinfarcts [36], which differ from deep white matter lesions in this study. Additionally, the severe CSID group exhibited a lower CSVD burden than the non-CSVID group did. This finding may be attributable to the lack of an association between pulmonary hypertension and seizures and CSVD: Pulmonary hypertension has only been linked to seizures in isolated case reports [37, 38], and research has documented no association between pulmonary hypertension and CSVD [39]. Therefore, although heart failure and pulmonary hypertension were more prevalent in the severe CSID group in the current study, these conditions are unlikely to confound the observed inverse association between infection severity and chronic brain lesion burden.\u003c/p\u003e\n\u003cp\u003eNotably, the patients with CSIDs linked to GPC exhibited significantly lower chronic brain lesion burden than those with CSIDs linked to GNB did. The literature in this field has primarily addressed Staphylococcal or Streptococcal toxic shock syndrome, which is characterized by multiple organ failure (respiratory, renal, and hepatic failure; skin necrosis; and coagulopathy) due to diffuse capillary leakage. Additionally, because the neurological manifestations of CSIDs have not been well described [40], whether diffuse capillary leakage in the CNS increases susceptibility to inflammatory mediators and the risk of subsequent seizures when brain integrity is uncompromised remains unknown. Nevertheless, our findings support the hypothesis that certain pathogens possess higher intrinsic ictogenic toxicity and epileptogenic potential than others do. However, these observations should be interpreted with caution; due to the relatively small sample size, our analysis may have limited statistical power and an increased risk of type I error. Therefore, these results should be considered preliminary and require validation in larger, multicenter cohorts.\u003c/p\u003e\n\u003cp\u003eWe also evaluated the association of fever with seizures. Although fever\u0026rsquo;s role in childhood seizures is well established [8, 9] and one study indicated that cytokines linked to fever, such as interleukin-1\u0026beta; and interleukin-6, may predispose children to febrile seizures [41], no significant radiological differences were observed between the afebrile and febrile subgroups in the present study. This result suggests that fever may not function as a primary seizure trigger in adults by the proposed \u0026ldquo; Inverse model\u0026rdquo; in the radiological standpoint. But still there found an analogy between febrile status and prevalence of major electrolyte / glucose imbalance, which is beyond the scope of this study. This finding is particularly notable because older adults with dementia or structural brain lesions may not exhibit typical infection symptoms [14-16].\u003c/p\u003e\n\u003cp\u003eThis study has several limitations. First, the retrospective cross-sectional design restricted the conclusions to associations rather than causal relationships. Furthermore, the retrospective nature of the study may affect data precision. This is exemplified by the discrepancy where the recorded number of patients with a known epilepsy history was lower than those already receiving ASMs, suggesting an underestimation of the true prevalence of epilepsy history. Consequently, we did not perform a subgroup analysis based on the presence or absence of a prior epilepsy history. Additionally, a higher proportion of generalized tonic-clonic seizures (GTCS) was observed. We speculate that this is ascribed to the fact that seizure semiology was primarily documented based on witness accounts, most of whom were family members rather than medical professionals, potentially leading to the under-reporting of more subtle seizure types. Second, results in this study were derived from hospitalized patients and focused on non-surgical ward patients with acute symptomatic seizures rather than unprovoked seizures, which may limit the generalizability of the results to the epilepsy population. Only a minority (19.4%) of patients had prior history of epilepsy (18.6% for non-CSID, 19.7% for CSID), raising the potential for selection bias, such as Berkson\u0026rsquo;s paradox. Third, while considerable effort was made to rigorously define and distinguish cases with CSIDs, challenges remain. The inclusion criteria allowed for infectious signs and diagnoses identified during the pre-ictal, ictal, or within 24 hours post-ictal period, this approach cannot fully eliminate the possibility that some infections may have been triggered or exacerbated by the seizures, such as seizure-induced aspiration pneumonia. Despite this limitation, the 24-hour window was selected as a clinically reasonable approach to enhance diagnostic sensitivity while minimizing reverse causation. Furthermore, due to the retrospective design and the resulting missing data, standard clinical scoring systems such as APACHE II or qSOFA could not be applied for CSID severity grading. Nonetheless, our simplified classification based on septic shock and bacteremia offers greater clinical utility and ease of application in real-world practice.\u003c/p\u003e\n\u003cp\u003eFourth, missing data and a relatively small sample size may also limit the generalizability of the findings. Finally, the observations from MRIs and microbiological evaluations did not reach significance and remained suggestive, likely because the high cost of MRIs and the low yield rate of current culture techniques render such evaluations difficult to obtain large sample size [42]. Despite these limitations, the current findings support our multiple-hit hypotheses regarding the interaction between systemic inflammation and neuronal vulnerability and its implications for seizure risk assessment and targeted interventions. Future prospective studies are warranted to further clarify the temporal relationship between systemic infections and seizure onset, and to determine whether timely infection recognition and appropriate treatment may help reduce seizure burden in at-risk populations, particularly older adults with underlying brain vulnerability such as cerebral small vessel disease, chronic brain lesion or dementia. \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eSystemic infections frequently contribute to seizure occurrence and remain underrecognized, particularly in older adults with chronic brain lesions. Our findings support a multiple-hit hypothesis, in which seizures result from the combined effects of systemic inflammation and diminished brain resilience. The observed inverse association between infection severity and brain lesion burden suggests that milder infections were associated with seizures in patients with vulnerable brains, whereas more severe infections are associated with seizure occurrence in patients with structurally intact brains. GPC may also pose a higher seizure risk than GNB do. These findings underscore the importance of infection screening in older patients and those with cognitive impairment presenting with seizures, even in the absence of fever. Nevertheless, a similar analogy was also found between febrile status and prevalence of major electrolyte / glucose imbalance, rather than radiological abnormality burden. Further studies are required to validate this model and obtain findings that can inform targeted prevention strategies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eASM: antiseizure medication\u003c/p\u003e\n\u003cp\u003eBG: basal ganglion\u003c/p\u003e\n\u003cp\u003eBUN: blood urea nitrogen\u003c/p\u003e\n\u003cp\u003eCCI: Charlson Comorbidity Index\u003c/p\u003e\n\u003cp\u003eCKD: chronic kidney disease\u003c/p\u003e\n\u003cp\u003eCM: cerebral microbleed\u003c/p\u003e\n\u003cp\u003eCNS: central nervous system\u003c/p\u003e\n\u003cp\u003eCrea: creatinine\u003c/p\u003e\n\u003cp\u003eCS: centrum semiovale\u003c/p\u003e\n\u003cp\u003eCSVD: cerebral small vessel disease\u003c/p\u003e\n\u003cp\u003eCT: computed tomography\u003c/p\u003e\n\u003cp\u003eDM: diabetes mellitus\u003c/p\u003e\n\u003cp\u003eESCI: Epilepsy-Specific Comorbidity Index\u003c/p\u003e\n\u003cp\u003eEPVS: enlarged perivascular space\u003c/p\u003e\n\u003cp\u003eGNB: Gram-negative bacilli\u003c/p\u003e\n\u003cp\u003eGPC: Gram-positive cocci\u003c/p\u003e\n\u003cp\u003eHF: heart failure\u003c/p\u003e\n\u003cp\u003eHTN: hypertension\u003c/p\u003e\n\u003cp\u003eICC: intraclass correlation coefficient\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eICD\u003c/em\u003e: \u003cem\u003eInternational Classification of Diseases\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eIQR: interquartile range\u003c/p\u003e\n\u003cp\u003eMRI: magnetic resonance imaging\u003c/p\u003e\n\u003cp\u003eOR: odds ratio\u003c/p\u003e\n\u003cp\u003eSD: standard deviation\u003c/p\u003e\n\u003cp\u003eSTRIVE: STandards for Reporting and Imaging of Small Vessel Disease\u003c/p\u003e\n\u003cp\u003eTBI: traumatic brain injury\u003c/p\u003e\n\u003cp\u003eWMHI: white matter hyperintensity\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe authors confirm that the manuscript is not being considered for publication by another journal, nor will it be submitted elsewhere while under consideration by this journal, and has not been published previously (partly or in full).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the institutional review board of National Cheng Kung University Hospital (Approval number: A-ER-111-475). The requirement to obtain informed consent was not applicable because of the retrospective study design and the use of deidentified medical records and imaging data. For these reasons, the requirement to obtain written informed consent from the patients was waived.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study does not contain any individual person\u0026rsquo;s data in any form (including individual details, images, or videos).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported in part by grants from the National Science and Technology Council (112-2314-B-006 -047 -MY2), Taiwan. None of the funding sources had any role in the design, analysis, data interpretation, preparation, review, or manuscript approval of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor\u003c/strong\u003e\u003cstrong\u003es\u0026rsquo;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ec\u003c/strong\u003e\u003cstrong\u003eontributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe corresponding authors of this manuscript had full access to all the data in the study and took responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Y.T. Huang, C.M. Chang, and C.W. Huang. Acquisition of data: Y.T. Huang. Manuscript drafting: Y.T. Huang and C.W. Huang. Digital plotting: Y.T. Huang. Image scoring: Y.T. Huang and T.R. Chen. Statistical consultation: S.H. Lin and T.R. Chen. Critical revision of the manuscript for important intellectual content: Y.T. Huang, T.H. Huang, Y.S. Chen, T.R. Chen, S.H. Lin, C.M. Chang, and C.W. Huang. Study supervision: C.W. Huang. All authors read and approved the final manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledg\u003c/strong\u003e\u003cstrong\u003ee\u003c/strong\u003e\u003cstrong\u003ements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript was edited by Wallace Academic Editing.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e1. Y.T. Huang, MD: Neurologist and geriatrician\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan\u003c/p\u003e\n\u003cp\u003e2. T.H. Huang, MD: Neurologist\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan\u003c/p\u003e\n\u003cp\u003e3. Y.S. Chen: Nurse practitioner of Neurology\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan\u003c/p\u003e\n\u003cp\u003e4. T. R. Chen, MD: Radiologist with a subspecialty in neuroradiology\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan\u003c/p\u003e\n\u003cp\u003e5. S.H. Lin, Professor: Epidemiologist and statistician\u003c/p\u003e\n\u003cp\u003eE-mail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.35, Siao dong Road, North Dist., Tainan 70457, Taiwan\u003c/p\u003e\n\u003cp\u003e6. C.M. Chang, Associate Professor: Geriatrician and infectious diseases specialist\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan\u003c/p\u003e\n\u003cp\u003e7. C.W. Huang, Professor: Neurologist\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003cp\u003eAddress: No.138, Sheng Li Road, North Dist., Tainan 70428, Taiwan\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAydin S, \u0026Ouml;zdemir C, G\u0026uuml;nd\u0026uuml;z A, Kiziltan ME. Seizures in patients with respiratory disease-a retrospective single center study. Arq Neuropsiquiatr. 2020;78:247\u0026ndash;54 DOI: 10.1590/0004-282x20190196.\u003c/li\u003e\n\u003cli\u003eAlessandri F, Badenes R, Bilotta F. Seizures and sepsis: a narrative review. Journal of Clinical Medicine. 2021;10(5):1041 DOI: 10.3390/jcm10051041.\u003c/li\u003e\n\u003cli\u003eBelleville S, Mellah S, Cloutier S, et al. Neural correlates of resilience to the effects of hippocampal atrophy on memory. NeuroImage: Clinical. 2021;29:102526 DOI: 10.1016/j.nicl.2020.102526.\u003c/li\u003e\n\u003cli\u003ePeterson KA, Savulich G, Jackson D, Killikelly C, Pickard JD, Sahakian BJ. 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Chest. 1997;112(3):840\u0026ndash;2 DOI: 10.1378/chest.112.3.840.\u003c/li\u003e\n\u003cli\u003eIzzo A, McSweeney J, Kulik T, Khatwa U, Kothare SV. \u0026ldquo;Nocturnal seizures\u0026rdquo; in idiopathic pulmonary arterial hypertension. J Clin Sleep Med. 2013;9(10):1091\u0026ndash;2 DOI: 10.5664/jcsm.3094.\u003c/li\u003e\n\u003cli\u003eYuan P, Li J, Liu J, et al. Cognitive dysfunction in patients with pulmonary hypertension. Am J Respir Crit Care Med. 2022;206(10):1289\u0026ndash;93 DOI: 10.1164/rccm.202204-0726LE.\u003c/li\u003e\n\u003cli\u003eCommons RJ, Smeesters PR, Proft T, Fraser JD, Robins-Browne R, Curtis N. Streptococcal superantigens: categorization and clinical associations. Trends Mol Med. 2014;20(1):48\u0026ndash;62 DOI: 10.1016/j.molmed.2013.10.004.\u003c/li\u003e\n\u003cli\u003eKwon A, Kwak BO, Kim K, et al. Cytokine levels in febrile seizure patients: A systematic review and meta-analysis. 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Arch Intern Med. 2004;164(16):1807\u0026ndash;11 DOI: 10.1001/archinte.164.16.1807.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e Comparison of Demographic, Clinical, and Radiological Features Between Patients with Seizures with and without CSIDs\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;Non-CSID, \u003cem\u003eN\u003c/em\u003e1 = 59\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;CSID, \u003cem\u003eN\u003c/em\u003e2 = 157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eEpidemiology, \u003cem\u003eN\u003c/em\u003e = 216\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eAge, years, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e18-96 (56.3 \u0026plusmn; 20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e18-104 (65.9 \u0026plusmn; 18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0020*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eSex, % male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e30 (50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e78 (49.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.8786\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0-13 (5.9 \u0026plusmn; 3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0-14 (6.6 \u0026plusmn; 3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2190\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eESCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0-16 (5.6 \u0026plusmn; 4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0-14 (5.6 \u0026plusmn; 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.9828\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003ePast history of epilepsy (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e11 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e31 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.8554\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eSeizure category (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eAcute symptomatic (provoked)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e53 (89.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e157 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0003***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eUnprovoked\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e6 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0003***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eSeizure semiology (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eGeneralized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e23 (37.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e86 (55.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0386*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eFocal-to-bilateral tonic-clonic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e6 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e13 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.6623\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eFocal impaired consciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e22 (35.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e45 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2220\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eFocal preserved consciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e8 (12.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e13 (8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2433\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eUnderlying disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eHTN/DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e31 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e103 (66.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0780\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCKD/Liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e14 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e33 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.6672\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eHF/Pulmonary HTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e20 (32.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e59 (38.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.6167\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMalignancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e27 (44.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e41 (26.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0056**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e6 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e39 (25.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0180*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eClinical/laboratory profile (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMajor electrolyte/glucose imbalance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e14 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e46 (29.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.4154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eRecent fever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e55 (35.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eSeptic shock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e1 (1.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e24 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0054**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eAcid\u0026ndash;base imbalance positivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e14 (23.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e83 (53.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0001***\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eRespiratory acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e3 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e26 (16.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0275*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eRespiratory alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e38 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0099**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMetabolic acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e7 (11.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e47 (29.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0063**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMetabolic alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e6 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e15 (9.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.8918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eHigh lactate \u0026ge; 2.0 (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e13 (22.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e56 (35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0555\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eSevere azotemia, BUN \u0026ge; 90 (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e3 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e6 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.7074\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eBUN/Crea ratio \u0026ge; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e29 (49.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e77 (49.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.9887\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eBrain disease condition (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eRecent brain injury\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e28 (47.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e43 (27.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0051**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eChronic brain injury\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e18 (30.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e79 (50.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0091**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eDevelopmental anomaly\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e5 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e9 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.5362\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eRadiological profile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCT or MRI, \u003cem\u003eN\u0026nbsp;\u003c/em\u003e= 210\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003eN1 = 59 (missed = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003eN2 = 151 (missed = 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eHippocampal atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e26 (44.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e94 (62.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0167*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eLacunae positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e9 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e37 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.1452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eLacunae number, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCT, \u003cem\u003eN\u003c/em\u003e = 204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003eN1 = 56 (missed = 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003eN2 = 148 (missed = 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCT CSVD score, 0\u0026ndash;3, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.84 (1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.30 (1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0097**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMRI, \u003cem\u003eN\u003c/em\u003e = 144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003eN1 = 47 (missed = 12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003eN2 = 97 (missed = 60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMRI total CSVD score, 0\u0026ndash;4, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.74 (1.11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.18 (1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0373*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eWMHI positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e13 (27.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e36 (37.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2616\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Deep, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.81 (0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.22 (1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0265*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Periventricular, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e1.09 (1.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.63 (1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0093**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCM positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e6 (12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e24 (24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0971\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCM, deep, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.3271\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eCM, cortical, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.6171\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eEPVS positivity if BG 2\u0026ndash;4 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e7 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e25 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.1409\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eEPVS, total = BG + CS, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e1.70 (1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e2.18 (1.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0525\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eEPVS, BG, 0\u0026ndash;4, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.77 (0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.07 (0.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.0310*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eEPVS, CS, 0\u0026ndash;4, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.94 (0.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.11 (0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2128\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eMortality or critical discharge/transfer to other facility (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e9 (15.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e27 (17.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.7328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eASM status for survivors, \u003cem\u003eN\u003c/em\u003e = 180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003eN1 = 50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003eN2 = 130\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003ePast history of epilepsy among survivors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e9 (18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e29 (22.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.5259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eASM number (before admission) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e0 (Non-user)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e38 (76.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e87 (66.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eUser\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e12 (24.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e43 (33.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2364\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e4 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e22 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.1586\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e4 (8.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e15 (11.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.5960\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e2 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e4 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.6704\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e1 (2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.4795\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e1 (2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2778\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eAverage ASM class number (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.56 (1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0.56 (0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.9937\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eASM number (discharge) (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e0 (Non-user)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e8 (16.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e14 (10.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.3372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eUser\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e42 (84.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e116 (89.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.3372\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e30 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e72 (55.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.5757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e7 (14.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e27 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.2987\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e3 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e9 (6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e5 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.3242\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e2 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e2 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.1871\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eAverage ASM class number (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e1.30 (1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e1.45 (1.09)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.4363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 40.6028%;\"\u003e\n \u003cp\u003eAdded on average ASM class number (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.1631%;\"\u003e\n \u003cp\u003e0.74 (0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.695%;\"\u003e\n \u003cp\u003e0.92 (0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.539%;\"\u003e\n \u003cp\u003e0.1355\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eASM: antiseizure medication. BG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. IQR: interquartile range. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eRecent brain injury: recent stroke, brain tumor, or anoxic brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eChronic brain injury: old stroke, encephalomalacia, traumatic brain injury, or surgical brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDevelopmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly\u003c/p\u003e\n\u003cp\u003e* \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01, *** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable legends\u003c/strong\u003e: Patients with CSIDs had significantly more prevalent hippocampal atrophy, severe CT CSVD scores, and severe MRI CSVD scores than did those without CSIDs. The features that differed significantly on MRI were deep white matter hyperintensity, periventricular white matter hyperintensity, and basal ganglion EPVS. No significant differences were observed between groups in survival rates and ASM prescriptions.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Clinical and Radiological Profiles of Patients with Seizures with Mild versus Severe CSIDs\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003eWithout septic shock or bacteremia, \u003cem\u003eN\u003c/em\u003e1 = 108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003eWith septic shock or bacteremia, \u003cem\u003eN\u003c/em\u003e2 = 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eEpidemiology, \u003cem\u003eN\u003c/em\u003e = 157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eAge, years, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e22-95 (65.7 \u0026plusmn; 18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e18-104 (66.3 \u0026plusmn; 19.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.8493\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eSex, % male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e53 (49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e25 (51.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.8212\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e0-14 (6.3 \u0026plusmn; 3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e0-14 (7.5 \u0026plusmn; 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0398*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eESCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e0-13 (5.2 \u0026plusmn; 3.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e1-14 (6.3 \u0026plusmn; 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0722\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003ePast history of epilepsy (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e23 (21.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e8 (16.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.4686\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eSeizure semiology (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eGeneralized\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e59 (54.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e27 (55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9561\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eFocal-to-bilateral tonic-clonic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e10 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e3 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.7558\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eFocal impaired consciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e30 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e15 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.7159\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eFocal preserved consciousness\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e9 (8.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e4 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eUnderlying disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eHTN/DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e74 (68.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e29 (59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.2539\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCKD/Liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e20 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e14 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.1565\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eHF/Pulmonary HTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e33 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e26 (53.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0070**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eMalignancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e26 (24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e15 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.3875\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e30 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e9 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.2061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eClinical/laboratory profile (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eMajor electrolyte/glucose imbalance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e34 (31.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e11 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.2462\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eRecent fever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e32 (29.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e24 (49.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0190*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eAcid\u0026ndash;base imbalance positivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e54 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e29 (59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.2855\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eRespiratory acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e20 (18.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e6 (12.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.3272\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eRespiratory alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e21 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e17 (34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0387*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eMetabolic acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e32 (29.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e15 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eMetabolic alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e10 (9.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e5 (10.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eHigh lactate \u0026ge; 2.0 (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e36 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e20 (40.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.3644\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eSevere azotemia, BUN \u0026ge; 90 (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e2 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e4 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0765\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eBUN/Crea ratio \u0026ge; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e50 (46.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e27 (55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.3065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eBrain disease condition (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eRecent brain injury\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e28 (25.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e15 (30.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.5418\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eChronic brain injury\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e61 (56.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e28 (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9382\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eDevelopmental anomaly\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e6 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e3 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eRadiological profile (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCT or MRI, \u003cem\u003eN\u003c/em\u003e = 151\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003eN1 = 103 (missed = 5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003eN2 = 48 (missed = 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eHippocampal atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e64 (62.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e29 (60.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.8397\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eLacunae positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e23 (22.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e15 (31.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.2395\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eLacunae number, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.2757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCT, \u003cem\u003eN\u003c/em\u003e = 148\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003eN1 = 100 (missed = 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003eN2 = 48 (missed = 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCT CSVD score, 0\u0026ndash;3, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e1.41 (1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e1.06 (1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0767\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eMRI, \u003cem\u003eN\u003c/em\u003e = 97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003eN1 = 71 (missed = 37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003eN2 = 26 (missed = 23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eMRI total CSVD score, 0\u0026ndash;4, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e1.20 (1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e1.19 (1.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9863\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eWMHI positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e30 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e5 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0365*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Deep, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e1.34 (1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e0.85 (0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.0190*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Periventricular, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e1.70 (1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e1.38 (1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.1968\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCM positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e18 (25.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e7 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.8755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCM, deep, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eCM, cortical, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.8572\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eEPVS positivity if BG 2\u0026ndash;4 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e19 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e7 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9872\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eEPVS, total = BG + CS (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e2.20 (1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e2.23 (1.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.9266\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eEPVS, BG, 0\u0026ndash;4 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e1.11 (0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e1.00 (0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.5660\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41.0488%;\"\u003e\n \u003cp\u003eEPVS, CS, 0\u0026ndash;4 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.0615%;\"\u003e\n \u003cp\u003e1.10 (0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22.4231%;\"\u003e\n \u003cp\u003e1.23 (0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14.4665%;\"\u003e\n \u003cp\u003e0.5291\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. IQR: interquartile range. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eRecent brain injury: recent stroke, brain tumor, or anoxic brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eChronic brain injury: old stroke, encephalomalacia, traumatic brain injury or surgical brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDevelopmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly\u003c/p\u003e\n\u003cp\u003e* \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable legends\u003c/strong\u003e: Among the patients with CSIDs, those with severe infections were more likely to have higher comorbidity scores, including higher Charlson Comorbidity Index values and greater heart failure or pulmonary hypertension than those without severe infections were. Additionally, these patients had a lower burden of deep WMHI than did the mild CSID group, as well as less WMHI overall, suggesting an inverse association between infection severity and chronic brain lesion burden.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eUnivariate and logistic regression analysis of factors associated with mild CSID among patients with CSID\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003eMild CSID, \u003cem\u003eN\u003c/em\u003e1 = 71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003eSevere CSID, \u003cem\u003eN\u003c/em\u003e2 = 26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003eCrude OR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003eAdjusted OR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003eAdjusted \u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eHigh CCI, \u0026ge; 7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e37 (52.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e18 (69.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e0.48\u003c/p\u003e\n \u003cp\u003e(0.19-1.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e0.57\u003c/p\u003e\n \u003cp\u003e(0.13- 2.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.4617\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eHigh ESCI, \u0026ge; 6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e30 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e15 (57.7%)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e0.54\u003c/p\u003e\n \u003cp\u003e(0.22-1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e1.24\u003c/p\u003e\n \u003cp\u003e(0.30-5.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.7652\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eHF/Pulmonary HTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e24 (33.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e15 (57.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003cp\u003e(0.15-0.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003cp\u003e(0.10-1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.0534\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eRecent fever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e16 (22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e14 (53.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003cp\u003e(0.10-0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003cp\u003e(0.08-0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.0143*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eRespiratory alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e13 (18.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e12 (46.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e0.26\u003c/p\u003e\n \u003cp\u003e(0.10-0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e0.47\u003c/p\u003e\n \u003cp\u003e(0.15-1.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.2031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eWMHI positivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e30 (42.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e5 (19.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e3.07\u003c/p\u003e\n \u003cp\u003e(1.04-9.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003cp\u003e(0.19-6.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.9071\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 21.2654%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Deep, severe (2-3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e25 (35.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3568%;\"\u003e\n \u003cp\u003e2 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.8594%;\"\u003e\n \u003cp\u003e6.52\u003c/p\u003e\n \u003cp\u003e(1.42-29.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.2777%;\"\u003e\n \u003cp\u003e10.2\u003c/p\u003e\n \u003cp\u003e(1.06-99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.884%;\"\u003e\n \u003cp\u003e0.0448*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eCCI: Charlson Comorbidity Index. CI: confidence interval. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. OR: odds ratio. WMHI: white matter hyperintensity.\u003c/p\u003e\n\u003cp\u003e* \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable legends\u003c/strong\u003e: In the multivariable logistic regression analysis, the presence of fever showed a significant negative association with mild CSID, whereas a high Fazekas score-Deep (2\u0026ndash;3) was significantly and positively associated with mild CSID, consistent with our earlier observations. Other variables that initially presented with p \u0026lt; 0.1 in Table 2 lost their statistical significance after adjustment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Comparison of Patients with and without Fever in the Mild CSID Subgroup\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003eAfebrile, \u003cem\u003eN\u003c/em\u003e1 = 76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003eFebrile, \u003cem\u003eN\u003c/em\u003e2 = 32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eEpidemiology, \u003cem\u003eN\u003c/em\u003e= 108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eAge, years, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e22-92 (66.7 \u0026plusmn; 17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e22-95 (63.4 \u0026plusmn; 20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.4336\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eSex, % male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e34 (44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e19 (59.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.1647\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e0-12 (6.3 \u0026plusmn; 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e0-14 (6.1 \u0026plusmn; 3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.8121\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eESCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e0-13 (5.2 \u0026plusmn; 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e0-13 (5.3 \u0026plusmn; 3.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.8377\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eUnderlying disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eHTN/DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e56 (73.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e18 (56.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.0749\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCKD/Liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e14 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e5 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.7902\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eHF/Pulmonary HTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e28 (36.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e5 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.0288*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eMalignancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e15 (19.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e11 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.1042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e25 (32.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e5 (15.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.0673\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eClinical/laboratory profile (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eMajor electrolyte/glucose imbalance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e29 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e6 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.0491*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eAcid\u0026ndash;base imbalance positivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e37 (48.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e17 (53.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.6734\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eRespiratory acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e12 (15.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e8 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.2605\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eRespiratory alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e14 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e7 (21.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.6231\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eMetabolic acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e21 (27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e11 (34.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.4834\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eMetabolic alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e8 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e2 (6.25%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.7200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eHigh lactate \u0026ge; 2.0 (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e21 (27.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e15 (46.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.0527\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eSevere azotemia, BUN \u0026ge; 90 (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1 (3.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.5067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eBUN/Crea ratio \u0026ge; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e34 (44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e16 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.6165\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eBrain disease condition (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eRecent brain injury\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e19 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e9 (28.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.7351\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eChronic brain injury\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e42 (55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e14 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.2742\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eDevelopmental anomaly\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e3 (3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e3 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.3585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eRadiological profile (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCT or MRI, \u003cem\u003eN\u003c/em\u003e = 103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003eN1 = 74 (missed = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003eN2 = 29 (missed = 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eHippocampal atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e47 (61.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e17 (58.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.3999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eLacunae positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e16 (21.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e7 (24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.6452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eLacunae number, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0.5, 0.5, 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.8808\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCT, \u003cem\u003eN\u003c/em\u003e = 101\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003eN1 = 72 (missed = 4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003eN2 = 29 (missed = 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCT CSVD score, 0\u0026ndash;3, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1.47 (1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1.21 (1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.3062\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eMRI, \u003cem\u003eN\u003c/em\u003e = 71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003eN1 = 55 (missed = 21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003eN2 = 16 (missed = 16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eMRI total CSVD score, 0\u0026ndash;4, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1.20 (1.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1.19 (1.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.9726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eWMHI positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e23 (41.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e7 (43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.8905\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Deep, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1.35 (1.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1.31 (1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.9225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Periventricular, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1.71 (1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1.69 (1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.9459\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCM positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e14 (25.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e4 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCM, deep, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0.5, 0.5, 3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.9203\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eCM, cortical, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 11)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.8729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eEPVS positivity if BG 2\u0026ndash;4 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e15 (27.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e4 (25.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eEPVS, total = BG + CS (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e2.16 (1.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e2.31 (1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.7020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eEPVS, BG, 0\u0026ndash;4 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1.05 (0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1.31 (1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.3603\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 48.556%;\"\u003e\n \u003cp\u003eEPVS, CS, 0\u0026ndash;4 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.9531%;\"\u003e\n \u003cp\u003e1.13 (0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18.5921%;\"\u003e\n \u003cp\u003e1.00 (0.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.8989%;\"\u003e\n \u003cp\u003e0.5838\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. HF: heart failure. HTN: hypertension. IQR: interquartile range. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eRecent brain injury: recent stroke, brain tumor, or anoxic brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eChronic brain injury: old stroke, encephalomalacia, traumatic brain injury, or surgical brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDevelopmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly\u003c/p\u003e\n\u003cp\u003e* \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable legends\u003c/strong\u003e: Patients with CSID and fever had significantly lower rates of heart failure and pulmonary hypertension and less electrolyte or glucose imbalance than did those without. Nevertheless, no significant differences in neuroimaging markers were observed, suggesting that fever had a neutral effect on seizure risk.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5.\u003c/strong\u003e Clinical and Imaging Differences Between Patients with GPC and GNB Infections with Seizures and CSIDs\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003ePure GPC, \u003cem\u003eN\u003c/em\u003e1 = 18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003ePure GNB, \u003cem\u003eN\u003c/em\u003e2 = 53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u003cem\u003ep\u003c/em\u003e value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eEpidemiology, \u003cem\u003eN\u003c/em\u003e = 71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eAge, years, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e22-104 (66.9 \u0026plusmn; 22.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e25-95 (68.7 \u0026plusmn; 16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.7533\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eSex, % male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e7 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e24 (45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.6365\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0-12 (6.1 \u0026plusmn; 3.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e0-13 (6.8 \u0026plusmn; 3.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eESCI, range (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0-14 (5.9 \u0026plusmn; 4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e0-13 (5.3 \u0026plusmn; 2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5438\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eUnderlying disease (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eHTN/DM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e9 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e39 (73.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.0647\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCKD/Liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e6 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e9 (17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.1837\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eHF/Pulmonary HTN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e9 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e21 (39.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.4413\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eMalignancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e5 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e12 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.7514\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eDementia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e5 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e11 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5306\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eClinical/laboratory profile (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eMajor electrolyte/glucose imbalance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e3 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e15 (28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5313\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eRecent fever\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e5 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e19 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5317\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eInfection location\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003ePneumonia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e11 (61.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e25 (47.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eUTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e4 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e26 (49.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.0465*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eSeptic shock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e3 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e6 (11.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.6833\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eBacteremia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e5 (27.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e15 (28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.9659\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eAcid\u0026ndash;base imbalance positivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e7 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e28 (52.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3067\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eRespiratory acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e2 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e12 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.4937\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eRespiratory alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e3 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e12 (22.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.7450\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eMetabolic acidosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e6 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e14 (26.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5729\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eMetabolic alkalosis burden\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e5 (9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3199\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eHigh lactate \u0026ge; 2.0 (mmol/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e4 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e18 (34.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3521\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eSevere azotemia, BUN \u0026ge; 90 (mg/dL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1 (5.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e3 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eBUN/Crea ratio \u0026ge; 20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e9 (50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e8 (15.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.0080**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eBrain disease condition (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eRecent brain injury\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e6 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e11 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eChronic brain injury\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e6 (33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e36 (67.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.0099**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eDevelopmental anomaly\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e2 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e3 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5952\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eRadiological profile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCT or MRI, \u003cem\u003eN\u003c/em\u003e = 69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003eN1 = 18 (missed = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003eN2 = 51 (missed = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eHippocampal atrophy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e7 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e34 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.0391*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eLacunae positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e4 (22.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e19 (37.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.2448\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eLacunae number,\u003c/p\u003e\n \u003cp\u003emedian (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;1, 1, 6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3628\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCT, \u003cem\u003eN\u003c/em\u003e = 69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003eN1 = 18 (missed = 0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003eN2 = 51 (missed = 2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCT CSVD score, 0\u0026ndash;3, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1.06 (1.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e1.47 (1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.2146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eMRI, \u003cem\u003eN\u003c/em\u003e = 41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003eN1 = 10 (missed = 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003eN2 = 31 (missed = 22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eMRI total CSVD score, 0\u0026ndash;4, average (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0.80 (1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e1.32 (1.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.2714\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eWMHI positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e4 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e13 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e1.0000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Deep, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1.00 (1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e1.48 (1.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.2264\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eFazekas\u0026ndash;Periventricular, 0\u0026ndash;3 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1.4 (1.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e1.97 (0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.2422\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCM positivity (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1 (10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e8 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.1274\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCM, deep, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 12)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.8415\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eCM, cortical, median (Q1\u0026ndash;Q3, IQR, range)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e0 (0\u0026ndash;0, 0, 8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.5029\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eEPVS positivity if BG 2\u0026ndash;4 (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1 (10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e6 (19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.6599\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eEPVS, total = BG + CS (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1.70 (1.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e2.23 (1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eEPVS, BG, 0\u0026ndash;4 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0.70 (0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e1.06 (0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.1585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eEPVS, CS, 0\u0026ndash;4 (SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e1.00 (1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e1.16 (0.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.6608\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 44.7653%;\"\u003e\n \u003cp\u003eOffending antibiotics (Cefepime, imipenem, ertapenem \u0026amp; meropenem)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19.4946%;\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20.3971%;\"\u003e\n \u003cp\u003e6 (11.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.343%;\"\u003e\n \u003cp\u003e0.3072\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eBG: basal ganglion. BUN: blood urea nitrogen. CCI: Charlson Comorbidity Index. CKD: chronic kidney disease. CM: cerebral microbleed. Crea: creatinine. CS: centrum semiovale. CSVD: cerebral small vessel disease. CT: computed tomography. DM: diabetes mellitus. EPVS: enlarged perivascular space. ESCI: Epilepsy-Specific Comorbidity Index. GNB: Gram-negative bacillus. GPC: Gram-positive coccus. HF: heart failure. IQR: interquartile range. HTN: hypertension. MRI: magnetic resonance imaging. Q1: the first quartile. Q3: the third quartile. SD: standard deviation. WMHI: white matter hyperintensity.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003eRecent brain injury: recent stroke, brain tumor, or anoxic brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003eChronic brain injury: old stroke, encephalomalacia, traumatic brain injury, or surgical brain injury\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003eDevelopmental anomaly: cortical dysplasia, mesial temporal sclerosis, vascular anomaly, or microcephaly\u003c/p\u003e\n\u003cp\u003e* \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, ** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.01\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable legends\u003c/strong\u003e: In patients with CSID with positive cultures, the pure GNB subgroup had significantly more UTIs and a less extreme BUN/creatinine ratio than the pure GPC group did. Patients with GPC infections exhibited a significantly lower burden of chronic brain injury and hippocampal atrophy than did those with GNB infections, suggesting that GPC-related seizures may be observed in the setting of less extensive preexisting brain pathology, supporting the proposed \u0026ldquo;Inverse model\u0026rdquo; of systemic inflammation and seizure susceptibility.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Systemic infection, seizure, cerebral small vessel disease, chronic brain lesion, brain resilience, neuroinflammation, epileptogenesis, pneumonia, urinary tract infection, bacteremia","lastPublishedDoi":"10.21203/rs.3.rs-9149796/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9149796/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction\u003c/strong\u003e: Systemic infection and seizures frequently co-occur in patients. Nevertheless, the association between seizures, its triggers and concurrent systemic infectious diseases (CSIDs) other than central nervous system infections remains unclear.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: This retrospective cross-sectional study evaluated 216 inpatients with ongoing seizures at a tertiary center in Taiwan in 2018. Clinical, radiological, and microbiological characteristics were compared between the patients with or without CSIDs.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: CSIDs were identified in 72.6% of the patients. Those with CSIDs were older (p = 0.0020), and had more dementia (p = 0.0180), hippocampal atrophy (p = 0.0167), chronic brain injury (p = 0.0091), and greater cerebral small vessel disease (CSVD) burden (CT, p = 0.0373; MRI, p = 0.0373). Interestingly, those with severe CSIDs (septic shock, bacteremia) had lower CSVD burden (p = 0.0365, white matter lesion positivity; p = 0.0190, deep white matter Fazekas score) than mild CSIDs.Multivariate logistic regression confirmed this inverse relationship (adjusted OR: 10.2, p = 0.0448) for deep white matter Fazekas score. Additionally, seizures associated with Gram-positive cocci (GPC) infections occurred in patients with lower burden of chronic brain injury (p = 0.0099) and hippocampal atrophy (p = 0.0391) compared to Gram-negative bacilli (GNB)infections.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e: Thesefindings support an “Inverse model” hypothesis where systemic inflammation and diminished brain resilience are linked in seizure manifestation. Consequently, in older adults with chronic brain lesions, seizures may occur even in the setting of mild infections. In contrast, more severe infections tend to be associated with seizures in patients with uncompromised brains. Seizure risk was higher in patients with GPC infections than in those with GNB infections. These results underscore the importance of screening for systemic infections in older patients or those with dementia or higher chronic brain lesion burden who present with seizures, even in the absence of fever.\u003c/p\u003e","manuscriptTitle":"Systemic Infection and Brain Resilience in Patients With Seizures: An Inverse-Model Hypothesis From a Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-14 15:04:04","doi":"10.21203/rs.3.rs-9149796/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-04-07T14:51:45+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-18T14:42:54+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-18T09:44:47+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-18T09:44:24+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Neurology","date":"2026-03-17T13:55:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-neurology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"nurl","sideBox":"Learn more about [BMC Neurology](http://bmcneurol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/nurl","title":"BMC Neurology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3edbbbf0-ced6-483c-b9f9-e7b1ae91d513","owner":[],"postedDate":"April 14th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T15:04:05+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-14 15:04:04","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9149796","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9149796","identity":"rs-9149796","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}