Impact of SARS-CoV-2 Variants and Vaccination on Pediatric Febrile Seizures: A Retrospective Cohort Study

Impact of SARS-CoV-2 Variants and Vaccination on Pediatric Febrile Seizures: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Impact of SARS-CoV-2 Variants and Vaccination on Pediatric Febrile Seizures: A Retrospective Cohort Study Mei Yang, Yanzu Wang, Jing Gao, Chunlan Yao, Gangxi Lin, Caijin Yan This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6189452/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Nov, 2025 Read the published version in BMC Pediatrics → Version 1 posted 19 You are reading this latest preprint version Abstract Objective This study aimed to investigate the associations between SARS-CoV-2 variants, neuroinflammatory markers, vaccination history, and demographic characteristics in relation to the occurrence of febrile seizures (FS) in pediatric patients at a single tertiary medical center. Methods Retrospective cohort data were collected from a pediatric tertiary care institution between April 2020 and January 2023, encompassing 339 patients with PCR-confirmed SARS-CoV-2 infections. The cohort was separated into FS (n=102) and control (n=237) groups. A multivariable logistic regression analysis was employed to evaluate the impact of viral variants (Delta and Omicron sublineages), inflammatory markers (IL-6, D-dimer, CRP), vaccination status (unvaccinated, partially vaccinated, fully vaccinated), and demographic variables, while controlling for potential confounders. Results The incidence of FS among infants under one year of age was found to be 41.2%, in contrast to 17.7% in older children (OR=3.2, 95% CI: 1.8–5.7; P <0.001). Elevated levels of IL-6 exceeding 10 pg/mL and D-dimer levels surpassing 0.5 mg/L were independently associated with increased FS severity (adjusted OR [aOR]=2.8 and 2.1, respectively), as well as a 3.1-fold increase in the risk of recurrence. Full vaccination was linked to a 68% reduction in FS risk (aOR=0.32, 95% CI: 0.18–0.55), particularly benefiting infants. Additionally, male infants exhibited a 1.8-fold increased vulnerability ( P =0.016). Omicron sublineages (BA.5/XBB), which accounted for 78.4% of FS cases, correlated with heightened biomarker levels. Conclusion The findings suggest that IL-6 and D-dimer serve as valuable indicators for assessing the risk of FS in children infected with SARS-CoV-2. The protective effect of vaccination on neural tissues, in addition to its role in reducing viral transmission, is evident, highlighting the increased susceptibility in male infants. Febrile seizures SARS-CoV-2 variants (COVID-19) Neuroinflammation Pediatric vaccinaion Biomarker thresholds Sex disparities Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Key Points Neuroinflammatory Biomarkers in Pediatric Seizures: IL-6 and D-dimer are identified as significant mediators of SARS-CoV-2-related FS, reflecting a thromboinflammatory mechanism that is distinct from systemic hyperinflammation. Vaccination and Neurological Outcomes: Vaccination reduces the risk of FS through immune modulation, thereby extending its protective effects to encompass neuroprotection. Developmental Susceptibility in Male Infants: The increased susceptibility observed in male infants is associated with androgen-mediated pathways and the immature function of the blood-brain barrier during early stages of development. 1. Introduction The ongoing evolution of SARS-CoV-2 continues to challenge pediatric healthcare systems, as mounting evidence correlates the virus with neurological complications, particularly febrile seizures (FS). Characterized by generalized convulsions precipitated by fever (≥ 38°C) in the absence of central nervous system (CNS) infection or metabolic disturbances, FS is emerging as a significant concern among children infected with SARS-CoV-2, exhibiting an incidence rate 2.5 times higher than that observed with other viral infections (95% CI: 1.8–3.4) [ 1 ]. During the predominance of the Omicron variant, hospitalization rates in the pediatric population reached 48.2 per 100,000 children under 18 years, with 26.4% necessitating intensive care, particularly among unvaccinated individuals and those with comorbidities such as obesity or chronic respiratory conditions [ 2 ][ 3 ]. These trends underscore the pressing need to comprehend FS within this demographic. Despite vaccination demonstrating 75–78% efficacy in preventing severe outcomes, including multisystem inflammatory syndrome in children (MIS-C), coverage among infants (under 1 year) remains suboptimal, leaving this vulnerable group susceptible to neuroinflammatory complications due to the immature integrity of the blood-brain barrier and diminishing maternal antibody protection [ 4 ][ 5 ]. While there is an increasing body of evidence regarding neurological complications in pediatric COVID-19 cases, the specific risks associated with different variants for FS, as well as the neuroprotective benefits of vaccination, remain inadequately understood, highlighting a critical research gap that this study aims to fill. The mechanistic underpinnings of SARS-CoV-2-induced FS likely involve inflammatory and coagulopathic pathways. Elevated levels of IL-6, a cytokine recognized for its capacity to disrupt the functionality of the blood-brain barrier, and D-dimer, a product of fibrin degradation indicative of coagulopathy, have been associated with negative neurological outcomes in pediatric populations [ 6 ][ 7 ]. However, the precise role of this biomarker in febrile seizures (FS) across different viral variants remains inadequately defined [ 8 ]. Additionally, there is a notable increased vulnerability among male infants to severe SARS-CoV-2 infections, potentially attributable to androgen-mediated upregulation of angiotensin-converting enzyme 2 (ACE2), which facilitates the entry of the virus [ 9 ]. Several critical inquiries remain unresolved: Variant-specific neurotropism : Do the Omicron sublineages (e.g., BA.5, XBB.1.5), characterized by enhanced immune evasion and modified tissue affinity, influence the risk of FS differently? [ 10 ][ 11 ] Biomarker thresholds : Are certain cutoff values for IL-6 or D-dimer effective for predicting the recurrence of FS or serve as targets for therapeutic intervention? [ 12 ] Vaccination-mediated neuroprotection : In addition to reducing viral replication, does vaccination influence neuroinflammatory pathways in pediatric patients? [ 13 ] Unlike previous studies that primarily focused on systemic inflammation, the present data merge variant-specific genomic analysis with biomarkers pertinent to neurology to better understand the risk associated with FS. This investigation, derived from a single-center retrospective cohort, examines the interactions among SARS-CoV-2 variants, inflammatory biomarkers, vaccination status, and demographic characteristics in children with FS. The underlying hypotheses posit that inflammatory markers can predict the severity and recurrence of FS, that complete vaccination diminishes neuroinflammation, that male infants are at a heightened risk, and that Omicron sublineages are linked to a higher incidence of FS compared to ancestral strains. Hypotheses Omicron sublineages elevate the risk of FS in comparison to Delta due to their heightened neurotropism. Increased levels of IL-6 and D-dimer serve as predictors of FS severity and recurrence through mechanisms related to neuroinflammation and coagulopathy. Complete vaccination modulates immune responses, thereby reducing neuroinflammation and providing neuroprotective benefits beyond merely controlling the virus. 2. Materials and Methods 2.1 Study Design and Setting Data for this retrospective cohort study were sourced from the First Affiliated Hospital of Xiamen University, a tertiary pediatric center in southeastern China that manages SARS-CoV-2 cases. The study period spanned from April 2020 to January 2023, encompassing waves associated with Delta and Omicron sublineages (BA.5/XBB). The cohort included 339 patients, determined based on a targeted FS incidence of 10% and an odds ratio of 2.0 (α = 0.05, power = 80%). The sample size was derived using a formula for proportion comparison in cohort studies: n = [Zα/2 + Zβ]² * [p1(1-p1) + p2(1-p2)] / (p1-p2)², where p1 = 0.10 (FS incidence in controls), p2 = 0.182 (FS incidence with OR = 2.0), Zα/2 = 1.96 (α = 0.05), and Zβ = 0.84 (power = 80%), resulting in a minimum sample size of approximately 316 patients, which was then adjusted to 339 for enhanced reliability. 2.2 Study Population Inclusion Criteria Patients under the age of 18 with RT-PCR-confirmed SARS-CoV-2 infection. Availability of thorough clinical records, including vaccination history and serial assessments of inflammatory biomarkers (IL-6, D-dimer, CRP) within 24 hours of admission, along with documentation of neurological assessments. Exclusion Criteria Pre-existing neurological conditions such as epilepsy or structural brain abnormalities. Non-febrile seizures caused by conditions like hypoglycemia (glucose < 3.9 mmol/L) or electrolyte imbalances. Incomplete records regarding biomarkers or vaccination status (more than 5% missing data). 2.3 Data Collection and Variables Vaccination Status Unvaccinated : No doses of inactivated SARS-CoV-2 vaccines (e.g., Sinovac-CoronaVac, Sinopharm-BBIBP). Partially vaccinated : One dose administered at least 14 days prior to infection. Fully vaccinated : Two or more doses given with an interval of at least 21 days, defined as the completion of two doses, with the last administered at least 14 days before infection. Covariates Age categories: ( 10 years). Sex, comorbid disorders (e.g., asthma), and administration of antiviral or immunomodulatory treatments (e.g., remdesivir). 2.4 Statistical Analysis The statistical evaluation was conducted using SPSS (version 27.0; IBM) and R (version 4.2.2). Continuous variables were represented as medians with corresponding interquartile ranges (IQR) and were analyzed using the Mann-Whitney U test for comparison. For categorical variables, χ² tests or Fisher’s exact tests were employed. Multivariable logistic regression models, adjusted for age, sex, and comorbidities, provided adjusted odds ratios (aORs) for the risk of febrile seizures (FS), implementing Bonferroni correction (α = 0.01) to account for multiple comparisons. The Bonferroni correction was applied by dividing the overall α (0.05) by the number of primary predictors (including five key variables: age, sex, vaccination status, IL-6, and D-dimer), thus establishing a significance threshold of 0.01 for each test. Sensitivity analyses incorporated restricted cubic splines to evaluate nonlinear relationships and utilized complete-case analysis for validation purposes. Missing data, which constituted less than 5%, were addressed through multiple imputation using the ‘mice’ package in R (5 iterations), with no significant impact on outcomes (P > 0.05). The imputation process included age, sex, vaccination status, and biomarker levels as predictors in the MICE algorithm to ensure reliable estimates. 2.5 Ethical Approval The study protocol ([2024] Research Ethics Review No. 064) received endorsement from the Institutional Review Board of the First Affiliated Hospital of Xiamen University. The requirement for informed consent was waived owing to the retrospective analysis of anonymized data, with all patient identifiers being removed prior to the analysis. 3. Results 3.1 Cohort Stratification and Demographic Risk Landscape The analyzed cohort consisted of 339 pediatric patients diagnosed with SARS-CoV-2 infection (FS group: n=102; control group: n=237), revealing significant age-related disparities (refer to Table 1 ). Infants younger than 1 year represented 41.2% of FS cases, as opposed to 25.3% in the control group ( P <0.001; aOR=3.5, 95% CI: 1.8–6.8; see Table 2 ). Conversely, adolescents aged over 10 years demonstrated the lowest incidence of FS (9.8% versus 20.7%; P =0.006). Within the infant demographic, male patients exhibited a 1.8-fold increased risk compared to females (aOR=1.8, 95% CI: 1.1–2.9; P =0.016). Vaccination status markedly impacted outcomes: unvaccinated individuals comprised 89.2% of FS cases versus 68.8% in the control group ( P <0.001), and full vaccination correlated with a 68% decrease in FS risk (aOR=0.32, 95% CI: 0.18–0.55; refer to Table 2 ), with the most pronounced effect observed in infants (the odds ratio decreased from 3.5 to 1.8). The duration of hospital stays was significantly prolonged in the FS group (median: 5 days, IQR: 3–7) compared to controls (median: 3 days, IQR: 2–5; P =0.002, Mann-Whitney U=7842), suggesting potentially greater clinical severity or a higher requirement for management. 3.2 Neuroinflammatory Biomarkers: Precision Thresholds for Risk Stratification Patients experiencing FS displayed distinctive biomarker profiles (see Table 3 ; Figure 1 ). The concentrations of IL-6 were significantly elevated ( P =0.02), with levels surpassing 10 pg/mL correlating with a 3.1-fold increased risk of recurrence (OR=3.1, 95% CI: 1.8–5.4; aOR=2.8, see Table 2 ). D-dimer levels were similarly elevated ( P <0.01), with values exceeding 0.5 mg/L independently associated with recurrence (aOR=2.4, 95% CI: 1.3–4.5). Conversely, CRP levels did not reveal significant differences across groups ( P =0.15), highlighting its limited relevance in neurospecific contexts. The receiver operating characteristic (ROC) analysis substantiated IL-6 >10 pg/mL (AUC=0.78; sensitivity=82%; specificity=73%) and D-dimer >0.5 mg/L (AUC=0.71; sensitivity=75%; specificity=68%) as optimal diagnostic thresholds, surpassing CRP (AUC=0.52; refer to Figure 4 ). 3.3 Variant-Driven Pathogenesis: Omicron’s Neurotropic Shift Among the FS cases, Omicron sublineages (BA.5: 65%; XBB.1.5: 35%) were predominant (78.4%), leading to a 2.2-fold heightened risk in infants when compared to the Delta variant (aOR=2.2, 95% CI: 1.2–4.0; P =0.01; refer to Figure 2 ), accompanied by increased levels of IL-6 and D-dimer. The underrepresentation of Delta variant cases, which accounted for less than 22%, may diminish its comparative efficacy. 3.4 Age-Sex Interaction: Identification of Vulnerability Hotspots The incidence of febrile seizures (FS) reached its highest point among male infants under one year of age, recorded at 41.2% (95% CI: 32.5–50.1), and exhibited a decreasing trend with advancing age. In contrast, the incidence reached its lowest point among female adolescents over the age of ten, at 8.2% (refer to Figure 3 ), underscoring the age- and sex-dependent patterns of susceptibility. 3.5 Threshold Optimization: Achieving an Equilibrium of Sensitivity and Specificity IL-6 levels surpassing 10 pg/mL (Youden index=0.55) exhibited enhanced diagnostic accuracy when compared to D-dimer levels exceeding 0.5 mg/L (Youden index=0.43; see Figure 5 ), aligning with IL-6’s recognized function in neuronal hyperexcitability. The moderate effectiveness of D-dimer suggests the potential benefit of employing a composite biomarker strategy. 3.6 Sensitivity Analyses and Model Robustness A consistent outcome was noted between complete-case and imputed analyses (ΔaOR0.05), thereby reinforcing the credibility of the proposed thresholds. 4. Discussion 4.1 Neuroinflammatory Cascades: Expanding Beyond Cytokine Storms The increased levels of IL-6 and D-dimer in FS cases (refer to Table 3 ) indicate the presence of a neuroinflammatory cascade that is separate from systemic hyperinflammation, a phenomenon that is gaining recognition in the context of SARS-CoV-2 neuropathology [14][15]. The prolonged duration of hospitalization for the FS group ( P =0.002; Table 1 ) likely reflects a greater severity of the disease or the necessity for extended observation due to the risk of seizure recurrence, emphasizing the clinical challenges posed by FS in this demographic, and highlighting the potential role of IL-6 and D-dimer as indicators for resource allocation. IL-6 as a Mediator of Neuroinflammation IL-6 is a versatile cytokine that plays a pivotal role in the immune response to viral infections. Under inflammatory conditions, it is capable of crossing the blood-brain barrier (BBB), which leads to the activation of microglia and astrocytes, the central nervous system’s resident immune cells [16]. This activation instigates a cascade of pro-inflammatory cytokines, including TNF-α and IL-1β, which can exacerbate neuronal injury and provoke seizure activity [17]. The elevated IL-6 levels documented in this study ( Table 3 ) imply that IL-6 may enhance neuronal hyperexcitability through the mediation of N-methyl-D-aspartate (NMDA) receptors in the hippocampus [18]. This increased excitability may be driven by IL-6-induced activation of glial cells, particularly astrocytes, which release additional pro-inflammatory cytokines, further contributing to neuronal damage [19]. D-dimer and Coagulopathy The significant rise in D-dimer levels ( Table 3 ) suggests a hypercoagulable state, potentially induced by SARS-CoV-2-related endothelial dysfunction and complement activation [20]. Elevated D-dimer levels have been associated with cerebral microthrombosis and the disruption of the BBB, which facilitates viral entry and neuroinvasion [21]. This coagulopathic mechanism may play a role in the observed escalation of FS severity and recurrence, as microthrombi can induce localized ischemia and neuronal impairment [22]. The lack of significant differentiation in CRP levels ( P =0.15; Table 3 ) highlights the restricted utility of CRP as a neurospecific marker, advocating for the implementation of CNS-focused biomarker panels in clinical practice [23]. 4.2 Vaccination and Neuroimmune Interactions: Elucidating Mechanisms Full vaccination was linked to a 68% reduction in the risk of FS (aOR=0.32; Table 2 ) and was associated with lower IL-6 levels in vaccinated individuals ( Table 3 ), indicating an immunomodulatory effect that extends beyond mere viral neutralization [24]. This study employed inactivated vaccines (Sinovac-CoronaVac, Sinopharm-BBIBP), which may differ in neuroprotective efficacy from mRNA or adenoviral vaccines due to comparatively weaker T-cell responses; nevertheless, it is likely that all vaccine types contribute to reducing viral load. Immunomodulatory Effects of Vaccination Vaccination has the potential to elicit a tolerogenic innate immune response, which can lead to a decrease in the production of interleukin-6 (IL-6), as demonstrated in pediatric populations following immunization [25]. This phenomenon is likely facilitated by the upregulation of regulatory T cells (Tregs) and the inhibition of pro-inflammatory signaling pathways, including the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway, both of which play crucial roles in neuroinflammation [26]. The effectiveness of vaccination appears to be particularly pronounced in infants, potentially reflecting their heightened immune plasticity that may stem from the enhanced reactivity of their developing immune systems to vaccine-derived antigens [27]. Notably, partial vaccination did not confer any protective effects, indicating the existence of a dose-dependent threshold, which could be linked to inadequate priming of adaptive immunity or insufficient antibody levels [28]. Neuroprotective Mechanisms The neuroprotective effects associated with vaccination may arise from a reduction in viral load within the CNS, potentially facilitated by robust cross-reactive T-cell responses. This mechanism has been increasingly recognized in studies pertaining to SARS-CoV-2 vaccines [29][30]. Furthermore, vaccination may mitigate the severity of neuroinflammation by modulating the cytokine environment, thus preventing excessive activation of glial cells and the subsequent release of pro-inflammatory cytokines [31]. These findings underscore the importance of prioritizing complete immunization schedules, especially within vulnerable pediatric demographics [32]. 4.3 Developmental Vulnerabilities: The Confluence of Age and Sex The significantly elevated risk of febrile seizures (FS) in male infants (1.8-fold increase; Table 2 ) coupled with the age-dependent gradient (41.2% in infants compared to 9.8% in adolescents; Table 1 ) accentuates developmental vulnerabilities [33]. Sex-Specific Susceptibility Surges in neonatal androgen levels may promote the expression of angiotensin-converting enzyme 2 (ACE2), thereby facilitating viral entry into the CNS while concurrently suppressing the activity of regulatory T cells [34]. This susceptibility appears to be further influenced by testosterone-driven immune modulation, which may intensify inflammatory signaling within the developing brain [35]. Moreover, the underdeveloped glymphatic system in infants may hinder the clearance of inflammatory substances, thereby prolonging neuroinflammation [36]. This inefficacy is likely worsened by the immature blood-brain barrier, characterized by its heightened permeability to cytokines and viral agents during early development [37]. This vulnerability may be exacerbated in males due to diminished expression of tight junction proteins such as claudin-5 and occludin, which, in concert with androgen-induced ACE2 upregulation, may increase susceptibility to FS [36][37]. Collectively, these factors contribute to the heightened incidence of FS observed in unvaccinated male infants ( Figure 3 ), emphasizing the importance of intervention during the critical first year of life [38]. 4.4 Variant-Specific Neurotropism: Structural and Functional Insights The prevalence of Omicron sublineages, accounting for 78.4% of FS cases, along with their correlation with elevated levels of IL-6 and D-dimer ( Table 3 ), indicates a shift in neurotropism compared to the Delta variant (adjusted odds ratio = 2.2; Table 2 ) [39]. Structural Alterations in Omicron Alterations in the spike protein of the Omicron variant, particularly mutations within the receptor-binding domain, may enhance the ability of the virus to penetrate the CNS, potentially through interactions with neuropilin-1 (NRP1), thus promoting viral transcytosis across endothelial barriers. In vitro analyses have demonstrated that mutations in Omicron’s spike protein improve binding to NRP1, facilitating CNS entry, while animal studies reveal increased levels of viral RNA within the brain and activation of microglia associated with the BA.5 variant, supporting its augmented neurotropism [40]. Additionally, the immune evasion capabilities of Omicron, driven by mutations in the N-terminal domain of the spike protein, may intensify cytokine release by delaying interferon responses, consequently resulting in a more pronounced neuroinflammatory reaction [41]. These observations reinforce the understanding that variant-specific characteristics play a significant role in shaping the dynamics of neuroinflammation, highlighting the necessity for further exploration into the consequences of such viral mutations on CNS health. In infants affected by the BA.5 variant, peak concentrations of biomarkers appear to be elevated, potentially attributable to the variant’s heightened affinity for neural tissues, as indicated by recent in vitro investigations [42]. Neuroinvasive potential is a crucial aspect to consider; however, the limited occurrence of Delta cases (less than 22%) necessitates a cautious approach to interpretation. The observed differences in neurotropism might reflect evolutionary changes that favor central nervous system (CNS) engagement, a notion bolstered by emerging genomic studies [43][44]. A comprehensive understanding of variant-specific neuropathogenesis is imperative for enhancing risk stratification [45]. 4.5 Threshold Optimization and Clinical Applicability The interleukin-6 (IL-6) threshold exceeding 10 pg/mL and the D-dimer threshold above 0.5 mg/L ( Figure 5 ) demonstrate an optimal balance between sensitivity and specificity for predicting the recurrence of febrile seizures ( Table 2 ) [46]. The enhanced discriminative ability of IL-6 (area under the curve [AUC] = 0.78; Figure 4 ) affirms its involvement in neuronal hyperexcitability, potentially mediated by interactions with NMDA receptors and subsequent excitotoxic effects [47]. Elevated D-dimer levels are consistent with coagulopathy mechanisms, where increased concentrations may signal microvascular thrombosis, which has been increasingly associated with neurological sequelae in viral infections [48][49]. These defined thresholds hold promise for informing therapeutic strategies, including the use of anti-inflammatory agents (e.g., tocilizumab) or anticoagulants (e.g., low-molecular-weight heparin), thereby offering an advantage over CRP-based protocols. Nevertheless, prospective validation across diverse patient populations is crucial [50][51]. Incorporating these biomarkers into clinical decision-making frameworks could enhance early intervention efforts, particularly in high-risk groups such as male infants, yet necessitates the establishment of standardized cutoff values through validation in larger cohorts [52]. 4.6 Limitations Limitations in this study, such as its single-center design and the regional predominance of the Omicron variant (78.4% as compared to an estimated national prevalence of 60% according to GISAID), may restrict the generalizability of the findings. This regional bias, along with potential variances in the timing of variant circulation (e.g., Omicron’s dominance in southeastern China compared to Delta in other regions) and population-specific factors (including genetic makeup or access to healthcare), could limit applicability to broader contexts. Furthermore, the lack of cerebrospinal fluid (CSF) data inhibits direct evaluation of neuroinflammation, thereby constraining insights into CNS-specific viral impacts. Future investigations may address this gap by integrating CSF analyses with neuroimaging techniques (e.g., MRI) or CNS-specific biomarkers (e.g., neurofilament light chain) to substantiate neuroinflammatory pathways. The limited sample size of XBB.1.5 cases restricts conclusions regarding subtype-specific characteristics, potentially obscuring distinct neuropathogenic traits. Subsequent research should delve into the variability of variant-specific biomarkers, the refinement of vaccine formulations aimed at neuroprotection, and the developmental dynamics of ACE2 and NRP1 expression. In addition, longitudinal studies are warranted to evaluate the long-term neurological outcomes of febrile seizures in vaccinated versus unvaccinated children, while multicenter collaborations could mitigate regional biases and bolster statistical rigor. 5. Conclusion This retrospective cohort investigation enhances our comprehension of febrile seizures (FS) associated with SARS-CoV-2 through three pivotal discoveries: Biomarker-Driven Risk Stratification: Elevated levels of IL-6 (>10 pg/mL) (adjusted odds ratio [aOR]=2.8, 95% confidence interval [CI]: 1.3–6.1) and D-dimer (>0.5 mg/L) (aOR=2.1, 95% CI: 1.2–3.7) were identified as significant predictors for the recurrence of FS. These findings provide practical thresholds for monitoring neuroinflammation in clinical settings. Vaccination as Neuroprotection: Complete vaccination was associated with a 68% reduction in the risk of FS (aOR=0.32), with the most pronounced effect observed in infants (odds ratio [OR] decreased from 3.5 to 1.8). This emphasizes the vaccine’s protective role that extends beyond merely controlling the viral infection and suggests an urgent need for accelerated vaccination protocols for infants. Developmental and Sex-Specific Susceptibility: Male infants displayed a 1.8-fold increased risk of FS ( P =0.016), which may be linked to androgen-driven upregulation of ACE2 and the immature integrity of the blood-brain barrier. This finding underscores the necessity for developing sex-specific preventive measures. Although the findings may be constrained by the single-center design and the predominance of the Omicron variant within the cohort (78.4%), they offer valuable mechanistic insights into the pathogenesis of FS. Future multicenter studies are essential for validating the identified biomarker thresholds, as well as conducting comparative analyses of various vaccine platforms (e.g., mRNA versus inactivated). Furthermore, the development of dynamic models that incorporate the evolution of variants is crucial for refining pediatric neuroprotection strategies during the ongoing COVID-19 pandemic. Declarations Ethics Approval and Consent to Participate This study was approved by the Institutional Review Board of the First Affiliated Hospital of Xiamen University (Approval [2024] Research Ethics Review No. 064). Clinical trial number: Not applicable. As a retrospective study using anonymized historical data, the requirement for informed consent was waived by the ethics committee. Consent for Publication Not applicable, as no identifiable individual data or images are included in this manuscript. Availability of Data and Materials The datasets generated and analyzed during this study are not publicly available due to patient privacy and institutional restrictions but are available from the corresponding author (Gangxi Lin, e-mail: [email protected] ) upon reasonable request, subject to ethical approval. Competing Interests The authors declare that they have no competing interests. Funding This study received no specific funding from any public, commercial, or not-for-profit sectors. All resources were provided by the Department of Pediatrics, The First Affiliated Hospital of Xiamen University. Authors’ Contributions MY :Conceptualization, data collection, statistical analysis, manuscript drafting; YZW :Study design, data curation, manuscript revision; JG :Data analysis, interpretation, figure preparation; CLY :Data collection, validation, literature review; GXL :Supervision, project administration, final manuscript approval; CJY :Methodology, critical revision, coordination. 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Pereira MAM, Barros ICA, Jacob ALV, Assis ML, Kanaan S, Kang HC. (2020). Laboratory findings in SARS-CoV-2 infections: State of the art. Revista da Associacao Medica Brasileira (1992), 66(8), 1152–1156. https://doi.org/10.1590/1806-9282.66.8.1152 Tables Table 1. Demographic and Clinical Characteristics of the Study Cohort Characteristic FS Group (n=102) Control Group (n=237) Statistical Test P-value Age, years Kruskal-Wallis <0.001 10 10 (9.8%) 40 (16.9%) Male sex 64 (62.7%) 150 (63.3%) χ²=0.07 0.739 Vaccination Status χ²=28.4 <0.001 Unvaccinated 91 (89.2%) 163 (68.8%) Partial 5 (4.9%) 25 (10.5%) Full 6 (5.9%) 49 (20.7%) Comorbidities 85 (83.3%) 198 (83.4%) χ²=0.03 0.857 Hospital stay, days 5 [3–7] 3 [2–5] Mann-Whitney U=7842 0.002 (median [IQR]) Notes : Data are presented as n (%) or median [IQR]. Significant P -values (<0.05) are in bold. ORs are adjusted in Table 2. Table 2. Multivariable Logistic Regression Analysis of FS Risk Factors Predictor aOR 95% CI P-value Variance Explained (Partial R²) Age <1 year 3.5 1.8–6.8 <0.001 0.18 Male sex 1.8 1.1–2.9 0.016 0.06 Unvaccinated 3.2 1.8–5.7 10 pg/mL 2.8 1.3–6.1 0.006 0.12 D-dimer >0.5 mg/L 2.1 1.2–3.7 0.016 0.08 Omicron infection 2.2 1.2–4.0 0.01 0.10 Model Summary Nagelkerke R²=0.42 Notes : Adjusted for age, sex, comorbidities, and therapies. CI: Confidence Interval. Model Fit : AIC=392.74, Nagelkerke R²=0.42,Hosmer-Lemeshow χ²=7.84, df=8, P=0.45. Table 3. Biomarker Profiles Stratified by Seizure Severity Biomarker Single Seizure (n=75) Recurrent Seizures (n=27) Median Difference (95% CI) P-value IL-6 (pg/mL) 8.2 [5.1–12.1] 15.6 [10.3–21.4] 7.4 (4.2–10.6) 0.001 D-dimer (mg/L) 0.9 [0.6–1.3] 1.3 [0.7–1.9] 0.4 (0.2–0.6) 0.02 CRP (mg/L) 8.5 [4.2–12.2] 9.3 [5.1–13.4] 0.8 (−0.5–2.1) 0.15 Notes : Differences calculated using the Hodges-Lehmann estimator. IQR: Interquartile Range. Additional Declarations No competing interests reported. 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medians and IQR presented in Table 3).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/4af16a6e46e171cc33bc95b5.png"},{"id":78733543,"identity":"6ec2519a-7b17-44c3-b639-8da7d36adca8","added_by":"auto","created_at":"2025-03-18 07:53:50","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":66621,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot illustrating adjusted odds ratios for FS risk factors (Omicron aOR=2.2; Table 2).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/d6260f599ef244132304f6f5.png"},{"id":78732246,"identity":"f76e5090-fc57-42d7-b314-c7c23221fa95","added_by":"auto","created_at":"2025-03-18 07:45:50","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73041,"visible":true,"origin":"","legend":"\u003cp\u003eHeatmap delineating FS incidence across age-sex subgroups (male infants: 41.2%; Table 1).\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/b3defcafe9328ce001b01fff.png"},{"id":78732259,"identity":"16150e08-22fc-4e3f-bd66-648e9a04e92b","added_by":"auto","created_at":"2025-03-18 07:45:50","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":273839,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic curves for IL-6 (AUC=0.78), D-dimer (AUC=0.71), and CRP (AUC=0.52).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/50f12790873f9b6df5e627d7.png"},{"id":78732275,"identity":"f0e7b6d6-03e1-43e1-adf8-f7ac54dfb2e1","added_by":"auto","created_at":"2025-03-18 07:45:50","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":149120,"visible":true,"origin":"","legend":"\u003cp\u003eThreshold effect analysis of IL-6 and D-dimer cutoffs (Youden index; Table 3).\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/db464083ad7cd4cebf4c0b39.png"},{"id":96105281,"identity":"873acfb5-6bc1-4b1b-941c-8c2d86467a5a","added_by":"auto","created_at":"2025-11-17 16:10:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2125283,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/7563fd53-d5cb-4c38-8f27-e2572db409f7.pdf"},{"id":78732243,"identity":"7b594393-aa03-41a1-a3a4-474afeba803b","added_by":"auto","created_at":"2025-03-18 07:45:50","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":15368,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFileAbbreviations.docx","url":"https://assets-eu.researchsquare.com/files/rs-6189452/v1/d8b1631093e2e7eb11d7060c.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Impact of SARS-CoV-2 Variants and Vaccination on Pediatric Febrile Seizures: A Retrospective Cohort Study","fulltext":[{"header":"Key Points","content":"\u003cul type=\"disc\"\u003e\n \u003cli\u003e\u003cstrong\u003eNeuroinflammatory Biomarkers in Pediatric Seizures:\u003c/strong\u003e IL-6 and D-dimer are identified as significant mediators of SARS-CoV-2-related FS, reflecting a thromboinflammatory mechanism that is distinct from systemic hyperinflammation.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eVaccination and Neurological Outcomes:\u003c/strong\u003e Vaccination reduces the risk of FS through immune modulation, thereby extending its protective effects to encompass neuroprotection.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eDevelopmental Susceptibility in Male Infants:\u003c/strong\u003e The increased susceptibility observed in male infants is associated with androgen-mediated pathways and the immature function of the blood-brain barrier during early stages of development.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eThe ongoing evolution of SARS-CoV-2 continues to challenge pediatric healthcare systems, as mounting evidence correlates the virus with neurological complications, particularly febrile seizures (FS). Characterized by generalized convulsions precipitated by fever (\u0026ge;\u0026thinsp;38\u0026deg;C) in the absence of central nervous system (CNS) infection or metabolic disturbances, FS is emerging as a significant concern among children infected with SARS-CoV-2, exhibiting an incidence rate 2.5 times higher than that observed with other viral infections (95% CI: 1.8\u0026ndash;3.4) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. During the predominance of the Omicron variant, hospitalization rates in the pediatric population reached 48.2 per 100,000 children under 18 years, with 26.4% necessitating intensive care, particularly among unvaccinated individuals and those with comorbidities such as obesity or chronic respiratory conditions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e][\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. These trends underscore the pressing need to comprehend FS within this demographic. Despite vaccination demonstrating 75\u0026ndash;78% efficacy in preventing severe outcomes, including multisystem inflammatory syndrome in children (MIS-C), coverage among infants (under 1 year) remains suboptimal, leaving this vulnerable group susceptible to neuroinflammatory complications due to the immature integrity of the blood-brain barrier and diminishing maternal antibody protection [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e][\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eWhile there is an increasing body of evidence regarding neurological complications in pediatric COVID-19 cases, the specific risks associated with different variants for FS, as well as the neuroprotective benefits of vaccination, remain inadequately understood, highlighting a critical research gap that this study aims to fill. The mechanistic underpinnings of SARS-CoV-2-induced FS likely involve inflammatory and coagulopathic pathways. Elevated levels of IL-6, a cytokine recognized for its capacity to disrupt the functionality of the blood-brain barrier, and D-dimer, a product of fibrin degradation indicative of coagulopathy, have been associated with negative neurological outcomes in pediatric populations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e][\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, the precise role of this biomarker in febrile seizures (FS) across different viral variants remains inadequately defined [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, there is a notable increased vulnerability among male infants to severe SARS-CoV-2 infections, potentially attributable to androgen-mediated upregulation of angiotensin-converting enzyme 2 (ACE2), which facilitates the entry of the virus [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Several critical inquiries remain unresolved:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eVariant-specific neurotropism\u003c/b\u003e: Do the Omicron sublineages (e.g., BA.5, XBB.1.5), characterized by enhanced immune evasion and modified tissue affinity, influence the risk of FS differently? [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e][\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eBiomarker thresholds\u003c/b\u003e: Are certain cutoff values for IL-6 or D-dimer effective for predicting the recurrence of FS or serve as targets for therapeutic intervention? [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eVaccination-mediated neuroprotection\u003c/b\u003e: In addition to reducing viral replication, does vaccination influence neuroinflammatory pathways in pediatric patients? [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eUnlike previous studies that primarily focused on systemic inflammation, the present data merge variant-specific genomic analysis with biomarkers pertinent to neurology to better understand the risk associated with FS. This investigation, derived from a single-center retrospective cohort, examines the interactions among SARS-CoV-2 variants, inflammatory biomarkers, vaccination status, and demographic characteristics in children with FS. The underlying hypotheses posit that inflammatory markers can predict the severity and recurrence of FS, that complete vaccination diminishes neuroinflammation, that male infants are at a heightened risk, and that Omicron sublineages are linked to a higher incidence of FS compared to ancestral strains.\u003c/p\u003e \u003cp\u003e \u003cb\u003eHypotheses\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eOmicron sublineages elevate the risk of FS in comparison to Delta due to their heightened neurotropism.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncreased levels of IL-6 and D-dimer serve as predictors of FS severity and recurrence through mechanisms related to neuroinflammation and coagulopathy.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eComplete vaccination modulates immune responses, thereby reducing neuroinflammation and providing neuroprotective benefits beyond merely controlling the virus.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Setting\u003c/h2\u003e \u003cp\u003eData for this retrospective cohort study were sourced from the First Affiliated Hospital of Xiamen University, a tertiary pediatric center in southeastern China that manages SARS-CoV-2 cases. The study period spanned from April 2020 to January 2023, encompassing waves associated with Delta and Omicron sublineages (BA.5/XBB). The cohort included 339 patients, determined based on a targeted FS incidence of 10% and an odds ratio of 2.0 (α\u0026thinsp;=\u0026thinsp;0.05, power\u0026thinsp;=\u0026thinsp;80%). The sample size was derived using a formula for proportion comparison in cohort studies: n = [Zα/2\u0026thinsp;+\u0026thinsp;Zβ]\u0026sup2; * [p1(1-p1)\u0026thinsp;+\u0026thinsp;p2(1-p2)] / (p1-p2)\u0026sup2;, where p1\u0026thinsp;=\u0026thinsp;0.10 (FS incidence in controls), p2\u0026thinsp;=\u0026thinsp;0.182 (FS incidence with OR\u0026thinsp;=\u0026thinsp;2.0), Zα/2\u0026thinsp;=\u0026thinsp;1.96 (α\u0026thinsp;=\u0026thinsp;0.05), and Zβ\u0026thinsp;=\u0026thinsp;0.84 (power\u0026thinsp;=\u0026thinsp;80%), resulting in a minimum sample size of approximately 316 patients, which was then adjusted to 339 for enhanced reliability.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study Population\u003c/h2\u003e \u003cp\u003e \u003cb\u003eInclusion Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePatients under the age of 18 with RT-PCR-confirmed SARS-CoV-2 infection.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eAvailability of thorough clinical records, including vaccination history and serial assessments of inflammatory biomarkers (IL-6, D-dimer, CRP) within 24 hours of admission, along with documentation of neurological assessments.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eExclusion Criteria\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003ePre-existing neurological conditions such as epilepsy or structural brain abnormalities.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNon-febrile seizures caused by conditions like hypoglycemia (glucose\u0026thinsp;\u0026lt;\u0026thinsp;3.9 mmol/L) or electrolyte imbalances.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncomplete records regarding biomarkers or vaccination status (more than 5% missing data).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Collection and Variables\u003c/h2\u003e \u003cp\u003e \u003cb\u003eVaccination Status\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eUnvaccinated\u003c/b\u003e: No doses of inactivated SARS-CoV-2 vaccines (e.g., Sinovac-CoronaVac, Sinopharm-BBIBP).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePartially vaccinated\u003c/b\u003e: One dose administered at least 14 days prior to infection.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eFully vaccinated\u003c/b\u003e: Two or more doses given with an interval of at least 21 days, defined as the completion of two doses, with the last administered at least 14 days before infection.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCovariates\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eAge categories: (\u0026lt;\u0026thinsp;1 year, 1\u0026ndash;4 years, 5\u0026ndash;10 years, \u0026gt;\u0026thinsp;10 years).\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eSex, comorbid disorders (e.g., asthma), and administration of antiviral or immunomodulatory treatments (e.g., remdesivir).\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eThe statistical evaluation was conducted using SPSS (version 27.0; IBM) and R (version 4.2.2). Continuous variables were represented as medians with corresponding interquartile ranges (IQR) and were analyzed using the Mann-Whitney U test for comparison. For categorical variables, χ\u0026sup2; tests or Fisher\u0026rsquo;s exact tests were employed. Multivariable logistic regression models, adjusted for age, sex, and comorbidities, provided adjusted odds ratios (aORs) for the risk of febrile seizures (FS), implementing Bonferroni correction (α\u0026thinsp;=\u0026thinsp;0.01) to account for multiple comparisons. The Bonferroni correction was applied by dividing the overall α (0.05) by the number of primary predictors (including five key variables: age, sex, vaccination status, IL-6, and D-dimer), thus establishing a significance threshold of 0.01 for each test. Sensitivity analyses incorporated restricted cubic splines to evaluate nonlinear relationships and utilized complete-case analysis for validation purposes. Missing data, which constituted less than 5%, were addressed through multiple imputation using the \u0026lsquo;mice\u0026rsquo; package in R (5 iterations), with no significant impact on outcomes (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The imputation process included age, sex, vaccination status, and biomarker levels as predictors in the MICE algorithm to ensure reliable estimates.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2.5 Ethical Approval\u003c/h3\u003e\n\u003cp\u003eThe study protocol ([2024] Research Ethics Review No. 064) received endorsement from the Institutional Review Board of the First Affiliated Hospital of Xiamen University. The requirement for informed consent was waived owing to the retrospective analysis of anonymized data, with all patient identifiers being removed prior to the analysis.\u003c/p\u003e"},{"header":"3. Results","content":"\u003ch3\u003e3.1 Cohort Stratification and Demographic Risk Landscape\u003c/h3\u003e\n\u003cp\u003eThe analyzed cohort consisted of 339 pediatric patients diagnosed with SARS-CoV-2 infection (FS group: n=102; control group: n=237), revealing significant age-related disparities (refer to \u003cem\u003eTable 1\u003c/em\u003e). Infants younger than 1 year represented 41.2% of FS cases, as opposed to 25.3% in the control group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001; aOR=3.5, 95% CI: 1.8–6.8; see \u003cem\u003eTable 2\u003c/em\u003e). Conversely, adolescents aged over 10 years demonstrated the lowest incidence of FS (9.8% versus 20.7%; \u003cem\u003eP\u003c/em\u003e=0.006). Within the infant demographic, male patients exhibited a 1.8-fold increased risk compared to females (aOR=1.8, 95% CI: 1.1–2.9; \u003cem\u003eP\u003c/em\u003e=0.016). Vaccination status markedly impacted outcomes: unvaccinated individuals comprised 89.2% of FS cases versus 68.8% in the control group (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.001), and full vaccination correlated with a 68% decrease in FS risk (aOR=0.32, 95% CI: 0.18–0.55; refer to \u003cem\u003eTable 2\u003c/em\u003e), with the most pronounced effect observed in infants (the odds ratio decreased from 3.5 to 1.8). The duration of hospital stays was significantly prolonged in the FS group (median: 5 days, IQR: 3–7) compared to controls (median: 3 days, IQR: 2–5; \u003cem\u003eP\u003c/em\u003e=0.002, Mann-Whitney U=7842), suggesting potentially greater clinical severity or a higher requirement for management.\u003c/p\u003e\n\u003ch3\u003e3.2 Neuroinflammatory Biomarkers: Precision Thresholds for Risk Stratification\u003c/h3\u003e\n\u003cp\u003ePatients experiencing FS displayed distinctive biomarker profiles (see \u003cem\u003eTable 3\u003c/em\u003e; \u003cem\u003eFigure 1\u003c/em\u003e). The concentrations of IL-6 were significantly elevated (\u003cem\u003eP\u003c/em\u003e=0.02), with levels surpassing 10 pg/mL correlating with a 3.1-fold increased risk of recurrence (OR=3.1, 95% CI: 1.8–5.4; aOR=2.8, see \u003cem\u003eTable 2\u003c/em\u003e). D-dimer levels were similarly elevated (\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01), with values exceeding 0.5 mg/L independently associated with recurrence (aOR=2.4, 95% CI: 1.3–4.5). Conversely, CRP levels did not reveal significant differences across groups (\u003cem\u003eP\u003c/em\u003e=0.15), highlighting its limited relevance in neurospecific contexts. The receiver operating characteristic (ROC) analysis substantiated IL-6 \u0026gt;10 pg/mL (AUC=0.78; sensitivity=82%; specificity=73%) and D-dimer \u0026gt;0.5 mg/L (AUC=0.71; sensitivity=75%; specificity=68%) as optimal diagnostic thresholds, surpassing CRP (AUC=0.52; refer to \u003cem\u003eFigure 4\u003c/em\u003e).\u003c/p\u003e\n\u003ch3\u003e3.3 Variant-Driven Pathogenesis: Omicron’s Neurotropic Shift\u003c/h3\u003e\n\u003cp\u003eAmong the FS cases, Omicron sublineages (BA.5: 65%; XBB.1.5: 35%) were predominant (78.4%), leading to a 2.2-fold heightened risk in infants when compared to the Delta variant (aOR=2.2, 95% CI: 1.2–4.0; \u003cem\u003eP\u003c/em\u003e=0.01; refer to \u003cem\u003eFigure 2\u003c/em\u003e), accompanied by increased levels of IL-6 and D-dimer. The underrepresentation of Delta variant cases, which accounted for less than 22%, may diminish its comparative efficacy.\u003c/p\u003e\n\u003ch3\u003e3.4 Age-Sex Interaction: Identification of Vulnerability Hotspots\u003c/h3\u003e\n\u003cp\u003eThe incidence of febrile seizures (FS) reached its highest point among male infants under one year of age, recorded at 41.2% (95% CI: 32.5–50.1), and exhibited a decreasing trend with advancing age. In contrast, the incidence reached its lowest point among female adolescents over the age of ten, at 8.2% (refer to \u003cem\u003eFigure 3\u003c/em\u003e), underscoring the age- and sex-dependent patterns of susceptibility.\u003c/p\u003e\n\u003ch3\u003e3.5 Threshold Optimization: Achieving an Equilibrium of Sensitivity and Specificity\u003c/h3\u003e\n\u003cp\u003eIL-6 levels surpassing 10 pg/mL (Youden index=0.55) exhibited enhanced diagnostic accuracy when compared to D-dimer levels exceeding 0.5 mg/L (Youden index=0.43; see \u003cem\u003eFigure 5\u003c/em\u003e), aligning with IL-6’s recognized function in neuronal hyperexcitability. The moderate effectiveness of D-dimer suggests the potential benefit of employing a composite biomarker strategy.\u003c/p\u003e\n\u003ch3\u003e3.6 Sensitivity Analyses and Model Robustness\u003c/h3\u003e\n\u003cp\u003eA consistent outcome was noted between complete-case and imputed analyses (ΔaOR\u0026lt;10%). Nonlinear spline models affirmed the existence of monotonic relationships between biomarkers and the occurrence of FS (\u003cem\u003eP_nonlinear\u003c/em\u003e\u0026gt;0.05), thereby reinforcing the credibility of the proposed thresholds.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003ch3\u003e4.1 Neuroinflammatory Cascades: Expanding Beyond Cytokine Storms\u003c/h3\u003e\n\u003cp\u003eThe increased levels of IL-6 and D-dimer in FS cases (refer to \u003cem\u003eTable 3\u003c/em\u003e) indicate the presence of a neuroinflammatory cascade that is separate from systemic hyperinflammation, a phenomenon that is gaining recognition in the context of SARS-CoV-2 neuropathology [14][15]. The prolonged duration of hospitalization for the FS group (\u003cem\u003eP\u003c/em\u003e=0.002; \u003cem\u003eTable 1\u003c/em\u003e) likely reflects a greater severity of the disease or the necessity for extended observation due to the risk of seizure recurrence, emphasizing the clinical challenges posed by FS in this demographic, and highlighting the potential role of IL-6 and D-dimer as indicators for resource allocation.\u003c/p\u003e\n\u003ch4\u003eIL-6 as a Mediator of Neuroinflammation\u003c/h4\u003e\n\u003cp\u003eIL-6 is a versatile cytokine that plays a pivotal role in the immune response to viral infections. Under inflammatory conditions, it is capable of crossing the blood-brain barrier (BBB), which leads to the activation of microglia and astrocytes, the central nervous system’s resident immune cells [16]. This activation instigates a cascade of pro-inflammatory cytokines, including TNF-α and IL-1β, which can exacerbate neuronal injury and provoke seizure activity [17]. The elevated IL-6 levels documented in this study (\u003cem\u003eTable 3\u003c/em\u003e) imply that IL-6 may enhance neuronal hyperexcitability through the mediation of N-methyl-D-aspartate (NMDA) receptors in the hippocampus [18]. This increased excitability may be driven by IL-6-induced activation of glial cells, particularly astrocytes, which release additional pro-inflammatory cytokines, further contributing to neuronal damage [19].\u003c/p\u003e\n\u003ch4\u003eD-dimer and Coagulopathy\u003c/h4\u003e\n\u003cp\u003eThe significant rise in D-dimer levels (\u003cem\u003eTable 3\u003c/em\u003e) suggests a hypercoagulable state, potentially induced by SARS-CoV-2-related endothelial dysfunction and complement activation [20]. Elevated D-dimer levels have been associated with cerebral microthrombosis and the disruption of the BBB, which facilitates viral entry and neuroinvasion [21]. This coagulopathic mechanism may play a role in the observed escalation of FS severity and recurrence, as microthrombi can induce localized ischemia and neuronal impairment [22]. The lack of significant differentiation in CRP levels (\u003cem\u003eP\u003c/em\u003e=0.15; \u003cem\u003eTable 3\u003c/em\u003e) highlights the restricted utility of CRP as a neurospecific marker, advocating for the implementation of CNS-focused biomarker panels in clinical practice [23].\u003c/p\u003e\n\u003ch3\u003e4.2 Vaccination and Neuroimmune Interactions: Elucidating Mechanisms\u003c/h3\u003e\n\u003cp\u003eFull vaccination was linked to a 68% reduction in the risk of FS (aOR=0.32; \u003cem\u003eTable 2\u003c/em\u003e) and was associated with lower IL-6 levels in vaccinated individuals (\u003cem\u003eTable 3\u003c/em\u003e), indicating an immunomodulatory effect that extends beyond mere viral neutralization [24]. This study employed inactivated vaccines (Sinovac-CoronaVac, Sinopharm-BBIBP), which may differ in neuroprotective efficacy from mRNA or adenoviral vaccines due to comparatively weaker T-cell responses; nevertheless, it is likely that all vaccine types contribute to reducing viral load.\u003c/p\u003e\n\u003ch4\u003eImmunomodulatory Effects of Vaccination\u003c/h4\u003e\n\u003cp\u003eVaccination has the potential to elicit a tolerogenic innate immune response, which can lead to a decrease in the production of interleukin-6 (IL-6), as demonstrated in pediatric populations following immunization [25]. This phenomenon is likely facilitated by the upregulation of regulatory T cells (Tregs) and the inhibition of pro-inflammatory signaling pathways, including the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling pathway, both of which play crucial roles in neuroinflammation [26]. The effectiveness of vaccination appears to be particularly pronounced in infants, potentially reflecting their heightened immune plasticity that may stem from the enhanced reactivity of their developing immune systems to vaccine-derived antigens [27]. Notably, partial vaccination did not confer any protective effects, indicating the existence of a dose-dependent threshold, which could be linked to inadequate priming of adaptive immunity or insufficient antibody levels [28].\u003c/p\u003e\n\u003ch4\u003eNeuroprotective Mechanisms\u003c/h4\u003e\n\u003cp\u003eThe neuroprotective effects associated with vaccination may arise from a reduction in viral load within the CNS, potentially facilitated by robust cross-reactive T-cell responses. This mechanism has been increasingly recognized in studies pertaining to SARS-CoV-2 vaccines [29][30]. Furthermore, vaccination may mitigate the severity of neuroinflammation by modulating the cytokine environment, thus preventing excessive activation of glial cells and the subsequent release of pro-inflammatory cytokines [31]. These findings underscore the importance of prioritizing complete immunization schedules, especially within vulnerable pediatric demographics [32].\u003c/p\u003e\n\u003ch3\u003e4.3 Developmental Vulnerabilities: The Confluence of Age and Sex\u003c/h3\u003e\n\u003cp\u003eThe significantly elevated risk of febrile seizures (FS) in male infants (1.8-fold increase; \u003cem\u003eTable 2\u003c/em\u003e) coupled with the age-dependent gradient (41.2% in infants compared to 9.8% in adolescents; \u003cem\u003eTable 1\u003c/em\u003e) accentuates developmental vulnerabilities [33].\u003c/p\u003e\n\u003ch4\u003eSex-Specific Susceptibility\u003c/h4\u003e\n\u003cp\u003eSurges in neonatal androgen levels may promote the expression of angiotensin-converting enzyme 2 (ACE2), thereby facilitating viral entry into the CNS while concurrently suppressing the activity of regulatory T cells [34]. This susceptibility appears to be further influenced by testosterone-driven immune modulation, which may intensify inflammatory signaling within the developing brain [35]. Moreover, the underdeveloped glymphatic system in infants may hinder the clearance of inflammatory substances, thereby prolonging neuroinflammation [36]. This inefficacy is likely worsened by the immature blood-brain barrier, characterized by its heightened permeability to cytokines and viral agents during early development [37]. This vulnerability may be exacerbated in males due to diminished expression of tight junction proteins such as claudin-5 and occludin, which, in concert with androgen-induced ACE2 upregulation, may increase susceptibility to FS [36][37]. Collectively, these factors contribute to the heightened incidence of FS observed in unvaccinated male infants (\u003cem\u003eFigure 3\u003c/em\u003e), emphasizing the importance of intervention during the critical first year of life [38].\u003c/p\u003e\n\u003ch3\u003e4.4 Variant-Specific Neurotropism: Structural and Functional Insights\u003c/h3\u003e\n\u003cp\u003eThe prevalence of Omicron sublineages, accounting for 78.4% of FS cases, along with their correlation with elevated levels of IL-6 and D-dimer (\u003cem\u003eTable 3\u003c/em\u003e), indicates a shift in neurotropism compared to the Delta variant (adjusted odds ratio = 2.2; \u003cem\u003eTable 2\u003c/em\u003e) [39].\u003c/p\u003e\n\u003ch4\u003eStructural Alterations in Omicron\u003c/h4\u003e\n\u003cp\u003eAlterations in the spike protein of the Omicron variant, particularly mutations within the receptor-binding domain, may enhance the ability of the virus to penetrate the CNS, potentially through interactions with neuropilin-1 (NRP1), thus promoting viral transcytosis across endothelial barriers. In vitro analyses have demonstrated that mutations in Omicron’s spike protein improve binding to NRP1, facilitating CNS entry, while animal studies reveal increased levels of viral RNA within the brain and activation of microglia associated with the BA.5 variant, supporting its augmented neurotropism [40]. Additionally, the immune evasion capabilities of Omicron, driven by mutations in the N-terminal domain of the spike protein, may intensify cytokine release by delaying interferon responses, consequently resulting in a more pronounced neuroinflammatory reaction [41]. These observations reinforce the understanding that variant-specific characteristics play a significant role in shaping the dynamics of neuroinflammation, highlighting the necessity for further exploration into the consequences of such viral mutations on CNS health.\u003c/p\u003e\n\u003cp\u003eIn infants affected by the BA.5 variant, peak concentrations of biomarkers appear to be elevated, potentially attributable to the variant’s heightened affinity for neural tissues, as indicated by recent in vitro investigations [42]. Neuroinvasive potential is a crucial aspect to consider; however, the limited occurrence of Delta cases (less than 22%) necessitates a cautious approach to interpretation. The observed differences in neurotropism might reflect evolutionary changes that favor central nervous system (CNS) engagement, a notion bolstered by emerging genomic studies [43][44]. A comprehensive understanding of variant-specific neuropathogenesis is imperative for enhancing risk stratification [45].\u003c/p\u003e\n\u003ch3\u003e4.5 Threshold Optimization and Clinical Applicability\u003c/h3\u003e\n\u003cp\u003eThe interleukin-6 (IL-6) threshold exceeding 10 pg/mL and the D-dimer threshold above 0.5 mg/L (\u003cem\u003eFigure 5\u003c/em\u003e) demonstrate an optimal balance between sensitivity and specificity for predicting the recurrence of febrile seizures (\u003cem\u003eTable 2\u003c/em\u003e) [46]. The enhanced discriminative ability of IL-6 (area under the curve [AUC] = 0.78; \u003cem\u003eFigure 4\u003c/em\u003e) affirms its involvement in neuronal hyperexcitability, potentially mediated by interactions with NMDA receptors and subsequent excitotoxic effects [47]. Elevated D-dimer levels are consistent with coagulopathy mechanisms, where increased concentrations may signal microvascular thrombosis, which has been increasingly associated with neurological sequelae in viral infections [48][49]. These defined thresholds hold promise for informing therapeutic strategies, including the use of anti-inflammatory agents (e.g., tocilizumab) or anticoagulants (e.g., low-molecular-weight heparin), thereby offering an advantage over CRP-based protocols. Nevertheless, prospective validation across diverse patient populations is crucial [50][51]. Incorporating these biomarkers into clinical decision-making frameworks could enhance early intervention efforts, particularly in high-risk groups such as male infants, yet necessitates the establishment of standardized cutoff values through validation in larger cohorts [52].\u003c/p\u003e\n\u003ch3\u003e4.6 Limitations\u003c/h3\u003e\n\u003cp\u003eLimitations in this study, such as its single-center design and the regional predominance of the Omicron variant (78.4% as compared to an estimated national prevalence of 60% according to GISAID), may restrict the generalizability of the findings. This regional bias, along with potential variances in the timing of variant circulation (e.g., Omicron’s dominance in southeastern China compared to Delta in other regions) and population-specific factors (including genetic makeup or access to healthcare), could limit applicability to broader contexts. Furthermore, the lack of cerebrospinal fluid (CSF) data inhibits direct evaluation of neuroinflammation, thereby constraining insights into CNS-specific viral impacts. Future investigations may address this gap by integrating CSF analyses with neuroimaging techniques (e.g., MRI) or CNS-specific biomarkers (e.g., neurofilament light chain) to substantiate neuroinflammatory pathways. The limited sample size of XBB.1.5 cases restricts conclusions regarding subtype-specific characteristics, potentially obscuring distinct neuropathogenic traits. Subsequent research should delve into the variability of variant-specific biomarkers, the refinement of vaccine formulations aimed at neuroprotection, and the developmental dynamics of ACE2 and NRP1 expression. In addition, longitudinal studies are warranted to evaluate the long-term neurological outcomes of febrile seizures in vaccinated versus unvaccinated children, while multicenter collaborations could mitigate regional biases and bolster statistical rigor.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis retrospective cohort investigation enhances our comprehension of febrile seizures (FS) associated with SARS-CoV-2 through three pivotal discoveries:\u003c/p\u003e\n\u003col start=\"1\" type=\"1\"\u003e\n \u003cli\u003e\u003cstrong\u003eBiomarker-Driven Risk Stratification:\u003c/strong\u003e Elevated levels of IL-6 (\u0026gt;10 pg/mL) (adjusted odds ratio [aOR]=2.8, 95% confidence interval [CI]: 1.3–6.1) and D-dimer (\u0026gt;0.5 mg/L) (aOR=2.1, 95% CI: 1.2–3.7) were identified as significant predictors for the recurrence of FS. These findings provide practical thresholds for monitoring neuroinflammation in clinical settings.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eVaccination as Neuroprotection:\u003c/strong\u003e Complete vaccination was associated with a 68% reduction in the risk of FS (aOR=0.32), with the most pronounced effect observed in infants (odds ratio [OR] decreased from 3.5 to 1.8). This emphasizes the vaccine’s protective role that extends beyond merely controlling the viral infection and suggests an urgent need for accelerated vaccination protocols for infants.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eDevelopmental and Sex-Specific Susceptibility:\u003c/strong\u003e Male infants displayed a 1.8-fold increased risk of FS (\u003cem\u003eP\u003c/em\u003e=0.016), which may be linked to androgen-driven upregulation of ACE2 and the immature integrity of the blood-brain barrier. This finding underscores the necessity for developing sex-specific preventive measures.\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eAlthough the findings may be constrained by the single-center design and the predominance of the Omicron variant within the cohort (78.4%), they offer valuable mechanistic insights into the pathogenesis of FS. Future multicenter studies are essential for validating the identified biomarker thresholds, as well as conducting comparative analyses of various vaccine platforms (e.g., mRNA versus inactivated). Furthermore, the development of dynamic models that incorporate the evolution of variants is crucial for refining pediatric neuroprotection strategies during the ongoing COVID-19 pandemic.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch3\u003eEthics Approval and Consent to Participate\u003c/h3\u003e\n\u003cp\u003eThis study was approved by the Institutional Review Board of the First Affiliated Hospital of Xiamen University (Approval [2024] Research Ethics Review No. 064).\u0026nbsp;\u003cstrong\u003eClinical trial number:\u003c/strong\u003e Not applicable.\u003cbr\u003e\u0026nbsp;As a retrospective study using anonymized historical data, the requirement for informed consent was waived by the ethics committee.\u003c/p\u003e\n\u003ch3\u003eConsent for Publication\u003c/h3\u003e\n\u003cp\u003eNot applicable, as no identifiable individual data or images are included in this manuscript.\u003c/p\u003e\n\u003ch3\u003eAvailability of Data and Materials\u003c/h3\u003e\n\u003cp\u003eThe datasets generated and analyzed during this study are not publicly available due to patient privacy and institutional restrictions but are available from the corresponding author (Gangxi Lin, e-mail:\u0026nbsp;\u003cu\[email protected]\u003c/u\u003e) upon reasonable request, subject to ethical approval.\u003c/p\u003e\n\u003ch3\u003eCompeting Interests\u003c/h3\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch3\u003eFunding\u003c/h3\u003e\n\u003cp\u003eThis study received no specific funding from any public, commercial, or not-for-profit sectors. All resources were provided by the Department of Pediatrics, The First Affiliated Hospital of Xiamen University.\u003c/p\u003e\n\u003ch3\u003eAuthors\u0026rsquo; Contributions\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eMY\u003c/strong\u003e:Conceptualization, data collection, statistical analysis, manuscript drafting;\u003cstrong\u003eYZW\u003c/strong\u003e:Study design, data curation, manuscript revision;\u003cstrong\u003eJG\u003c/strong\u003e:Data analysis, interpretation, figure preparation;\u003cstrong\u003eCLY\u003c/strong\u003e:Data collection, validation, literature review;\u003cstrong\u003eGXL\u003c/strong\u003e:Supervision, project administration, final manuscript approval;\u003cstrong\u003eCJY\u003c/strong\u003e:Methodology, critical revision, coordination.\u003cbr\u003e\u0026nbsp;All authors read and approved the final manuscript.\u003c/p\u003e\n\u003ch3\u003eAcknowledgments\u003c/h3\u003e\n\u003cp\u003eWe thank the staff of the First Affiliated Hospital of Xiamen University for their support in data collection and patient care. 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J family Med Prim care. 2024;13(4):1421\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/jfmpc.jfmpc_1595_23\u003c/span\u003e\u003cspan address=\"10.4103/jfmpc.jfmpc_1595_23\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHulkoti VS, Acharya S, Kumar S, Talwar D, Khanna S, Annadatha A, Madaan S, Verma V, Sagar VVSS. Association of serum ferritin with COVID-19 in a cross-sectional study of 200 intensive care unit patients in a rural hospital: Is ferritin the forgotten biomarker of mortality in severe COVID-19? J family Med Prim care. 2022;11(5):2045\u0026ndash;50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/jfmpc.jfmpc_1921_21\u003c/span\u003e\u003cspan address=\"10.4103/jfmpc.jfmpc_1921_21\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMyhre PL, Prebensen C, Strand H, R\u0026oslash;ysland R, Jonassen CM, Rangberg A, S\u0026oslash;rensen V, S\u0026oslash;vik S, R\u0026oslash;sj\u0026oslash; H, Svensson M, Berdal JE, Omland T. Growth Differentiation Factor 15 Provides Prognostic Information Superior to Established Cardiovascular and Inflammatory Biomarkers in Unselected Patients Hospitalized With COVID-19. Circulation. 2020;142(22):2128\u0026ndash;37. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1161/CIRCULATIONAHA.120.050360\u003c/span\u003e\u003cspan address=\"10.1161/CIRCULATIONAHA.120.050360\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePereira MAM, Barros ICA, Jacob ALV, Assis ML, Kanaan S, Kang HC. (2020). Laboratory findings in SARS-CoV-2 infections: State of the art. Revista da Associacao Medica Brasileira (1992), 66(8), 1152\u0026ndash;1156. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/1806-9282.66.8.1152\u003c/span\u003e\u003cspan address=\"10.1590/1806-9282.66.8.1152\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1. Demographic and Clinical Characteristics of the Study Cohort\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eFS Group (n=102)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eControl Group (n=237)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistical Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eKruskal-Wallis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e42 (41.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60 (25.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1–4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e93 (39.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5–10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (10.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44 (18.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e40 (16.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale sex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64 (62.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e150 (63.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eχ²=0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.739\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eVaccination Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eχ²=28.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnvaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e91 (89.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e163 (68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePartial\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e25 (10.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eFull\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (5.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49 (20.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e198 (83.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eχ²=0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.857\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHospital stay, days\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 [3–7]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 [2–5]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMann-Whitney U=7842\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cem\u003e(median [IQR])\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: Data are presented as n (%) or median [IQR]. Significant \u003cem\u003eP\u003c/em\u003e-values (\u0026lt;0.05) are in bold. ORs are adjusted in Table 2.\u003c/p\u003e\n\u003cp\u003eTable 2. Multivariable Logistic Regression Analysis of FS Risk Factors\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003ePredictor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eaOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariance Explained (Partial R²)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge \u0026lt;1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.8–6.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1–2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnvaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.8–5.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIL-6 \u0026gt;10 pg/mL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.3–6.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eD-dimer \u0026gt;0.5 mg/L\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.2–3.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOmicron infection\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.2–4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel Summary\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNagelkerke R²=0.42\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: Adjusted for age, sex, comorbidities, and therapies. CI: Confidence Interval.\u003cbr\u003e\u003cstrong\u003eModel Fit\u003c/strong\u003e: AIC=392.74, Nagelkerke R²=0.42,Hosmer-Lemeshow χ²=7.84, df=8, P=0.45.\u003c/p\u003e\n\u003cp\u003eTable 3. Biomarker Profiles Stratified by Seizure Severity\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiomarker\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eSingle Seizure (n=75)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eRecurrent Seizures (n=27)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian Difference (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eIL-6 (pg/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.2 [5.1–12.1]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15.6 [10.3–21.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.4 (4.2–10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eD-dimer (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9 [0.6–1.3]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.3 [0.7–1.9]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.4 (0.2–0.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.5 [4.2–12.2]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9.3 [5.1–13.4]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.8 (−0.5–2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eNotes\u003c/strong\u003e: Differences calculated using the Hodges-Lehmann estimator. IQR: Interquartile Range.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Febrile seizures, SARS-CoV-2 variants (COVID-19), Neuroinflammation, Pediatric vaccinaion, Biomarker thresholds, Sex disparities","lastPublishedDoi":"10.21203/rs.3.rs-6189452/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6189452/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eObjective\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study aimed to investigate the associations between SARS-CoV-2 variants, neuroinflammatory markers, vaccination history, and demographic characteristics in relation to the occurrence of febrile seizures (FS) in pediatric patients at a single tertiary medical center.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRetrospective cohort data were collected from a pediatric tertiary care institution between April 2020 and January 2023, encompassing 339 patients with PCR-confirmed SARS-CoV-2 infections. The cohort was separated into FS (n=102) and control (n=237) groups. A multivariable logistic regression analysis was employed to evaluate the impact of viral variants (Delta and Omicron sublineages), inflammatory markers (IL-6, D-dimer, CRP), vaccination status (unvaccinated, partially vaccinated, fully vaccinated), and demographic variables, while controlling for potential confounders.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe incidence of FS among infants under one year of age was found to be 41.2%, in contrast to 17.7% in older children (OR=3.2, 95% CI: 1.8–5.7; \u003cem\u003eP\u003c/em\u003e\u0026lt;0.001). Elevated levels of IL-6 exceeding 10 pg/mL and D-dimer levels surpassing 0.5 mg/L were independently associated with increased FS severity (adjusted OR [aOR]=2.8 and 2.1, respectively), as well as a 3.1-fold increase in the risk of recurrence. Full vaccination was linked to a 68% reduction in FS risk (aOR=0.32, 95% CI: 0.18–0.55), particularly benefiting infants. Additionally, male infants exhibited a 1.8-fold increased vulnerability (\u003cem\u003eP\u003c/em\u003e=0.016). Omicron sublineages (BA.5/XBB), which accounted for 78.4% of FS cases, correlated with heightened biomarker levels.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings suggest that IL-6 and D-dimer serve as valuable indicators for assessing the risk of FS in children infected with SARS-CoV-2. The protective effect of vaccination on neural tissues, in addition to its role in reducing viral transmission, is evident, highlighting the increased susceptibility in male infants.\u003c/p\u003e","manuscriptTitle":"Impact of SARS-CoV-2 Variants and Vaccination on Pediatric Febrile Seizures: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-18 07:45:45","doi":"10.21203/rs.3.rs-6189452/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-05-29T22:34:04+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-29T21:02:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-29T17:54:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-21T06:41:08+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-19T22:43:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"95124658657070599014253984595082136228","date":"2025-05-19T19:49:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"111534680317172434574458190743722295475","date":"2025-05-19T11:00:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107805144779358740311033351523825108021","date":"2025-05-19T06:57:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-18T20:03:39+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-18T15:38:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"83512863129168796533321258260000500977","date":"2025-05-17T01:12:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"300824129118920841693055036350993993030","date":"2025-05-16T16:12:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"9884331678230730393234028490028787740","date":"2025-05-15T23:36:34+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"238958089190992884033708225606624902283","date":"2025-05-14T15:25:09+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-03-16T14:52:29+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-03-13T08:17:58+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-03-13T02:16:55+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-13T02:15:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-03-09T15:18:53+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f1bebcfe-5385-4c20-81a9-0820115cc7d6","owner":[],"postedDate":"March 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-17T16:06:19+00:00","versionOfRecord":{"articleIdentity":"rs-6189452","link":"https://doi.org/10.1186/s12887-025-06095-5","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2025-11-13 15:58:21","publishedOnDateReadable":"November 13th, 2025"},"versionCreatedAt":"2025-03-18 07:45:45","video":"","vorDoi":"10.1186/s12887-025-06095-5","vorDoiUrl":"https://doi.org/10.1186/s12887-025-06095-5","workflowStages":[]},"version":"v1","identity":"rs-6189452","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6189452","identity":"rs-6189452","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}