Geriatric Nutritional Risk Index has a Prognostic value for Recovery Outcomes in Elderly Patients with Brain Abscess

Geriatric Nutritional Risk Index has a Prognostic value for Recovery Outcomes in Elderly Patients with Brain Abscess | 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 Geriatric Nutritional Risk Index has a Prognostic value for Recovery Outcomes in Elderly Patients with Brain Abscess Xu Pei, Yutu Zhang, Dongfeng Jiang, Meng Zhang, Junyan Fu, Yang Niu, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4020068/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: The Geriatric Nutritional Risk Index (GNRI) is a straightforward and objective tool for nutritional screening in elderly patients and has been demonstrated to possess prognostic predictive value in several diseases. Nonetheless, there is a lack of research on the nutritional risk associated with brain abscess in the elderly. This study aimed to evaluate the prevalence of nutritional risk among these patients by GNRI and to investigate its potential prognostic value for clinical outcomes. Methods: From August 2019 to April 2023, 100 elderly patients diagnosed with brain abscess were enrolled in the study. The collected data encompassed age, gender, body mass index (BMI), smoking and alcohol consumption history, number of comorbidities, length of hospital stay (LOS), serum albumin and C-reactive protein (CRP) levels at admission and calculated the GNRI, the Glasgow outcome scale (GOS) score 6 months post-discharge. A GOS score of 5 was considered indicative of a good recovery, whereas scores ranging from 1 to 4 were classified as poor recovery. Results: The prevalence of malnutrition risk among elderly patients with brain abscesses was found to be 48% according to GNRI. Compared to those without nutritional risk, patients at risk exhibited significantly higher post-admission C-reactive protein (CRP) levels (P=0.017), a greater number of comorbidities (P<0.001), and elevated age-adjusted Charlson Comorbidity Index (aCCI) scores (P<0.001). Spearman correlation analysis revealed a negative correlation between GNRI scores and CRP levels, the number of comorbidities, and aCCI scores (Spearman's ρ=-0.291, -0.284, and -0.310, respectively), and a positive correlation with Glasgow Outcome Scale (GOS) scores (Spearman's ρ=0.624, P<0.001). Multivariate logistic regression analysis indicated that lower GNRI values in these patients were associated with reduced GOS levels (OR = 0.826, 95% CI: 0.775-0.880). Furthermore, receiver operating characteristic (ROC) analysis identified a GNRI threshold of 97.50 for predicting poor recovery, with a sensitivity of 90.57% and a specificity of 87.23%. Conclusions: Elderly brain abscess patients exhibited a high malnutrition risk. GNRI showed an important predictive value for recovery in elderly patients, which could be helpful in clinical intervention and rehabilitation. Geriatric Nutritional Risk Index (GNRI) brain abscess Glasgow Outcome Scale (GOS) prognosis Figures Figure 1 Figure 2 Figure 3 Introduction Brain abscess, a serious intracranial infection, manifests as a pus collection within the brain tissue[ 1 ]. Its complex pathogenesis involves a variety of infectious agents, such as bacteria[ 2 ], fungi[ 3 ], and parasites[ 4 ]. Risk factors for the formation of a brain abscess include skull injuries, peripheral infections, a compromised immune system, malnutrition, and factors associated with advanced age[ 1 ]. The mortality rate for brain abscesses is around 10%, with 45% of affected patients experiencing neurological deficits post-treatment[ 4 – 6 ]. In elderly patients, this mortality rate increases, with studies indicating a range of 20–40%[ 4 , 6 ]. The Glasgow outcome scale (GOS) is a scale used to systematically evaluate post-brain injury recovery, categorizing outcomes into five levels: death, vegetative state, severe disability, moderate disability, and good recovery[ 7 ]. The GOS has been employed widely as a metric to assess the effectiveness of brain injury treatment and rehabilitation strategies[ 8 , 9 ]. Nutritional status significantly influences the progression of brain abscesses and the efficacy of treatments[ 10 ]. Inadequate nutrition weakens immune defenses, increasing infection risks[ 11 ]. Furthermore, nutritional health is vital during treatment and recovery, with nutritional deficits potentially delaying wound healing, impeding neurological recovery, and prolonging the recovery process[ 12 ]. Such deficiencies can negatively impact patient lifespan, and quality of life, and impose significant economic costs[ 13 ]. Given the heightened risk of malnutrition among the elderly due to aging, conducting a simple and objective assessment of malnutrition risk is imperative to develop effective nutritional interventions. The geriatric nutritional risk index (GNRI) serves as an objective screen tool to evaluate the nutritional status of elderly individuals and its association with health risks[ 14 ]. The GNRI has emerged as a powerful prognostic indicator for the elderly, particularly regarding long-term postoperative outcomes[ 15 – 17 ]. Numerous studies have demonstrated the utility of the GNRI in predicting outcomes among a wide range of clinical conditions in the elderly, including chronic kidney disease[ 18 ], heart failure[ 19 ], chronic obstructive pulmonary disease[ 20 ], and sepsis[ 21 ]. Additionally, GNRIs have relevant applications in brain-related injuries. Su et al.'s study revealed that the GNRI is a prognostic factor for death in elderly patients with moderate to severe Traumatic Brain Injuries[ 22 ]. Furthermore, evidence from another study highlighted that a lower GNRI is an independent predictor of brain infarction and hemorrhage in patients on maintenance hemodialysis[ 23 ]. Similarly, the study by Dai et al demonstrated that GNRI was related to the risk of stroke-associated pneumonia[ 24 ]. To our knowledge, no study has examined the nutritional status of brain abscess patients and its correlation with clinical outcomes. Therefore, this study employed the GNRI to assess the risk of malnutrition among elderly brain abscess patients, exploring the relationship between nutritional status and clinical features. Additionally, we employed the GOS to evaluate recovery post-discharge in these patients, further exploring GNRI's predictive value for GOS scores in elderly brain abscess patients’ post-discharge. Materials and methods Study design and participants This single-center prospective cohort study was executed at Huashan Hospital, Fudan University. The study population comprised individuals admitted with a diagnosis of brain abscess between August 2019 and April 2023. Patients were subjected to a follow-up period of 6 months post-discharge. The current study excludes individuals younger than 60 years and those lost to follow-up (Fig. 1 ). Ethical endorsement for this study's protocol was granted by the Research Ethics Committee of Huashan Hospital, Fudan University. This approval was secured to ascertain adherence to the ethical guidelines outlined in the Declaration of Helsinki (1975), as well as its later amendments, thereby ensuring the protection of participants' rights and well-being throughout the research. Data collection Demographic and clinical characteristics Demographic and clinical data were systematically gathered, encompassing age, gender, tobacco use and alcohol consumption histories. Serum albumin levels and C-reactive protein (CRP) concentrations were documented for all subjects upon their initial evaluation, conducted within the first 48 hours post-admission. Additional details regarding therapeutic interventions employed, comorbidities were also collected. Comorbid conditions encompass a spectrum of diseases and disorders, including chronic illnesses (e.g., hypertension, diabetes mellitus, cardiovascular disorders, pulmonary pathologies, renal dysfunctions), psychiatric disorders (e.g., depressive disorders, anxiety disorders, bipolar affective disorders), autoimmune diseases (e.g., rheumatoid arthritis, systemic lupus erythematosus), neurological pathologies (e.g., Alzheimer's disease, Parkinson's disease), metabolic disorders (e.g., obesity, dyslipidemia), infectious diseases (e.g., chronic hepatitis, HIV/AIDS), and gastroenterological conditions (e.g., chronic gastritis, inflammatory bowel disease). The age-adjusted Charlson Comorbidity Index (aCCI) was employed to evaluate the aggregate risk associated with patients. Nutritional assessment Anthropometric parameters were ascertained by trained medical personnel employing a calibrated scale equipped with a stadiometer (RGZ 120, China). Body mass index (BMI) was calculated utilizing the formula: weight (kg) / height 2 (m²). The classification of BMI adhered to the guidelines established by the Chinese Obesity Working Group, delineating the categories as follows: underweight ( 23.9 kg/m²). The GNRI is derived through the following equation[ 14 ]: $$GNRI=\frac{14.89*albumin(g/l)}{22.0}+\frac{41.7*weight\left(kg\right)}{ideal weight\left(kg\right)}$$ The ideal weight within this equation is ascertained via the Lorenz formula, which is contingent upon the individual's sex and stature. Should the ratio of the current to ideal weight exceed 1, it is subsequently adjusted to 1. Lorenz formula: For male: \(ideal weight \left(kg\right)=height\left(cm\right)-100-\frac{height\left(cm\right)-150}{4}\) For female: \(ideal weight \left(kg\right)=height\left(cm\right)-100-\frac{height\left(cm\right)-150}{2.5}\) Outcomes The length of stay (LOS) of each patient was recorded. LOS was defined as the interval, measured in days, extending from the initial date of admission to the terminal date of discharge. GOS was employed for the assessment of overall functional recuperation in overall. The scale is stratified into quintuple gradations as follows: GOS = 1, death; GOS = 2, vegetative state; GOS = 3, severe disability; GOS = 4, moderate disability; and GOS = 5, good recovery. Statistical analysis Participant characteristics in this study were summarized as mean ± standard deviation (SD) for normally distributed continuous variables and median (interquartile range, IQR) for non-normally distributed continuous variables. Categorical variables were reported as frequencies and percentages. The t-test and Wilcoxon rank-sum test assessed differences in key indicators between groups with and without nutritional risk. Pearson correlation analysis explored factors associated with GNRI scores. Univariate logistic regression on GOS included variables with P < 0.20 in a subsequent multivariate analysis. Odds ratios (OR) and 95% confidence intervals (CI) were reported. A stratified histogram depicted GOS score distributions across nutritional risk categories in brain abscess patients. The prognostic value of GNRI for elderly brain abscess patients was determined using receiver operating characteristic curve (ROC) analysis, a GOS score of 5 was classified as indicative of good recovery, whereas scores ranging from 1 to 4 were considered to reflect poor recovery. Statistical analyses were two-sided, with an alpha level of 0.05, performed using SAS V.9.4 (SAS Institute, Cary, NC, USA). R version 4.3.2, with ggplot2 and pROC packages, was used for histogram and ROC curve visualizations. Results This study's final analysis included a cohort of 100 elderly patients diagnosed with brain abscess. Table 1 revealed the median age to be 68 years (IQR 64.5–72), with females constituting 61% (61/100) of the sample. In this cohort, 11% (11/100) were underweight, and 30% (30/100) were overweight. The proportion of alcohol consumption and smoking was noted in 19% (19/100) and 18% (18/100) of the patients, respectively. Comorbidities were prevalent in elderly brain abscess patients, with the median number of comorbidities being 2 (IQR 0–3). GNRI assessments conducted within 48 hours of admission indicated malnutrition risks in 48% of patients, with 4% facing major malnutrition risk, 23% moderate risk, and 21% low risk. The median hospital stay duration was 15 days (IQR 10–22), and the median GOS score at 6 months post-discharge was 5 (IQR 3–5), reflecting generally favorable outcomes. Table 1 Characteristcs of this study participants. Whole study group (n = 100) Age (year) (median, IQR) 68.0 (64.5–72.0) Male (n, %) 61 (61.00%) Height (cm) (mean ± SD) 166.05 ± 7.13 Weight (kg) (mean ± SD) 62.22 ± 10.50 BMI (kg/m²) (mean ± SD) 22.50 ± 3.15 Underweight ( 23.9 kg/m 2 ) (n, %) 30 (30.0%) Smoking status (n,%) Current or former 19 (19.0%) Never 81 (81.0%) Drinking status (n,%) Current or former 18 (18.0%) Never 82 (82.0%) Comorbidity (median, IQR) 2 (0–3) aCCI score (median, IQR) 1 (0–2) LOS (days) (median, IQR) 15 (10–22) GOS score (median, IQR) 5 (3–5) Malnutrition risk to GNRI (n, %) 48 (48.0%) Major malnutritional risk (GNRI: <82) 4 (4.0%) Moderate malnutritional risk (GNRI: 82–91) 23 (23.0%) Low malnutritional risk (GNRI: 92–98) 21 (21.0%) IQR, Interquartile range; BMI, Body mass index; aCCI, age-adjusted Charlson Comorbidity Index; LOS, Length of stay; GOS, Glasgow outcome scale; GNRI, Geriatric nutritional risk index As shown in Table 2 , individuals at risk for malnutrition had significantly lower BMI compared to those not at risk (P < 0.001). This group also had a higher median comorbidity count of 3 (IQR 1–4) (P < 0.001), suggesting a higher burden of comorbid conditions. Furthermore, aCCI scores were significantly higher in the malnutrition risk group (P < 0.001). Admission CRP levels were also higher in the malnutrition risk group than in the non-risk group (P = 0.017), indicating more severe inflammation. Treatment strategies varied, with a larger fraction of the malnutrition risk group receiving conservative medical treatment (66.7%) compared to the non-risk group (38.5%) (P = 0.003). Additionally, the malnutrition risk group had lower median GOS scores of 3 (IQR 3–4) (P < 0.001), indicating a worse prognosis. Table 2 A comparative analysis of demographic and clinical characteristics between patients with and without malnutrition risk according to GNRI No malnutrition risk (n = 52) Malnutrition risk (n = 48) P value Age (year) (mean ± SD) 68.04 ± 5.40 68.77 ± 5.19 0.492 Male (n, %) 35 (67.3%) 26 (54.2%) 0.182 BMI (kg/m²) (mean ± SD) 24.13 ± 2.83 20.74 ± 2.48 <0.001 Underweight ( 23.9 kg/m 2 ) (n, %) 25 (48.1%) 5 (10.4%) Smoking status (n,%) 0.342 Current or former 8 (15.4%) 11 (22.9%) Never 44 (84.6%) 37 (77.1%) Drinking status (n,%) 0.484 Current or former 8 (15.4%) 10 (20.8%) Never 44 (84.6%) 38 (79.2%) Comorbidity (median, IQR) 1 (0–2) 3 (1–4) <0.001 aCCI score (median, IQR) 3 (2–3) 3 (3–4) <0.001 CRP (mg/L) (median, IQR) 4.3 (1.8–16.0) 15.6 (4.9–42.2) 0.017 Treatment modality (n, %) 0.003 Conservative therapeutic 20 (38.5%) 32 (66.7%) Aspiration 17 (32.7%) 11 (22.9%) Excession 15 (28.8%) 5 (10.4%) LOS (days) (median, IQR) 14.5(10.0–62.0) 15.5 (9.0-23.5) 0.822 GOS score (median, IQR) 5 (5–5) 3 (3–4) <0.001 GNRI, Geriatric nutritional risk index; BMI, Body mass index; IQR, Interquartile range; aCCI, age-adjusted Charlson Comorbidity Index; CRP: C-reactive protein; LOS, Length of stay; GOS, Glasgow outcome scale Table 3 demonstrated the relationships between GNRI scores and various clinical parameters. Specifically, CRP levels (Spearman's ρ=−0.291, P = 0.006), the total number of comorbidities (Spearman's ρ=−0.284, P = 0.004), and aCCI scores (Spearman's ρ=−0.310, P = 0.002) are inversely correlated with GNRI scores. In contrast, GOS scores show a strong positive correlation with GNRI scores (Spearman's ρ = 0.624, P < 0.001), indicating that higher nutritional status is associated with better neurological outcomes. Figure 2 delineates the distribution of GOS scores across varying malnutrition risk categories, with the precise value distribution elaborated in Table S1 (P < 0.001) [see Additional file 1]. Furthermore, by assigning numerical values to surgical methods—1 for conservative therapeutic, 2 for aspiration, and 3 for excision—a positive correlation is observed between these values and GNRI scores (Spearman's ρ = 0.340, P < 0.001). This suggests a preference for conservative treatment in patients with poorer nutritional status, consistent with the trends shown in Table 2 . Table 3 Correlation analysis of potential factors associated with GNRI score. Spearman's ρ P value Age(y) -0.099 0.328 CRP (mg/L) -0.291 0.006 Smoking status -0.182 0.069 Drinking status -0.139 0.168 Treatment modality 0.340 < 0.001 Comorbidity -0.284 0.004 aCCI score -0.310 0.002 LOS (days) -0.020 0.845 GOS score 0.624 < 0.001 GNRI, Geriatric nutritional risk index; BMI, Body mass index; aCCI, age-adjusted Charlson Comorbidity Index; CRP, C-reactive protein; LOS, Length of stay; GOS, Glasgow outcome scale In the univariate logistic regression analyses, the association of each predictor variable with the GOS score was assessed. The results revealed no significant correlation for age or gender with the GOS score. BMI and GNRI score were significantly negatively correlated with the GOS score, whereas CRP、aCCI score, and number of comorbidities showed a positive correlation with the GOS score. In the subsequent multivariable logistic regression analysis, which incorporated variables with a P-value of less than 0.2 from the univariate analysis, GNRI was found to have a significant negative correlation with GOS score (Table 4 ). This highlights GNRI's potential as a predictive factor for outcomes. Additionally, Fig. 3 showed the ROC curve for GNRI in predicting poor recovery. The analysis yielded an Area Under the Curve (AUC) of 0.903, with the 95% Confidence Interval (CI) extending from 0.832 to 0.975. At the optimal threshold of 97.50, with a sensitivity of 90.57% and a specificity of 87.23% in predicting recovery outcomes. Table 4 Logistic regression analysis for GOS as a dependent variable Univariate Multivariate OR (95%CI) P value OR (95%CI) P value Age 1.063 (0.991–1.141) 0.090 1.012 (0.902–1.135) 0.845 sex 0.520 (0.244–1.109) 0.091 0.829 (0.288–2.384) 0.728 BMI 0.757 (0.656–0.874) < 0.001 0.908 (0.721–1.144) 0.413 Smoking status 1.581 (0.629–3.972) 0.330 Drinking status 2.413 (0.948–6.146) 0.089 1.154 (0.253–5.265) 0.853 CRP (mg/L) 1.012 (1.004–1.021) 0.003 1.010 (0.999–1.021) 0.073 Treatment modality 0.669 (0.409–1.094) 0.109 1.338 (0.654–2.738) 0.425 Comorbidity 1.216 (1.041–1.420) 0.014 0.969 (0.748–1.254) 0.811 aCCI score 2.024 (1.411–2.903) < 0.001 1.456 (0.800-0.916) 0.219 LOS 0.995 (0.965–1.023) 0.662 GNRI 0.826 (0.775–0.880) < 0.001 0.830 (0.752–0.916) < 0.001 GOS, Glasgow outcome scale; BMI, Body mass index; CRP, C-reactive protein; aCCI, age-adjusted Charlson Comorbidity Index; LOS, Length of stay; GNRI, Geriatric nutritional risk index Univariate: Univariate logistic regression analysis Multivariate: Multivariate logistic regression analysis: inclusion of predictors exhibiting univariate logistic regression outcomes with P <0.20 Discussion This study represents the first study into the association between malnutrition risk, as determined by the GNRI, and clinical outcomes in elderly patients with brain abscess. Findings from this prospective cohort study revealed that nearly half of the elderly brain abscess patients exhibited malnutritional risk, which is related to their treatment modality as well. Concurrently, the GNRI displayed associations with both the quantum of comorbidities and the aCCI score, underscoring the intricate interplay between nutritional status and the aggregate health burden in this demographic. Notably, elderly brain abscess patients presenting with lower GNRI scores were observed to have diminished GOS scores, indicating that GNRI has a predictive impact on their clinical outcomes. Malnutrition, often underreported and underdiagnosed, is widespread among elderly hospitalized patients, contributing to adverse clinical outcomes such as prolonged hospital stays and elevated mortality rates[ 25 ]. The GNRI provides an efficient, objective, and age-specific approach to nutritional screening in the elderly[ 14 ]. It assesses the nutritional risks of the elderly in a timely and accurate manner by utilizing current weight metrics and serum albumin levels, thereby minimizing recall bias associated with past weight changes[ 14 ]. In this study, the GNRI was employed to assess the malnutrition risk in elderly patients with brain abscesses, revealing a significant prevalence of 48%. Similarly, Bao et al.'s study revealed that among elderly patients experiencing early neurological deterioration following acute ischemic stroke, 48.3% were at risk of malnutrition according to GNRI[ 26 ]. In another study, the GNRI assessment revealed a malnutrition risk of approximately 42.5% (97/228) among elderly patients with mild traumatic brain injury[ 27 ]. These results above suggest that brain injury in elderly patients is often accompanied by malnutrition. This high incidence of malnutrition in the elderly may be attributed to various factors. With advancing age, oral issues such as missing teeth impair chewing ability, impacting food intake and digestion[ 28 ]. Moreover, elderly individuals frequently contend with chronic diseases like diabetes and heart disease, potentially increasing metabolic demands and subsequently heightening the risk of malnutrition[ 29 ]. This study's findings revealed a significant negative correlation between GNRI and the level of comorbidity, further substantiated that the heightened burden of chronic diseases contributes to the increased risk of malnutrition. As an infectious disease affecting the nervous system, brain abscesses induce inflammation that escalates the body's metabolic demands, thereby heightening nutritional requirements[ 1 , 30 ]. This, combined with the adverse effects of infection and pharmacological treatments on appetite, can precipitate a further decline in the nutritional status of patients with brain abscesses[ 30 ]. In the correlation analysis conducted in this study, the GNRI and CRP values upon admission in elderly patients with brain abscesses were found to be significantly negatively correlated (P = 0.006), thereby further indicating the relation between the level of inflammation and the nutritional risk. Furthermore, we observed that patients at nutritional risk underwent more conservative treatment during hospitalization compared to their counterparts without nutritional risk (38.5% vs 66.7%). This finding implies that the nutritional status of elderly patients with brain abscess may influence their treatment approach. In clinical practice, the typical focus on infection control and acute neurological symptom management in brain abscess cases often overshadows the scrutiny of patients' nutritional status. The findings of this study indicated that elderly brain abscess patients at higher malnutrition risk exhibit poorer clinical prognoses (P < 0.001). A positive correlation emerged between GNRI scores and GOS scores(P < 0.001), indicating a nutritional status may be significantly associated with recovery and long-term outcomes in brain abscess patients. Several studies also have demonstrated a correlation between elevated malnutrition risks and adverse clinical outcomes in geriatric patients[ 27 , 31 ]. It can be seen that in the process of diagnosis and treatment of geriatric diseases, the assessment of nutritional status cannot be ignored. GNRI has been employed as an independent predictive factor for morbidity and mortality in elderly hospitalized patients with cancer [ 32 ]. Research on elderly colorectal cancer patients revealed that the preoperative GNRI served as an independent prognostic factor for those who underwent curative colorectal resection[ 33 ]. In another study, the GNRI has been identified as an independent predictor of prognosis and postoperative complications after radical nephroureterectomy for upper urinary tract urothelial carcinoma[ 34 ]. In addition to its extensive application in forecasting postoperative complications and the long-term prognosis of tumors, the GNRI was also employed in other diseases for its prognostic significance for recuperation and clinical outcomes. A study focused on elderly patients with mild traumatic brain injury revealed that a higher GNRI was associated with a decreased risk of incomplete recovery at the 6-month mark. Furthermore, the ROC analysis established a GNRI threshold of 97.85[ 27 ]. And GNRI was considered a promising tool for predicting mortality outcomes in older patients with moderate to severe TBI[ 22 ]. These findings indicated that GNRI may have applicability in diseases related to brain injury. In our multivariate regression analysis, we found that lower GNRI values were positively associated with poorer prognosis (i.e., lower GOS score). Moreover, the results of the ROC analysis, which yielded an AUC of 0.903, underscore the significant potential of GNRI in predicting the long-term outcomes for elderly patients with brain abscess. Our study offered several strengths. Firstly, as a prospective cohort study, the high standardization of our data collection protocols ensures data quality, while simultaneously reducing selection and recall biases. Secondly, this is the inaugural investigation into the prevalence of nutritional risk among elderly patients with brain abscesses, providing a novel insight into the clinical implications of GNRI scores. Furthermore, our use of logistic regression analysis has elucidated the relationship between GNRI and the prognostic score for geriatric brain abscesses (GOS), affirming GNRI's utility in predicting outcomes for elderly hospitalized patients with brain abscesses. This study, while providing valuable insights, has certain limitations. Firstly, being a single-center study, the generalizability of the results to broader populations may be compromised. Secondly, the relatively small cohort size could diminish the statistical power, potentially impacting the robustness of the findings. Thirdly, the reliance on the GNRI, which is primarily based on current weight, may not adequately capture changes in a patient's nutritional status over time. Therefore, future research should be conducted across multiple centers, incorporate larger patient samples, and integrate additional nutritional assessment methods, such as Dual-energy X-ray Absorptiometry (DXA) or Bioelectrical Impedance Analysis (BIA). To deepen our understanding of the nutritional status of elderly patients with brain abscess and further explore the impact of nutritional status on treatment and clinical outcomes. Conclusion This inaugural study on the nutritional status of elderly patients with brain abscesses revealed that nearly half are at risk of malnutrition according to the GNRI. The GNRI is correlated with the number of comorbidities, aCCI scores, and treatment modalities, underscoring the intricate relationship between nutritional status and the overall health burden in this demographic. Moreover, the study observed that lower GNRI scores in these patients were associated with decreased GOS scores, and found that GNRI is a prognostic indicator of clinical outcomes. Clinically, heightened attention is warranted for patients with GNRI scores below the critical threshold of 97.5, and prompt nutritional interventions should be administered. Consequently, we advocate regular nutritional evaluations for all elderly patients with brain abscesses, ensuring early intervention with nutritional therapy to preserve their nutritional health and mitigate the risk of adverse outcomes. Abbreviations GOS Glasgow Outcome Scale GNRI Geriatric Nutritional Risk Index aCCI age-adjusted Charlson Comorbidity Index BMI Body mass index LOS Length of stay OR Odds ratios CI Confidence intervals ROC Receiver operating characteristic curve DXA Dual-energy X-ray Absorptiometry BIA Bioelectrical Impedance Analysis Declarations Acknowledgements The authors express their gratitude to the staff responsible for data collection and patient follow-up, as well as to the participants and their families, for their invaluable cooperation. Authors’ contributions The authors confirm contributions as follows: Study conception and design were carried out by HSS, TM, and PX. Data collection was performed by ZYT, JDF, FJY, ZM and NY. Analysis was conducted by HSS and PX. The initial draft of the manuscript was prepared by PX and HSS, while TM, NY, and HSS critically reviewed and revised it for important intellectual content. All authors have read and approved the final manuscript for publication and accept responsibility for the work’s accuracy and integrity. Funding No funding was secured for this study. Availability of data and materials The data underpinning the findings of this study can be obtained from the corresponding author upon reasonable request. Ethics approval and consent to participate This study was approved by the Ethics Committee of Huashan Hospital affiliated with Fudan University School of Medicine (No. KY2023-847). Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Brouwer MC, Tunkel AR, McKhann GM 2nd, van de Beek D. Brain abscess. N Engl J Med. 2014;371:447–56. Sonneville R, Ruimy R, Benzonana N, Riffaud L, Carsin A, Tadié JM, Piau C, Revest M, Tattevin P. An update on bacterial brain abscess in immunocompetent patients. Clin Microbiol Infect. 2017;23:614–20. 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Performance of the Geriatric Nutritional Risk Index in predicting 28-day hospital mortality in older adult patients with sepsis. Clin Nutr. 2013;32:843–8. Su WT, Tsai CH, Huang CY, Chou SE, Li C, Hsu SY, Hsieh CH. Geriatric Nutritional Risk Index as a Prognostic Factor for Mortality in Elderly Patients with Moderate to Severe Traumatic Brain Injuries. Risk Manag Healthc Policy. 2021;14:2465–74. Tsuneyoshi S, Matsukuma Y, Kawai Y, Hiyamuta H, Yamada S, Kitamura H, Tanaka S, Taniguchi M, Tsuruya K, Nakano T, Kitazono T. Association between geriatric nutritional risk index and stroke risk in hemodialysis patients: 10-Years outcome of the Q-Cohort study. Atherosclerosis. 2021;323:30–6. Dai C, Yan D, Xu M, Huang Q, Ren W. Geriatric Nutritional Risk Index is related to the risk of stroke-associated pneumonia. Brain Behav. 2022;12:e2718. Kaegi-Braun N, Mueller M, Schuetz P, Mueller B, Kutz A. Evaluation of Nutritional Support and In-Hospital Mortality in Patients With Malnutrition. JAMA Netw Open. 2021;4:e2033433. Bao Y, Zhang Y, Du C, Ji Y, Dai Y, Jiang W. Malnutrition and the Risk of Early Neurological Deterioration in Elderly Patients with Acute Ischemic Stroke. Neuropsychiatr Dis Treat. 2022;18:1779–87. Zhu B, Ou Y, Guo X, Liu W, Wu L. Poor nutritional status is associated with incomplete functional recovery in elderly patients with mild traumatic brain injury. Front Neurol. 2023;14:1131085. Corcoran C, Murphy C, Culligan EP, Walton J, Sleator RD. Malnutrition in the elderly. Sci Prog. 2019;102:171–80. Mathew AC, Das D, Sampath S, Vijayakumar M, Ramakrishnan N, Ravishankar SL. Prevalence and correlates of malnutrition among elderly in an urban area in Coimbatore. Indian J Public Health. 2016;60:112–7. Katona P, Katona-Apte J. The interaction between nutrition and infection. Clin Infect Dis. 2008;46:1582–8. Fang P, Yang Q, Zhou J, Yang Y, Luan S, Xiao X, Li X, Gu Y, Shang Q, Zhang H, et al. The impact of geriatric nutritional risk index on esophageal squamous cell carcinoma patients with neoadjuvant therapy followed by esophagectomy. Front Nutr. 2022;9:983038. Hao X, Li D, Zhang N. Geriatric Nutritional Risk Index as a predictor for mortality: a meta-analysis of observational studies. Nutr Res. 2019;71:8–20. Hayama T, Hashiguchi Y, Ozawa T, Watanabe M, Fukushima Y, Shimada R, Nozawa K, Matsuda K, Fujii S, Fukagawa T. The preoperative geriatric nutritional risk index (GNRI) is an independent prognostic factor in elderly patients underwent curative resection for colorectal cancer. Sci Rep. 2022;12:3682. Wu P, Liu J, Wang X, Lai S, Wang J, Wang J, Wang J, Zhang Y, Hao Q. Development and validation of a nomogram based on geriatric nutritional risk index for predicting prognosis and postoperative complications in surgical patients with upper urinary tract urothelial carcinoma. J Cancer Res Clin Oncol. 2023;149:18185–200. 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University","correspondingAuthor":false,"prefix":"","firstName":"Yutu","middleName":"","lastName":"Zhang","suffix":""},{"id":276890489,"identity":"1fef401d-8587-4543-a7d5-9e8c297e2ce2","order_by":2,"name":"Dongfeng Jiang","email":"","orcid":"","institution":"Fudan University","correspondingAuthor":false,"prefix":"","firstName":"Dongfeng","middleName":"","lastName":"Jiang","suffix":""},{"id":276890490,"identity":"0ce3b198-8f32-46b4-9827-5cb3f5596ba4","order_by":3,"name":"Meng Zhang","email":"","orcid":"","institution":"Liaocheng People's Hospital","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Zhang","suffix":""},{"id":276890491,"identity":"caf4c4b9-2692-4059-a18b-36d73d22f106","order_by":4,"name":"Junyan Fu","email":"","orcid":"","institution":"Huashan 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huang","email":"data:image/png;base64,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","orcid":"","institution":"Huashan Hospital","correspondingAuthor":true,"prefix":"","firstName":"shanshan","middleName":"","lastName":"huang","suffix":""}],"badges":[],"createdAt":"2024-03-06 08:45:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4020068/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4020068/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52453157,"identity":"332c51c5-031d-4565-b8d5-40bc8aa9febb","added_by":"auto","created_at":"2024-03-11 19:19:40","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":31252,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlow chart of included patients with brain abscess in the current analysis.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4020068/v1/3c590a9e13215889881a2b16.png"},{"id":52453159,"identity":"0f49fab8-0e88-4af5-a782-2baa988df030","added_by":"auto","created_at":"2024-03-11 19:19:40","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":650465,"visible":true,"origin":"","legend":"\u003cp\u003eThe proportion of GOS scores in different nutritional categories assessed by GNRI among 100 elderly patients with brain abscess\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4020068/v1/5bf7cf13eb2a2560e08a3d26.png"},{"id":52453158,"identity":"6e57aca1-c17d-45cc-83d9-4064569cda0f","added_by":"auto","created_at":"2024-03-11 19:19:40","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73059,"visible":true,"origin":"","legend":"\u003cp\u003eROC curve analysis of GNRI for poor recovery in the elderly hospitalized with brain abscess.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4020068/v1/321a0e5c1e170b70ca8c8be1.png"},{"id":52456442,"identity":"10d5cea8-d895-497c-9aeb-5a7fd16c0810","added_by":"auto","created_at":"2024-03-11 20:13:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":803703,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4020068/v1/2ff6abc7-da42-4d01-9d9d-5c203aee88a7.pdf"},{"id":52453160,"identity":"680ed0d6-e9ca-4697-a2f1-f42df335582f","added_by":"auto","created_at":"2024-03-11 19:19:41","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":106694,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4020068/v1/f32137e26b55c5a0a3cc5c85.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Geriatric Nutritional Risk Index has a Prognostic value for Recovery Outcomes in Elderly Patients with Brain Abscess","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBrain abscess, a serious intracranial infection, manifests as a pus collection within the brain tissue[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Its complex pathogenesis involves a variety of infectious agents, such as bacteria[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], fungi[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and parasites[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Risk factors for the formation of a brain abscess include skull injuries, peripheral infections, a compromised immune system, malnutrition, and factors associated with advanced age[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The mortality rate for brain abscesses is around 10%, with 45% of affected patients experiencing neurological deficits post-treatment[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In elderly patients, this mortality rate increases, with studies indicating a range of 20\u0026ndash;40%[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. The Glasgow outcome scale (GOS) is a scale used to systematically evaluate post-brain injury recovery, categorizing outcomes into five levels: death, vegetative state, severe disability, moderate disability, and good recovery[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The GOS has been employed widely as a metric to assess the effectiveness of brain injury treatment and rehabilitation strategies[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNutritional status significantly influences the progression of brain abscesses and the efficacy of treatments[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Inadequate nutrition weakens immune defenses, increasing infection risks[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Furthermore, nutritional health is vital during treatment and recovery, with nutritional deficits potentially delaying wound healing, impeding neurological recovery, and prolonging the recovery process[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Such deficiencies can negatively impact patient lifespan, and quality of life, and impose significant economic costs[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Given the heightened risk of malnutrition among the elderly due to aging, conducting a simple and objective assessment of malnutrition risk is imperative to develop effective nutritional interventions. The geriatric nutritional risk index (GNRI) serves as an objective screen tool to evaluate the nutritional status of elderly individuals and its association with health risks[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The GNRI has emerged as a powerful prognostic indicator for the elderly, particularly regarding long-term postoperative outcomes[\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Numerous studies have demonstrated the utility of the GNRI in predicting outcomes among a wide range of clinical conditions in the elderly, including chronic kidney disease[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], heart failure[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], chronic obstructive pulmonary disease[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], and sepsis[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Additionally, GNRIs have relevant applications in brain-related injuries. Su et al.'s study revealed that the GNRI is a prognostic factor for death in elderly patients with moderate to severe Traumatic Brain Injuries[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Furthermore, evidence from another study highlighted that a lower GNRI is an independent predictor of brain infarction and hemorrhage in patients on maintenance hemodialysis[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Similarly, the study by Dai et al demonstrated that GNRI was related to the risk of stroke-associated pneumonia[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo our knowledge, no study has examined the nutritional status of brain abscess patients and its correlation with clinical outcomes. Therefore, this study employed the GNRI to assess the risk of malnutrition among elderly brain abscess patients, exploring the relationship between nutritional status and clinical features. Additionally, we employed the GOS to evaluate recovery post-discharge in these patients, further exploring GNRI's predictive value for GOS scores in elderly brain abscess patients\u0026rsquo; post-discharge.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and participants\u003c/h2\u003e \u003cp\u003eThis single-center prospective cohort study was executed at Huashan Hospital, Fudan University. The study population comprised individuals admitted with a diagnosis of brain abscess between August 2019 and April 2023. Patients were subjected to a follow-up period of 6 months post-discharge. The current study excludes individuals younger than 60 years and those lost to follow-up (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Ethical endorsement for this study's protocol was granted by the Research Ethics Committee of Huashan Hospital, Fudan University. This approval was secured to ascertain adherence to the ethical guidelines outlined in the Declaration of Helsinki (1975), as well as its later amendments, thereby ensuring the protection of participants' rights and well-being throughout the research.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003eDemographic and clinical characteristics\u003c/h2\u003e \u003cp\u003eDemographic and clinical data were systematically gathered, encompassing age, gender, tobacco use and alcohol consumption histories. Serum albumin levels and C-reactive protein (CRP) concentrations were documented for all subjects upon their initial evaluation, conducted within the first 48 hours post-admission. Additional details regarding therapeutic interventions employed, comorbidities were also collected. Comorbid conditions encompass a spectrum of diseases and disorders, including chronic illnesses (e.g., hypertension, diabetes mellitus, cardiovascular disorders, pulmonary pathologies, renal dysfunctions), psychiatric disorders (e.g., depressive disorders, anxiety disorders, bipolar affective disorders), autoimmune diseases (e.g., rheumatoid arthritis, systemic lupus erythematosus), neurological pathologies (e.g., Alzheimer's disease, Parkinson's disease), metabolic disorders (e.g., obesity, dyslipidemia), infectious diseases (e.g., chronic hepatitis, HIV/AIDS), and gastroenterological conditions (e.g., chronic gastritis, inflammatory bowel disease). The age-adjusted Charlson Comorbidity Index (aCCI) was employed to evaluate the aggregate risk associated with patients.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eNutritional assessment\u003c/h2\u003e \u003cp\u003eAnthropometric parameters were ascertained by trained medical personnel employing a calibrated scale equipped with a stadiometer (RGZ 120, China). Body mass index (BMI) was calculated utilizing the formula: weight (kg) / height\u003csup\u003e2\u003c/sup\u003e (m\u0026sup2;). The classification of BMI adhered to the guidelines established by the Chinese Obesity Working Group, delineating the categories as follows: underweight (\u0026lt;\u0026thinsp;18.5 kg/m\u0026sup2;), normal weight (18.5\u0026ndash;23.9 kg/m\u0026sup2;), and overweight (\u0026gt;\u0026thinsp;23.9 kg/m\u0026sup2;).\u003c/p\u003e \u003cp\u003eThe GNRI is derived through the following equation[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]:\u003cdiv id=\"Equa\" class=\"Equation\"\u003e\u003cdiv format=\"TEX\" class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e\n$$GNRI=\\frac{14.89*albumin(g/l)}{22.0}+\\frac{41.7*weight\\left(kg\\right)}{ideal weight\\left(kg\\right)}$$\u003c/div\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eThe ideal weight within this equation is ascertained via the Lorenz formula, which is contingent upon the individual's sex and stature. Should the ratio of the current to ideal weight exceed 1, it is subsequently adjusted to 1.\u003c/p\u003e \u003cp\u003eLorenz formula:\u003c/p\u003e \u003cp\u003eFor male: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(ideal weight \\left(kg\\right)=height\\left(cm\\right)-100-\\frac{height\\left(cm\\right)-150}{4}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eFor female: \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(ideal weight \\left(kg\\right)=height\\left(cm\\right)-100-\\frac{height\\left(cm\\right)-150}{2.5}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcomes\u003c/h2\u003e \u003cp\u003eThe length of stay (LOS) of each patient was recorded. LOS was defined as the interval, measured in days, extending from the initial date of admission to the terminal date of discharge. GOS was employed for the assessment of overall functional recuperation in overall. The scale is stratified into quintuple gradations as follows: GOS\u0026thinsp;=\u0026thinsp;1, death; GOS\u0026thinsp;=\u0026thinsp;2, vegetative state; GOS\u0026thinsp;=\u0026thinsp;3, severe disability; GOS\u0026thinsp;=\u0026thinsp;4, moderate disability; and GOS\u0026thinsp;=\u0026thinsp;5, good recovery.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eParticipant characteristics in this study were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD) for normally distributed continuous variables and median (interquartile range, IQR) for non-normally distributed continuous variables. Categorical variables were reported as frequencies and percentages. The t-test and Wilcoxon rank-sum test assessed differences in key indicators between groups with and without nutritional risk. Pearson correlation analysis explored factors associated with GNRI scores. Univariate logistic regression on GOS included variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.20 in a subsequent multivariate analysis. Odds ratios (OR) and 95% confidence intervals (CI) were reported. A stratified histogram depicted GOS score distributions across nutritional risk categories in brain abscess patients. The prognostic value of GNRI for elderly brain abscess patients was determined using receiver operating characteristic curve (ROC) analysis, a GOS score of 5 was classified as indicative of good recovery, whereas scores ranging from 1 to 4 were considered to reflect poor recovery. Statistical analyses were two-sided, with an alpha level of 0.05, performed using SAS V.9.4 (SAS Institute, Cary, NC, USA). R version 4.3.2, with ggplot2 and pROC packages, was used for histogram and ROC curve visualizations.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis study\u0026apos;s final analysis included a cohort of 100 elderly patients diagnosed with brain abscess. Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e revealed the median age to be 68 years (IQR 64.5\u0026ndash;72), with females constituting 61% (61/100) of the sample. In this cohort, 11% (11/100) were underweight, and 30% (30/100) were overweight. The proportion of alcohol consumption and smoking was noted in 19% (19/100) and 18% (18/100) of the patients, respectively. Comorbidities were prevalent in elderly brain abscess patients, with the median number of comorbidities being 2 (IQR 0\u0026ndash;3). GNRI assessments conducted within 48 hours of admission indicated malnutrition risks in 48% of patients, with 4% facing major malnutrition risk, 23% moderate risk, and 21% low risk. The median hospital stay duration was 15 days (IQR 10\u0026ndash;22), and the median GOS score at 6 months post-discharge was 5 (IQR 3\u0026ndash;5), reflecting generally favorable outcomes.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCharacteristcs of this study participants.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWhole study group (n\u0026thinsp;=\u0026thinsp;100)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (year) (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.0 (64.5\u0026ndash;72.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e61 (61.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHeight (cm) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e166.05\u0026thinsp;\u0026plusmn;\u0026thinsp;7.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eWeight (kg) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62.22\u0026thinsp;\u0026plusmn;\u0026thinsp;10.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22.50\u0026thinsp;\u0026plusmn;\u0026thinsp;3.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnderweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (11.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal weight (18.5\u0026ndash;23.9 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (59.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverweight (\u0026gt;\u0026thinsp;23.9 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e30 (30.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status (n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent or former\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81 (81.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking status (n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent or former\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (18.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82 (82.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaCCI score (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (days) (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (10\u0026ndash;22)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOS score (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (3\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMalnutrition risk to GNRI (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (48.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMajor malnutritional risk (GNRI: \u0026lt;82)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate malnutritional risk (GNRI: 82\u0026ndash;91)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (23.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLow malnutritional risk (GNRI: 92\u0026ndash;98)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (21.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\"\u003eIQR, Interquartile range; BMI, Body mass index; aCCI, age-adjusted Charlson Comorbidity Index; LOS, Length of stay; GOS, Glasgow outcome scale; GNRI, Geriatric nutritional risk index\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e, individuals at risk for malnutrition had significantly lower BMI compared to those not at risk (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This group also had a higher median comorbidity count of 3 (IQR 1\u0026ndash;4) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting a higher burden of comorbid conditions. Furthermore, aCCI scores were significantly higher in the malnutrition risk group (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Admission CRP levels were also higher in the malnutrition risk group than in the non-risk group (P\u0026thinsp;=\u0026thinsp;0.017), indicating more severe inflammation. Treatment strategies varied, with a larger fraction of the malnutrition risk group receiving conservative medical treatment (66.7%) compared to the non-risk group (38.5%) (P\u0026thinsp;=\u0026thinsp;0.003). Additionally, the malnutrition risk group had lower median GOS scores of 3 (IQR 3\u0026ndash;4) (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a worse prognosis.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eA comparative analysis of demographic and clinical characteristics between patients with and without malnutrition risk according to GNRI\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo malnutrition risk\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;52)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMalnutrition risk\u003c/p\u003e\n \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;48)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (year) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.04\u0026thinsp;\u0026plusmn;\u0026thinsp;5.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68.77\u0026thinsp;\u0026plusmn;\u0026thinsp;5.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.492\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (54.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (kg/m\u0026sup2;) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.74\u0026thinsp;\u0026plusmn;\u0026thinsp;2.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eUnderweight (\u0026lt;\u0026thinsp;18.5 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal weight (18.5\u0026ndash;23.9 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (48.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (70.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverweight (\u0026gt;\u0026thinsp;23.9 kg/m\u003c/strong\u003e\u003csup\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003cstrong\u003e) (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25 (48.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status (n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.342\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent or former\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (77.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking status (n,%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCurrent or former\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (15.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNever\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (84.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (79.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (0\u0026ndash;2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (1\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaCCI score (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (2\u0026ndash;3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP (mg/L) (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4.3 (1.8\u0026ndash;16.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.6 (4.9\u0026ndash;42.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment modality (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eConservative therapeutic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAspiration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11 (22.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eExcession\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (28.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (10.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (days) (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.5(10.0\u0026ndash;62.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.5 (9.0-23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.822\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOS score (median, IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (5\u0026ndash;5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (3\u0026ndash;4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\"\u003eGNRI, Geriatric nutritional risk index; BMI, Body mass index; IQR, Interquartile range; aCCI, age-adjusted Charlson Comorbidity Index; CRP: C-reactive protein; LOS, Length of stay; GOS, Glasgow outcome scale\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e demonstrated the relationships between GNRI scores and various clinical parameters. Specifically, CRP levels (Spearman\u0026apos;s \u0026rho;=\u0026minus;0.291, P\u0026thinsp;=\u0026thinsp;0.006), the total number of comorbidities (Spearman\u0026apos;s \u0026rho;=\u0026minus;0.284, P\u0026thinsp;=\u0026thinsp;0.004), and aCCI scores (Spearman\u0026apos;s \u0026rho;=\u0026minus;0.310, P\u0026thinsp;=\u0026thinsp;0.002) are inversely correlated with GNRI scores. In contrast, GOS scores show a strong positive correlation with GNRI scores (Spearman\u0026apos;s \u0026rho;\u0026thinsp;=\u0026thinsp;0.624, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating that higher nutritional status is associated with better neurological outcomes. Figure\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e delineates the distribution of GOS scores across varying malnutrition risk categories, with the precise value distribution elaborated in Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) [see Additional file 1]. Furthermore, by assigning numerical values to surgical methods\u0026mdash;1 for conservative therapeutic, 2 for aspiration, and 3 for excision\u0026mdash;a positive correlation is observed between these values and GNRI scores (Spearman\u0026apos;s \u0026rho;\u0026thinsp;=\u0026thinsp;0.340, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This suggests a preference for conservative treatment in patients with poorer nutritional status, consistent with the trends shown in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation analysis of potential factors associated with GNRI score.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpearman\u0026apos;s \u0026rho;\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge(y)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.099\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.328\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP (mg/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.291\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.182\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.069\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.139\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.168\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment modality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.284\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaCCI score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.310\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (days)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGOS score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.624\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\"\u003eGNRI, Geriatric nutritional risk index; BMI, Body mass index; aCCI, age-adjusted Charlson Comorbidity Index; CRP, C-reactive protein; LOS, Length of stay; GOS, Glasgow outcome scale\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the univariate logistic regression analyses, the association of each predictor variable with the GOS score was assessed. The results revealed no significant correlation for age or gender with the GOS score. BMI and GNRI score were significantly negatively correlated with the GOS score, whereas CRP、aCCI score, and number of comorbidities showed a positive correlation with the GOS score. In the subsequent multivariable logistic regression analysis, which incorporated variables with a P-value of less than 0.2 from the univariate analysis, GNRI was found to have a significant negative correlation with GOS score (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e). This highlights GNRI\u0026apos;s potential as a predictive factor for outcomes. Additionally, Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e showed the ROC curve for GNRI in predicting poor recovery. The analysis yielded an Area Under the Curve (AUC) of 0.903, with the 95% Confidence Interval (CI) extending from 0.832 to 0.975. At the optimal threshold of 97.50, with a sensitivity of 90.57% and a specificity of 87.23% in predicting recovery outcomes.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eLogistic regression analysis for GOS as a dependent variable\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eUnivariate\u003c/p\u003e\n \u003c/th\u003e\n \u003cth colspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eMultivariate\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eOR (95%CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.063 (0.991\u0026ndash;1.141)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.012 (0.902\u0026ndash;1.135)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003esex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.520 (0.244\u0026ndash;1.109)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.091\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.829 (0.288\u0026ndash;2.384)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.728\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.757 (0.656\u0026ndash;0.874)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.908 (0.721\u0026ndash;1.144)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.413\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.581 (0.629\u0026ndash;3.972)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrinking status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.413 (0.948\u0026ndash;6.146)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.154 (0.253\u0026ndash;5.265)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.853\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCRP (mg/L)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.012 (1.004\u0026ndash;1.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.010 (0.999\u0026ndash;1.021)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.073\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment modality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.669 (0.409\u0026ndash;1.094)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.338 (0.654\u0026ndash;2.738)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.425\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.216 (1.041\u0026ndash;1.420)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.969 (0.748\u0026ndash;1.254)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eaCCI score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.024 (1.411\u0026ndash;2.903)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.456 (0.800-0.916)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.995 (0.965\u0026ndash;1.023)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGNRI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.826 (0.775\u0026ndash;0.880)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.830 (0.752\u0026ndash;0.916)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eGOS, Glasgow outcome scale; BMI, Body mass index; CRP, C-reactive protein; aCCI, age-adjusted Charlson Comorbidity Index; LOS, Length of stay; GNRI, Geriatric nutritional risk index\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eUnivariate: Univariate logistic regression analysis\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eMultivariate: Multivariate logistic regression analysis: inclusion of predictors exhibiting univariate logistic regression outcomes with \u003cem\u003eP\u003c/em\u003e\u0026lt;0.20\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study represents the first study into the association between malnutrition risk, as determined by the GNRI, and clinical outcomes in elderly patients with brain abscess. Findings from this prospective cohort study revealed that nearly half of the elderly brain abscess patients exhibited malnutritional risk, which is related to their treatment modality as well. Concurrently, the GNRI displayed associations with both the quantum of comorbidities and the aCCI score, underscoring the intricate interplay between nutritional status and the aggregate health burden in this demographic. Notably, elderly brain abscess patients presenting with lower GNRI scores were observed to have diminished GOS scores, indicating that GNRI has a predictive impact on their clinical outcomes.\u003c/p\u003e \u003cp\u003eMalnutrition, often underreported and underdiagnosed, is widespread among elderly hospitalized patients, contributing to adverse clinical outcomes such as prolonged hospital stays and elevated mortality rates[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The GNRI provides an efficient, objective, and age-specific approach to nutritional screening in the elderly[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. It assesses the nutritional risks of the elderly in a timely and accurate manner by utilizing current weight metrics and serum albumin levels, thereby minimizing recall bias associated with past weight changes[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, the GNRI was employed to assess the malnutrition risk in elderly patients with brain abscesses, revealing a significant prevalence of 48%. Similarly, Bao et al.'s study revealed that among elderly patients experiencing early neurological deterioration following acute ischemic stroke, 48.3% were at risk of malnutrition according to GNRI[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In another study, the GNRI assessment revealed a malnutrition risk of approximately 42.5% (97/228) among elderly patients with mild traumatic brain injury[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. These results above suggest that brain injury in elderly patients is often accompanied by malnutrition. This high incidence of malnutrition in the elderly may be attributed to various factors. With advancing age, oral issues such as missing teeth impair chewing ability, impacting food intake and digestion[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Moreover, elderly individuals frequently contend with chronic diseases like diabetes and heart disease, potentially increasing metabolic demands and subsequently heightening the risk of malnutrition[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. This study's findings revealed a significant negative correlation between GNRI and the level of comorbidity, further substantiated that the heightened burden of chronic diseases contributes to the increased risk of malnutrition.\u003c/p\u003e \u003cp\u003eAs an infectious disease affecting the nervous system, brain abscesses induce inflammation that escalates the body's metabolic demands, thereby heightening nutritional requirements[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. This, combined with the adverse effects of infection and pharmacological treatments on appetite, can precipitate a further decline in the nutritional status of patients with brain abscesses[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In the correlation analysis conducted in this study, the GNRI and CRP values upon admission in elderly patients with brain abscesses were found to be significantly negatively correlated (P\u0026thinsp;=\u0026thinsp;0.006), thereby further indicating the relation between the level of inflammation and the nutritional risk. Furthermore, we observed that patients at nutritional risk underwent more conservative treatment during hospitalization compared to their counterparts without nutritional risk (38.5% vs 66.7%). This finding implies that the nutritional status of elderly patients with brain abscess may influence their treatment approach.\u003c/p\u003e \u003cp\u003eIn clinical practice, the typical focus on infection control and acute neurological symptom management in brain abscess cases often overshadows the scrutiny of patients' nutritional status. The findings of this study indicated that elderly brain abscess patients at higher malnutrition risk exhibit poorer clinical prognoses (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A positive correlation emerged between GNRI scores and GOS scores(P\u0026thinsp;\u0026lt;\u0026thinsp;0.001), indicating a nutritional status may be significantly associated with recovery and long-term outcomes in brain abscess patients. Several studies also have demonstrated a correlation between elevated malnutrition risks and adverse clinical outcomes in geriatric patients[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. It can be seen that in the process of diagnosis and treatment of geriatric diseases, the assessment of nutritional status cannot be ignored.\u003c/p\u003e \u003cp\u003eGNRI has been employed as an independent predictive factor for morbidity and mortality in elderly hospitalized patients with cancer [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Research on elderly colorectal cancer patients revealed that the preoperative GNRI served as an independent prognostic factor for those who underwent curative colorectal resection[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. In another study, the GNRI has been identified as an independent predictor of prognosis and postoperative complications after radical nephroureterectomy for upper urinary tract urothelial carcinoma[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. In addition to its extensive application in forecasting postoperative complications and the long-term prognosis of tumors, the GNRI was also employed in other diseases for its prognostic significance for recuperation and clinical outcomes. A study focused on elderly patients with mild traumatic brain injury revealed that a higher GNRI was associated with a decreased risk of incomplete recovery at the 6-month mark. Furthermore, the ROC analysis established a GNRI threshold of 97.85[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. And GNRI was considered a promising tool for predicting mortality outcomes in older patients with moderate to severe TBI[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. These findings indicated that GNRI may have applicability in diseases related to brain injury. In our multivariate regression analysis, we found that lower GNRI values were positively associated with poorer prognosis (i.e., lower GOS score). Moreover, the results of the ROC analysis, which yielded an AUC of 0.903, underscore the significant potential of GNRI in predicting the long-term outcomes for elderly patients with brain abscess.\u003c/p\u003e \u003cp\u003eOur study offered several strengths. Firstly, as a prospective cohort study, the high standardization of our data collection protocols ensures data quality, while simultaneously reducing selection and recall biases. Secondly, this is the inaugural investigation into the prevalence of nutritional risk among elderly patients with brain abscesses, providing a novel insight into the clinical implications of GNRI scores. Furthermore, our use of logistic regression analysis has elucidated the relationship between GNRI and the prognostic score for geriatric brain abscesses (GOS), affirming GNRI's utility in predicting outcomes for elderly hospitalized patients with brain abscesses. This study, while providing valuable insights, has certain limitations. Firstly, being a single-center study, the generalizability of the results to broader populations may be compromised. Secondly, the relatively small cohort size could diminish the statistical power, potentially impacting the robustness of the findings. Thirdly, the reliance on the GNRI, which is primarily based on current weight, may not adequately capture changes in a patient's nutritional status over time. Therefore, future research should be conducted across multiple centers, incorporate larger patient samples, and integrate additional nutritional assessment methods, such as Dual-energy X-ray Absorptiometry (DXA) or Bioelectrical Impedance Analysis (BIA). To deepen our understanding of the nutritional status of elderly patients with brain abscess and further explore the impact of nutritional status on treatment and clinical outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis inaugural study on the nutritional status of elderly patients with brain abscesses revealed that nearly half are at risk of malnutrition according to the GNRI. The GNRI is correlated with the number of comorbidities, aCCI scores, and treatment modalities, underscoring the intricate relationship between nutritional status and the overall health burden in this demographic. Moreover, the study observed that lower GNRI scores in these patients were associated with decreased GOS scores, and found that GNRI is a prognostic indicator of clinical outcomes. Clinically, heightened attention is warranted for patients with GNRI scores below the critical threshold of 97.5, and prompt nutritional interventions should be administered. Consequently, we advocate regular nutritional evaluations for all elderly patients with brain abscesses, ensuring early intervention with nutritional therapy to preserve their nutritional health and mitigate the risk of adverse outcomes.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eGOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eGlasgow Outcome Scale\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eGNRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eGeriatric Nutritional Risk Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eaCCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eage-adjusted Charlson Comorbidity Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eBody mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eLOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eLength of stay\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eOdds ratios\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eConfidence intervals\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eROC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eReceiver operating characteristic curve\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eDXA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eDual-energy X-ray Absorptiometry\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25.678119349005424%\" valign=\"top\"\u003e\n \u003cp\u003eBIA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"74.32188065099457%\" valign=\"top\"\u003e\n \u003cp\u003eBioelectrical Impedance Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to the staff responsible for data collection and patient follow-up, as well as to the participants and their families, for their invaluable cooperation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors confirm contributions as follows: Study conception and design were carried out by HSS, TM, and PX. Data collection was performed by ZYT, JDF, FJY, ZM and NY. Analysis was conducted by HSS and PX. The initial draft of the manuscript was prepared by PX and HSS, while TM, NY, and HSS critically reviewed and revised it for important intellectual content. All authors have read and approved the final manuscript for publication and accept responsibility for the work\u0026rsquo;s accuracy and integrity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo funding was secured for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data underpinning the findings of this study can be obtained from the corresponding author upon reasonable request.\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 Ethics Committee of Huashan Hospital affiliated with Fudan University School of Medicine (No. KY2023-847).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBrouwer MC, Tunkel AR, McKhann GM 2nd, van de Beek D. 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BMJ Open Respir Res 2023, 10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLee JS, Choi HS, Ko YG, Yun DH. Performance of the Geriatric Nutritional Risk Index in predicting 28-day hospital mortality in older adult patients with sepsis. Clin Nutr. 2013;32:843\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu WT, Tsai CH, Huang CY, Chou SE, Li C, Hsu SY, Hsieh CH. Geriatric Nutritional Risk Index as a Prognostic Factor for Mortality in Elderly Patients with Moderate to Severe Traumatic Brain Injuries. Risk Manag Healthc Policy. 2021;14:2465\u0026ndash;74.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsuneyoshi S, Matsukuma Y, Kawai Y, Hiyamuta H, Yamada S, Kitamura H, Tanaka S, Taniguchi M, Tsuruya K, Nakano T, Kitazono T. Association between geriatric nutritional risk index and stroke risk in hemodialysis patients: 10-Years outcome of the Q-Cohort study. 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Front Neurol. 2023;14:1131085.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorcoran C, Murphy C, Culligan EP, Walton J, Sleator RD. Malnutrition in the elderly. Sci Prog. 2019;102:171\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMathew AC, Das D, Sampath S, Vijayakumar M, Ramakrishnan N, Ravishankar SL. Prevalence and correlates of malnutrition among elderly in an urban area in Coimbatore. Indian J Public Health. 2016;60:112\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatona P, Katona-Apte J. The interaction between nutrition and infection. Clin Infect Dis. 2008;46:1582\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFang P, Yang Q, Zhou J, Yang Y, Luan S, Xiao X, Li X, Gu Y, Shang Q, Zhang H, et al. The impact of geriatric nutritional risk index on esophageal squamous cell carcinoma patients with neoadjuvant therapy followed by esophagectomy. Front Nutr. 2022;9:983038.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao X, Li D, Zhang N. Geriatric Nutritional Risk Index as a predictor for mortality: a meta-analysis of observational studies. Nutr Res. 2019;71:8\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHayama T, Hashiguchi Y, Ozawa T, Watanabe M, Fukushima Y, Shimada R, Nozawa K, Matsuda K, Fujii S, Fukagawa T. The preoperative geriatric nutritional risk index (GNRI) is an independent prognostic factor in elderly patients underwent curative resection for colorectal cancer. Sci Rep. 2022;12:3682.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu P, Liu J, Wang X, Lai S, Wang J, Wang J, Wang J, Zhang Y, Hao Q. Development and validation of a nomogram based on geriatric nutritional risk index for predicting prognosis and postoperative complications in surgical patients with upper urinary tract urothelial carcinoma. J Cancer Res Clin Oncol. 2023;149:18185\u0026ndash;200.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Geriatric Nutritional Risk Index (GNRI), brain abscess, Glasgow Outcome Scale (GOS), prognosis","lastPublishedDoi":"10.21203/rs.3.rs-4020068/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4020068/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eThe Geriatric Nutritional Risk Index (GNRI) is a straightforward and objective tool for nutritional screening in elderly patients and has been demonstrated to possess prognostic predictive value in several diseases. Nonetheless, there is a lack of research on the nutritional risk associated with brain abscess in the elderly. This study aimed to evaluate the prevalence of nutritional risk among these patients by GNRI and to investigate its potential prognostic value for clinical outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eFrom August 2019 to April 2023, 100 elderly patients diagnosed with brain abscess were enrolled in the study. The collected data encompassed age, gender, body mass index (BMI), smoking and alcohol consumption history, number of comorbidities, length of hospital stay (LOS), serum albumin and C-reactive protein (CRP) levels at admission and calculated the GNRI, the Glasgow outcome scale (GOS) score 6 months post-discharge. A GOS score of 5 was considered indicative of a good recovery, whereas scores ranging from 1 to 4 were classified as poor recovery.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe prevalence of malnutrition risk among elderly patients with brain abscesses was found to be 48% according to GNRI. Compared to those without nutritional risk, patients at risk exhibited significantly higher post-admission C-reactive protein (CRP) levels (P=0.017), a greater number of comorbidities (P\u0026lt;0.001), and elevated age-adjusted Charlson Comorbidity Index (aCCI) scores (P\u0026lt;0.001). Spearman correlation analysis revealed a negative correlation between GNRI scores and CRP levels, the number of comorbidities, and aCCI scores (Spearman's ρ=-0.291, -0.284, and -0.310, respectively), and a positive correlation with Glasgow Outcome Scale (GOS) scores (Spearman's ρ=0.624, P\u0026lt;0.001). Multivariate logistic regression analysis indicated that lower GNRI values in these patients were associated with reduced GOS levels (OR = 0.826, 95% CI: 0.775-0.880). Furthermore, receiver operating characteristic (ROC) analysis identified a GNRI threshold of 97.50 for predicting poor recovery, with a sensitivity of 90.57% and a specificity of 87.23%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Elderly brain abscess patients exhibited a high malnutrition risk. GNRI showed an important predictive value for recovery in elderly patients, which could be helpful in clinical intervention and rehabilitation.\u003c/p\u003e","manuscriptTitle":"Geriatric Nutritional Risk Index has a Prognostic value for Recovery Outcomes in Elderly Patients with Brain Abscess","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-11 19:19:35","doi":"10.21203/rs.3.rs-4020068/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"51e68e49-c56b-4c73-8a6a-a5968e259ebd","owner":[],"postedDate":"March 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-11T20:04:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-11 19:19:35","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4020068","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4020068","identity":"rs-4020068","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}