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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Neurol.</journal-id>
<journal-title-group>
<journal-title>Frontiers in Neurology</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Neurol.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1664-2295</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fneur.2026.1759537</article-id>
<article-version article-version-type="Version of Record" vocab="NISO-RP-8-2008"/>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Original Research</subject>
</subj-group>
</article-categories>
<title-group>
<article-title>U-shaped association between serum uric acid at admission and post-stroke epilepsy in patients with ischemic stroke: a cohort study</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Liu</surname>
<given-names>Dayuan</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn0002"><sup>&#x2020;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2901303"/>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Peng</surname>
<given-names>Hao</given-names>
</name>
<xref ref-type="aff" rid="aff3"><sup>3</sup></xref>
<xref ref-type="aff" rid="aff4"><sup>4</sup></xref>
<xref ref-type="author-notes" rid="fn0002"><sup>&#x2020;</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author" equal-contrib="yes">
<name>
<surname>Zhai</surname>
<given-names>Yihao</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="author-notes" rid="fn0002"><sup>&#x2020;</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Wang</surname>
<given-names>Muyao</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3210136"/>
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<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="investigation" vocab-term-identifier="https://credit.niso.org/contributor-roles/investigation/">Investigation</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Jiang</surname>
<given-names>Hongli</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Data curation" vocab-term-identifier="https://credit.niso.org/contributor-roles/data-curation/">Data curation</role>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Su</surname>
<given-names>Baoshou</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/3326031"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhong</surname>
<given-names>Yunxiang</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="methodology" vocab-term-identifier="https://credit.niso.org/contributor-roles/methodology/">Methodology</role>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Deng</surname>
<given-names>Guolong</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/2901186"/>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; original draft" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-original-draft/">Writing &#x2013; original draft</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Ning</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Feng</surname>
<given-names>Jigao</given-names>
</name>
<xref ref-type="aff" rid="aff1"><sup>1</sup></xref>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<uri xlink:href="https://loop.frontiersin.org/people/1944619"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Zhang</surname>
<given-names>Caicai</given-names>
</name>
<xref ref-type="aff" rid="aff2"><sup>2</sup></xref>
<xref ref-type="corresp" rid="c001"><sup>&#x002A;</sup></xref>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="validation" vocab-term-identifier="https://credit.niso.org/contributor-roles/validation/">Validation</role>
<role vocab="credit" vocab-identifier="https://credit.niso.org/" vocab-term="Writing &#x2013; review &#x0026; editing" vocab-term-identifier="https://credit.niso.org/contributor-roles/writing-review-editing/">Writing &#x2013; review &#x0026; editing</role>
</contrib>
</contrib-group>
<aff id="aff1"><label>1</label><institution>Department of Neurosurgery, The Second Affiliated Hospital of Hainan Medical University</institution>, <city>Haikou</city>, <state>Hainan</state>, <country country="cn">China</country></aff>
<aff id="aff2"><label>2</label><institution>Key Laboratory of Tropical Translational Medicine of Ministry of Education &#x0026; Key Laboratory of Brain Science Research Transformation in Tropical Environment of Hainan Province, School of Basic Medicine and Life Sciences, Hainan Medical University</institution>, <city>Haikou</city>, <state>Hainan</state>, <country country="cn">China</country></aff>
<aff id="aff3"><label>3</label><institution>Department of Neurosurgery, The Second People&#x2019;s Hospital of Hainan Province</institution>, <city>Wuzhishan</city>,  <state>Hainan</state>, <country country="cn">China</country></aff>
<aff id="aff4"><label>4</label><institution>Department of Neurosurgery, Hainan Affiliated Hospital of Hainan Medical University</institution>, <city>Haikou</city>, <state>Hainan</state>, <country country="cn">China</country></aff>
<author-notes>
<corresp id="c001"><label>&#x002A;</label>Correspondence: Ning Li, <email xlink:href="mailto:lining1102@muhn.edu.cn">lining1102@muhn.edu.cn</email>; Jigao Feng, <email xlink:href="mailto:fengjigao@muhn.edu.cn">fengjigao@muhn.edu.cn</email>; Caicai Zhang, <email xlink:href="mailto:hy0206101@muhn.edu.cn">hy0206101@muhn.edu.cn</email></corresp>
<fn fn-type="equal" id="fn0002">
<label>&#x2020;</label>
<p>These authors have contributed equally to this work</p>
</fn>
</author-notes>
<pub-date publication-format="electronic" date-type="pub" iso-8601-date="2026-02-19">
<day>19</day>
<month>02</month>
<year>2026</year>
</pub-date>
<pub-date publication-format="electronic" date-type="collection">
<year>2026</year>
</pub-date>
<volume>17</volume>
<elocation-id>1759537</elocation-id>
<history>
<date date-type="received">
<day>03</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>28</day>
<month>12</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>21</day>
<month>01</month>
<year>2026</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#x00A9; 2026 Liu, Peng, Zhai, Wang, Jiang, Su, Zhong, Deng, Li, Feng and Zhang.</copyright-statement>
<copyright-year>2026</copyright-year>
<copyright-holder>Liu, Peng, Zhai, Wang, Jiang, Su, Zhong, Deng, Li, Feng and Zhang</copyright-holder>
<license>
<ali:license_ref start_date="2026-02-19">https://creativecommons.org/licenses/by/4.0/</ali:license_ref>
<license-p>This is an open-access article distributed under the terms of the <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution License (CC BY)</ext-link>. The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</license-p>
</license>
</permissions>
<abstract>
<sec>
<title>Background</title>
<p>The relationship between serum uric acid (SUA) and post-stroke epilepsy (PSE) remains uncertain. We investigated the association between serum uric acid at admission and PSE after acute ischemic stroke.</p>
</sec>
<sec>
<title>Methods</title>
<p>A retrospective cohort study was conducted on 21,459 ischemic stroke patients. Serum uric acid at admission was measured as part of routine laboratory testing and analyzed in quartiles (Q1-Q4). Logistic regression models with restricted cubic splines (RCS) were used to investigate the potential nonlinearity of the association between serum uric acid (SUA) levels and the risk of post-stroke epilepsy (PSE), with adjustments for demographic, clinical, and laboratory variables. Propensity score matching (PSM) was additionally employed to address potential confounding.</p>
</sec>
<sec>
<title>Results</title>
<p>A U-shaped association was observed. Compared with the mid-range (Q2&#x2013;Q3: ~305.3&#x2013;373.9&#x202F;&#x03BC;mol/L), both low (Q1) and high (Q4) SUA were associated with higher PSE risk (adjusted OR 2.32, 95% CI 1.79&#x2013;2.99; and 1.60, 95% CI 1.26&#x2013;2.02). RCS identified an inflection point around 335&#x202F;&#x03BC;mol/L: below this level, higher SUA related to lower PSE risk, whereas above it, higher SUA related to higher risk. Findings were robust in propensity score&#x2013;based and sensitivity analyses.</p>
</sec>
<sec>
<title>Conclusion</title>
<p>SUA shows a U-shaped association with PSE after ischemic stroke. SUA levels within an intermediate range were associated with a lower risk of PSE. This observation is hypothesis-generating and requires confirmation in prospective studies to evaluate potential causal relationships.</p>
</sec>
</abstract>
<kwd-group>
<kwd>inflammation</kwd>
<kwd>ischemic stroke</kwd>
<kwd>oxidative stress</kwd>
<kwd>post-stroke epilepsy</kwd>
<kwd>serum uric acid</kwd>
<kwd>U-shaped association</kwd>
</kwd-group>
<funding-group>
<funding-statement>The author(s) declared that financial support was not received for this work and/or its publication.</funding-statement>
</funding-group>
<counts>
<fig-count count="1"/>
<table-count count="4"/>
<equation-count count="0"/>
<ref-count count="41"/>
<page-count count="9"/>
<word-count count="6567"/>
</counts>
<custom-meta-group>
<custom-meta>
<meta-name>section-at-acceptance</meta-name>
<meta-value>Epilepsy</meta-value>
</custom-meta>
</custom-meta-group>
</article-meta>
</front>
<body>
<sec sec-type="intro" id="sec1">
<title>Introduction</title>
<p>Stroke ranks as the second-leading cause of mortality worldwide, frequently accompanied by severe complications during both its acute and recovery stages (<xref ref-type="bibr" rid="ref1">1</xref>). Post-stroke epilepsy (PSE) affects approximately 5&#x2013;9% of patients after stroke (<xref ref-type="bibr" rid="ref2">2</xref>). It is widely recognized that PSE contributes to extended hospitalization durations and escalates mortality rates in cerebrovascular disease patients. Ischemic stroke has been identified as the predominant cause of PSE, accounting for 70&#x2013;85% of cases associated with stroke-related epilepsy (<xref ref-type="bibr" rid="ref3">3</xref>). The reported frequency of post-stroke ictal and interictal epileptiform activity after stroke is 7 and 8%, respectively (<xref ref-type="bibr" rid="ref4">4</xref>). Addressing the profound influence of PSE on patient prognosis necessitates a thorough investigation of its risk factors, which is vital for enabling precise risk prediction and for generating hypotheses that may inform future preventive and therapeutic research (<xref ref-type="bibr" rid="ref5">5</xref>).</p>
<p>Recent studies have highlighted serum uric acid (SUA) as a biomarker of growing importance in stroke and PSE research (<xref ref-type="bibr" rid="ref5">5</xref>, <xref ref-type="bibr" rid="ref6">6</xref>). SUA, a metabolic byproduct of purine degradation, exhibits contrasting roles within the nervous system. While moderate levels exert antioxidant properties that counter neuronal damage caused by oxidative stress, elevated SUA concentrations may act as pro-oxidants, intensifying inflammatory responses and amplifying neural excitability (<xref ref-type="bibr" rid="ref7">7</xref>). Previous research has revealed a &#x201C;U-shaped&#x201D; dose&#x2013;response correlation between SUA levels and ischemic stroke risk (<xref ref-type="bibr" rid="ref8">8</xref>), emphasizing that both exceedingly high and low SUA levels markedly elevate stroke risk (<xref ref-type="bibr" rid="ref9">9</xref>, <xref ref-type="bibr" rid="ref10">10</xref>). This dualistic behavior suggests SUA&#x2019;s complex involvement in stroke pathophysiology, wherein it provides protective effects at optimal levels but contributes to adverse outcomes at extremes (<xref ref-type="bibr" rid="ref11">11</xref>). Nonetheless, the association between SUA levels and epilepsy risk remains contentious. Certain studies propose a &#x201C;L-shaped&#x201D; relationship, arguing that lower SUA levels heighten epilepsy risk, whereas higher levels seemingly plateau without further impact (<xref ref-type="bibr" rid="ref12">12</xref>). Supporters of this view underscore the significance of SUA&#x2019;s antioxidant activity, asserting that insufficient levels heighten vulnerability to oxidative damage, thereby fostering epileptogenesis (<xref ref-type="bibr" rid="ref13">13</xref>). Contrarily, alternative findings link elevated SUA to an increased likelihood of late-onset seizures post-ischemic stroke, implicating oxidative stress and inflammatory cascades as underlying mechanisms (<xref ref-type="bibr" rid="ref14">14</xref>, <xref ref-type="bibr" rid="ref15">15</xref>). These divergent results imply that SUA&#x2019;s role in PSE may vary depending on disease stage and individual patient conditions.</p>
<p>In the specific context of ischemic stroke, the interaction between SUA and PSE emerges as particularly intricate and remains insufficiently understood. For instance, low SUA levels may undermine antioxidant defenses, whereas excessive levels could aggravate inflammation and neuronal injury, collectively elevating epilepsy risks (<xref ref-type="bibr" rid="ref16">16</xref>). This dual role accentuates the need for elucidating SUA&#x2019;s biological mechanisms in PSE. Accordingly, the present study endeavors to systematically explore the association between SUA levels and PSE in ischemic stroke patients. By analyzing these relationships comprehensively, this study aims to provide foundational evidence supporting the prediction and clinical prevention of PSE.</p>
</sec>
<sec sec-type="materials|methods" id="sec2">
<title>Materials and methods</title>
<sec id="sec3">
<title>Data source</title>
<p>The dataset for this analysis was sourced from the Dryad Digital Repository.<xref ref-type="fn" rid="fn0001"><sup>1</sup></xref> Initially, this dataset was part of a study focusing on predictive models for post-stroke epilepsy in patients with acute ischemic stroke (<xref ref-type="bibr" rid="ref17">17</xref>). Its availability for public use was granted by the original authors, enabling secondary analysis while adhering to ethical research standards, including compliance with STROBE guidelines and Dryad&#x2019;s Terms of Service.</p>
</sec>
<sec id="sec4">
<title>Study population</title>
<p>This investigation included a total of 21,459 patients diagnosed with acute ischemic stroke who were admitted to Chongqing Emergency Center over a five-year period (June 2017&#x2013;June 2022). Patients aged between 18 and 90&#x202F;years were eligible for inclusion, provided they had no prior history of stroke, epilepsy, or related conditions, and were not deceased within 72&#x202F;h or 3&#x202F;months post-stroke. Individuals lost to follow-up were likewise excluded. Data collection encompassed imaging studies (CT/MRI, CTA/MRA/DSA) and laboratory assessments, including blood lipid profiles, liver and kidney function markers, coagulation indicators, and myocardial enzyme levels. Secondary analyses utilized de-identified data from the Dryad Digital Repository (<xref ref-type="bibr" rid="ref17">17</xref>).</p>
</sec>
<sec id="sec5">
<title>Baseline serum uric acid</title>
<p>Serum uric acid at admission was measured as part of routine laboratory testing and analyzed as quartiles (Q1&#x2013;Q4).</p>
</sec>
<sec id="sec6">
<title>Covariates</title>
<p>Key covariates for regression analyses were selected based on clinical relevance, statistical significance in preliminary testing, and alignment with study objectives. These included demographic data (age, sex, and NIHSS scores at admission), comorbidities (e.g., hypertension, diabetes, atrial fibrillation, coronary disease, uremia, deep vein thrombosis, fatty liver, cerebral herniation, hydrocephalus, hypoproteinemia, and hyperlipidemia), vascular involvement (stenosis or occlusion of major cerebral arteries verified via CTA/MRA/DSA), and laboratory parameters such as red blood cell count, platelet count, renal function, low-density lipoprotein cholesterol (LDL-C) levels, and fibrinogen concentration. This systematic approach ensured a balance between clinical utility and statistical robustness, minimizing risks of overfitting.</p>
</sec>
<sec id="sec7">
<title>Outcome</title>
<p>The primary outcome was PSE within 1&#x202F;year after acute ischemic stroke, defined as the pre-labeled PSE variable provided in the Dryad dataset (see text footnote 1) derived from the published predictive-model study.</p>
</sec>
<sec id="sec8">
<title>Statistical analysis</title>
<p>Descriptive analyses were performed for all patient data. Continuous variables were expressed as mean &#x00B1; standard deviation for normally distributed data or median with interquartile range for skewed data. Categorical variables were reported as counts and percentages. Comparisons between categorical variables were assessed using chi-square or Fisher&#x2019;s exact tests, whereas continuous variables were evaluated through one-way ANOVA or Kruskal-Wallis tests, depending on their distributions. Logistic regression models were employed to examine the association between SUA levels and PSE risk, with odds ratios (ORs) and 95% confidence intervals (CIs) reported for unadjusted (Model 1), age- and sex-adjusted (Model 2), and fully adjusted analyses (Model 3). We further performed sex-stratified analyses and tested effect modification by including a SUA quartiles &#x00D7; sex interaction term. The interaction was evaluated using a likelihood ratio test comparing models with and without the interaction term. We assessed collinearity using the variance inflation factor (VIF), with values greater than 10 indicating problematic collinearity (<xref ref-type="bibr" rid="ref18">18</xref>). Nonlinearity in continuous variables was modeled using restricted cubic splines with four knots placed at the 5th, 35th, 65th, and 95th percentiles (<xref ref-type="bibr" rid="ref19">19</xref>). To address potential imbalances in covariates, propensity score matching (PSM) was performed using logistic regression with a logit link to estimate propensity scores (R package &#x2018;MatchIt&#x2019;) (<xref ref-type="bibr" rid="ref20">20</xref>). One-to-one nearest-neighbor matching without replacement was applied, with the caliper width set to 0.2 of the standard deviation of the logit of the propensity score. Covariate balance after matching was assessed using standardized mean differences (SMDs), with values below 0.2 indicating adequate balance (<xref ref-type="bibr" rid="ref21">21</xref>). Sensitivity analyses excluded patients with uremia, hydrocephalus, or cerebral herniation to ensure the robustness of findings. Statistical analyses were conducted using R software (version 4.4.1), with significance defined at two-sided <italic>p</italic>-value &#x003C; 0.05.</p>
</sec>
</sec>
<sec sec-type="results" id="sec9">
<title>Results</title>
<sec id="sec10">
<title>Baseline characteristics of participants</title>
<p>The baseline characteristics of the participants are summarized in <xref ref-type="table" rid="tab1">Table 1</xref>. A total of 21,459 patients were included in the study, with an average age of 66.41&#x202F;&#x00B1;&#x202F;12.35&#x202F;years. Among them, 49.47% were female and 50.53% were male. Participants were divided into quartiles (Q1-Q4) based on serum uric acid (SUA) levels, with average SUA levels of 279.31&#x202F;&#x00B1;&#x202F;24.05&#x202F;&#x03BC;mol/L, 320.85&#x202F;&#x00B1;&#x202F;8.57&#x202F;&#x03BC;mol/L, 351.28&#x202F;&#x00B1;&#x202F;10.86&#x202F;&#x03BC;mol/L, and 425.28&#x202F;&#x00B1;&#x202F;41.18&#x202F;&#x03BC;mol/L, respectively. Participants aged &#x2265;60&#x202F;years accounted for 73.68% of the cohort, and NIH Stroke Scale (NIHSS) scores averaged 8.01&#x202F;&#x00B1;&#x202F;2.94. Most participants (73.31%) had NIHSS scores &#x003C;10. Key comorbidities included hypertension (68.74%), diabetes (34.12%), coronary disease (45.07%), and hyperlipidemia (20.83%). The prevalence of PSE was 4.36%, with significant differences across SUA quartiles (<italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001). Laboratory indicators showed significant differences across quartiles, including platelet count, red blood cell count, LDL-C, creatinine, urea, and fibrinogen.</p>
<table-wrap position="float" id="tab1">
<label>Table 1</label>
<caption>
<p>Baseline characteristics of participants by quartiles of blood uric acid.<xref ref-type="table-fn" rid="tfn1"><sup>a</sup></xref></p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Characteristics</th>
<th align="left" valign="top">Total</th>
<th align="left" valign="top">Q1 (&#x003C;305.3)</th>
<th align="left" valign="top">Q2 (305.3&#x2013;335.3)</th>
<th align="left" valign="top">Q3 (335.3&#x2013;373.9)</th>
<th align="left" valign="top">Q4 (&#x2265;373.9)</th>
<th align="left" valign="top" rowspan="2"><italic>p</italic>-value</th>
</tr>
<tr>
<th align="left" valign="top">(<italic>n</italic> =&#x202F;21,459)</th>
<th align="left" valign="top">(<italic>n</italic> =&#x202F;5,372)</th>
<th align="left" valign="top">(<italic>n</italic> =&#x202F;5,374)</th>
<th align="left" valign="top">(<italic>n</italic> =&#x202F;5,349)</th>
<th align="left" valign="top">(<italic>n</italic> =&#x202F;5,364)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Blood uric acid, &#x03BC;mol/L</td>
<td align="left" valign="top">344.14&#x202F;&#x00B1;&#x202F;58.84</td>
<td align="left" valign="top">279.31&#x202F;&#x00B1;&#x202F;24.05</td>
<td align="left" valign="top">320.85&#x202F;&#x00B1;&#x202F;8.57</td>
<td align="left" valign="top">351.28&#x202F;&#x00B1;&#x202F;10.86</td>
<td align="left" valign="top">425.28&#x202F;&#x00B1;&#x202F;41.18</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Age (years)</td>
<td align="left" valign="top">66.41&#x202F;&#x00B1;&#x202F;12.35</td>
<td align="left" valign="top">68.26&#x202F;&#x00B1;&#x202F;12.14</td>
<td align="left" valign="top">67.08&#x202F;&#x00B1;&#x202F;11.81</td>
<td align="left" valign="top">65.04&#x202F;&#x00B1;&#x202F;11.75</td>
<td align="left" valign="top">65.25&#x202F;&#x00B1;&#x202F;13.35</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Age</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">&#x003C;60</td>
<td align="left" valign="top">5,647 (26.32)</td>
<td align="left" valign="top">1,095 (20.38)</td>
<td align="left" valign="top">1,315 (24.47)</td>
<td align="left" valign="top">1,468 (27.44)</td>
<td align="left" valign="top">1769 (32.98)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x003E;&#x202F;=&#x202F;60</td>
<td align="left" valign="top">15,812 (73.68)</td>
<td align="left" valign="top">4,277 (79.62)</td>
<td align="left" valign="top">4,059 (75.53)</td>
<td align="left" valign="top">3,881 (72.56)</td>
<td align="left" valign="top">3,595 (67.02)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">Gender</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Female</td>
<td align="left" valign="top">10,616 (49.47)</td>
<td align="left" valign="top">4,182 (77.85)</td>
<td align="left" valign="top">3,261 (60.68)</td>
<td align="left" valign="top">1732 (32.38)</td>
<td align="left" valign="top">1,441 (26.86)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">Male</td>
<td align="left" valign="top">10,843 (50.53)</td>
<td align="left" valign="top">1,190 (22.15)</td>
<td align="left" valign="top">2,113 (39.32)</td>
<td align="left" valign="top">3,617 (67.62)</td>
<td align="left" valign="top">3,923 (73.14)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">NIHSS</td>
<td align="left" valign="top">8.01&#x202F;&#x00B1;&#x202F;2.94</td>
<td align="left" valign="top">8.91&#x202F;&#x00B1;&#x202F;3.27</td>
<td align="left" valign="top">8.12&#x202F;&#x00B1;&#x202F;3.18</td>
<td align="left" valign="top">7.77&#x202F;&#x00B1;&#x202F;2.49</td>
<td align="left" valign="top">7.24&#x202F;&#x00B1;&#x202F;2.45</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">NIHSS</td>
<td/>
<td/>
<td/>
<td/>
<td/>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">&#x003C;10</td>
<td align="left" valign="top">15,731 (73.31)</td>
<td align="left" valign="top">4,181 (78.16)</td>
<td align="left" valign="top">3,286 (61.17)</td>
<td align="left" valign="top">3,715 (69.13)</td>
<td align="left" valign="top">4,549 (84.81)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">&#x2265;10</td>
<td align="left" valign="top">5,728 (26.69)</td>
<td align="left" valign="top">1,168 (21.84)</td>
<td align="left" valign="top">2086 (38.83)</td>
<td align="left" valign="top">1,659 (30.87)</td>
<td align="left" valign="top">815 (15.19)</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">Uremia</td>
<td align="left" valign="top">190 (0.89)</td>
<td align="left" valign="top">11 (0.20)</td>
<td align="left" valign="top">19 (0.35)</td>
<td align="left" valign="top">23 (0.43)</td>
<td align="left" valign="top">137 (2.55)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Deep vein thrombosis</td>
<td align="left" valign="top">1,324 (6.17)</td>
<td align="left" valign="top">448 (8.34)</td>
<td align="left" valign="top">312 (5.81)</td>
<td align="left" valign="top">230 (4.30)</td>
<td align="left" valign="top">334 (6.23)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Fatty liver</td>
<td align="left" valign="top">4,245 (19.78)</td>
<td align="left" valign="top">560 (10.42)</td>
<td align="left" valign="top">1,044 (19.43)</td>
<td align="left" valign="top">1,027 (19.20)</td>
<td align="left" valign="top">1,614 (30.09)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Diabetes</td>
<td align="left" valign="top">7,322 (34.12)</td>
<td align="left" valign="top">1,087 (20.23)</td>
<td align="left" valign="top">1748 (32.53)</td>
<td align="left" valign="top">2047 (38.27)</td>
<td align="left" valign="top">2,440 (45.49)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Hypertension</td>
<td align="left" valign="top">14,751 (68.74)</td>
<td align="left" valign="top">3,274 (60.95)</td>
<td align="left" valign="top">3,472 (64.61)</td>
<td align="left" valign="top">3,605 (67.40)</td>
<td align="left" valign="top">4,400 (82.03)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Coronary disease</td>
<td align="left" valign="top">9,672 (45.07)</td>
<td align="left" valign="top">1993 (37.10)</td>
<td align="left" valign="top">2065 (38.43)</td>
<td align="left" valign="top">2,565 (47.95)</td>
<td align="left" valign="top">3,049 (56.84)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Atrial fibrillation</td>
<td align="left" valign="top">2043 (9.52)</td>
<td align="left" valign="top">460 (8.56)</td>
<td align="left" valign="top">421 (7.83)</td>
<td align="left" valign="top">496 (9.27)</td>
<td align="left" valign="top">666 (12.42)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Cerebral herniation</td>
<td align="left" valign="top">181 (0.84)</td>
<td align="left" valign="top">86 (1.60)</td>
<td align="left" valign="top">25 (0.47)</td>
<td align="left" valign="top">42 (0.79)</td>
<td align="left" valign="top">28 (0.52)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Hydrocephalus</td>
<td align="left" valign="top">281 (1.31)</td>
<td align="left" valign="top">78 (1.45)</td>
<td align="left" valign="top">85 (1.58)</td>
<td align="left" valign="top">62 (1.16)</td>
<td align="left" valign="top">56 (1.04)</td>
<td align="left" valign="top">0.05</td>
</tr>
<tr>
<td align="left" valign="top">Hyperlipidemia</td>
<td align="left" valign="top">4,469 (20.83)</td>
<td align="left" valign="top">974 (18.13)</td>
<td align="left" valign="top">1,115 (20.75)</td>
<td align="left" valign="top">1,000 (18.70)</td>
<td align="left" valign="top">1,380 (25.73)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Hypoproteinemia</td>
<td align="left" valign="top">2,421 (11.28)</td>
<td align="left" valign="top">1,027 (19.12)</td>
<td align="left" valign="top">418 (7.78)</td>
<td align="left" valign="top">493 (9.22)</td>
<td align="left" valign="top">483 (9.00)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Anterior cerebral artery</td>
<td align="left" valign="top">274 (1.28)</td>
<td align="left" valign="top">120 (2.23)</td>
<td align="left" valign="top">63 (1.17)</td>
<td align="left" valign="top">37 (0.69)</td>
<td align="left" valign="top">54 (1.01)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Middle cerebral artery</td>
<td align="left" valign="top">828 (3.86)</td>
<td align="left" valign="top">198 (3.69)</td>
<td align="left" valign="top">196 (3.65)</td>
<td align="left" valign="top">225 (4.21)</td>
<td align="left" valign="top">209 (3.90)</td>
<td align="left" valign="top">0.42</td>
</tr>
<tr>
<td align="left" valign="top">Posterior cerebral artery</td>
<td align="left" valign="top">62 (0.29)</td>
<td align="left" valign="top">17 (0.32)</td>
<td align="left" valign="top">21 (0.39)</td>
<td align="left" valign="top">13 (0.24)</td>
<td align="left" valign="top">11 (0.21)</td>
<td align="left" valign="top">0.29</td>
</tr>
<tr>
<td align="left" valign="top">Vertebral artery</td>
<td align="left" valign="top">652 (3.04)</td>
<td align="left" valign="top">183 (3.41)</td>
<td align="left" valign="top">158 (2.94)</td>
<td align="left" valign="top">135 (2.52)</td>
<td align="left" valign="top">176 (3.28)</td>
<td align="left" valign="top">0.04</td>
</tr>
<tr>
<td align="left" valign="top">Basilar artery</td>
<td align="left" valign="top">191 (0.89)</td>
<td align="left" valign="top">75 (1.40)</td>
<td align="left" valign="top">37 (0.69)</td>
<td align="left" valign="top">29 (0.54)</td>
<td align="left" valign="top">50 (0.93)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Platelet count, (&#x00D7;10<sup>9</sup>/L)</td>
<td align="left" valign="top">189.90&#x202F;&#x00B1;&#x202F;27.02</td>
<td align="left" valign="top">188.02&#x202F;&#x00B1;&#x202F;30.01</td>
<td align="left" valign="top">190.00&#x202F;&#x00B1;&#x202F;24.67</td>
<td align="left" valign="top">188.81&#x202F;&#x00B1;&#x202F;23.84</td>
<td align="left" valign="top">192.76&#x202F;&#x00B1;&#x202F;28.81</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Red blood cell count, (&#x00D7;10<sup>12</sup>/L)</td>
<td align="left" valign="top">4.31&#x202F;&#x00B1;&#x202F;0.32</td>
<td align="left" valign="top">4.18&#x202F;&#x00B1;&#x202F;0.27</td>
<td align="left" valign="top">4.25&#x202F;&#x00B1;&#x202F;0.28</td>
<td align="left" valign="top">4.40&#x202F;&#x00B1;&#x202F;0.30</td>
<td align="left" valign="top">4.41&#x202F;&#x00B1;&#x202F;0.36</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">LDL-C, mg/dL</td>
<td align="left" valign="top">2.69&#x202F;&#x00B1;&#x202F;0.36</td>
<td align="left" valign="top">2.65&#x202F;&#x00B1;&#x202F;0.40</td>
<td align="left" valign="top">2.70&#x202F;&#x00B1;&#x202F;0.31</td>
<td align="left" valign="top">2.70&#x202F;&#x00B1;&#x202F;0.36</td>
<td align="left" valign="top">2.71&#x202F;&#x00B1;&#x202F;0.36</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Creatinine, &#x03BC;mol/L</td>
<td align="left" valign="top">84.89&#x202F;&#x00B1;&#x202F;51.17</td>
<td align="left" valign="top">70.55&#x202F;&#x00B1;&#x202F;14.23</td>
<td align="left" valign="top">76.99&#x202F;&#x00B1;&#x202F;18.60</td>
<td align="left" valign="top">79.67&#x202F;&#x00B1;&#x202F;26.10</td>
<td align="left" valign="top">112.35&#x202F;&#x00B1;&#x202F;90.53</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Urea, mmol/L</td>
<td align="left" valign="top">6.40&#x202F;&#x00B1;&#x202F;1.43</td>
<td align="left" valign="top">6.05&#x202F;&#x00B1;&#x202F;0.98</td>
<td align="left" valign="top">6.27&#x202F;&#x00B1;&#x202F;1.11</td>
<td align="left" valign="top">6.31&#x202F;&#x00B1;&#x202F;1.41</td>
<td align="left" valign="top">6.98&#x202F;&#x00B1;&#x202F;1.88</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Fibrinogen, g/L</td>
<td align="left" valign="top">3.60&#x202F;&#x00B1;&#x202F;0.47</td>
<td align="left" valign="top">3.56&#x202F;&#x00B1;&#x202F;0.54</td>
<td align="left" valign="top">3.55&#x202F;&#x00B1;&#x202F;0.39</td>
<td align="left" valign="top">3.57&#x202F;&#x00B1;&#x202F;0.42</td>
<td align="left" valign="top">3.72&#x202F;&#x00B1;&#x202F;0.51</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">post-stroke epilepsy</td>
<td align="left" valign="top">936 (4.36)</td>
<td align="left" valign="top">314 (5.85)</td>
<td align="left" valign="top">220 (4.09)</td>
<td align="left" valign="top">156 (2.92)</td>
<td align="left" valign="top">246 (4.59)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn1">
<label>a</label>
<p>Continuous variables are presented as mean&#x00B1;SD or median (IQR); categorical variables are presented as <italic>n</italic> (%).</p>
</fn>
<p>NIHSS, National Institutes of Health Stroke Scale.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec11">
<title>Association of SUA and PSE</title>
<p><xref ref-type="table" rid="tab2">Table 2</xref> illustrates the association between serum uric acid (SUA) levels and post-stroke epilepsy (PSE) across three logistic regression models. In Model 3, all variance inflation factor (VIF) values were below 5, indicating that multicollinearity did not significantly affect the model&#x2019;s stability (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>). In all models, both the lowest SUA quartile (Q1) and the highest SUA quartile (Q4) were significantly associated with increased risks of PSE compared to the reference group (Q3). After considering potential confounders, a U-shaped relationship between SUA and PSE was observed through quartile analysis. Compared to the Q3 group, the odds ratios (ORs) for Q1, Q2 and Q4 were 2.32 (95% CI: 1.79&#x2013;2.99, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001), 1.5 (95% CI: 1.18&#x2013;1.92, <italic>p</italic>&#x202F;=&#x202F;0.001) and 1.60 (95% CI: 1.26&#x2013;2.02, p&#x202F;&#x003C;&#x202F;0.0001), respectively. Considering the comparable risks observed in Q2 and Q3, the second and third quartiles were combined into one group (the 2&#x2013;3 quartiles) for simplified analysis. As expected, compared with those in the 2&#x2013;3 quartiles, participants in Q1 and Q4 demonstrated significantly higher risks of PSE, with adjusted ORs of 1.80 (95% CI: 1.47&#x2013;2.22) and 1.35 (95% CI: 1.10&#x2013;1.66) in the fully adjusted Model 3, respectively. To further explore sex differences, we conducted sex-stratified analyses of the association between SUA quartiles and PSE risk (Q3 as the reference). Among women, the ORs for Q1, Q2, and Q4 versus Q3 were 1.074 (95% CI 0.794&#x2013;1.472; <italic>p</italic> =&#x202F;0.651), 0.838 (95% CI 0.602&#x2013;1.176; <italic>p</italic> =&#x202F;0.299), and 1.341 (95% CI 0.934&#x2013;1.931; <italic>p</italic> =&#x202F;0.112), respectively. Among men, the corresponding ORs were 5.740 (95% CI 4.436&#x2013;7.463; <italic>p</italic> &#x003C;&#x202F;0.0001), 2.315 (95% CI 1.772&#x2013;3.035; <italic>p</italic> &#x003C;&#x202F;0.0001), and 1.747 (95% CI 1.364&#x2013;2.250; <italic>p</italic> &#x003C;&#x202F;0.0001) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S2</xref>). A likelihood ratio test indicated a significant interaction between SUA quartiles and sex (LR <italic>&#x03C7;</italic><sup>2</sup> =&#x202F;104.83; &#x0394;df&#x202F;=&#x202F;3; P for interaction &#x003C; 2.2&#x202F;&#x00D7;&#x202F;10<sup>&#x2212;16</sup>) (<xref ref-type="supplementary-material" rid="SM1">Supplementary Table S3</xref>).</p>
<table-wrap position="float" id="tab2">
<label>Table 2</label>
<caption>
<p>Associations between serum uric acid levels and epilepsy.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Serum uric acid, &#x03BC;mol/L</th>
<th align="left" valign="top">Model 1</th>
<th align="left" valign="top" rowspan="2"><italic>p</italic>-value</th>
<th align="left" valign="top">Model 2</th>
<th align="left" valign="top" rowspan="2"><italic>p</italic>-value</th>
<th align="left" valign="top">Model 3</th>
<th align="left" valign="top" rowspan="2"><italic>p</italic>-value</th>
</tr>
<tr>
<th align="left" valign="top">OR (95%CI)</th>
<th align="left" valign="top">OR (95%CI)</th>
<th align="left" valign="top">OR (95%CI)</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top" colspan="7">Quartiles</td>
</tr>
<tr>
<td align="left" valign="top">Q1</td>
<td align="left" valign="top">2.07 (1.70, 2.51)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">2.96 (2.41, 3.65)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">2.32 (1.79, 2.99)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Q2</td>
<td align="left" valign="top">1.42 (1.15, 1.75)</td>
<td align="left" valign="top">&#x003C;0.001</td>
<td align="left" valign="top">1.77 (1.43, 2.18)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.50 (1.18, 1.92)</td>
<td align="left" valign="top">0.001</td>
</tr>
<tr>
<td align="left" valign="top">Q3</td>
<td align="left" valign="top">Ref</td>
<td/>
<td align="left" valign="top">Ref</td>
<td/>
<td align="left" valign="top">Ref</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">Q4</td>
<td align="left" valign="top">1.60 (1.30, 1.96)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.53 (1.25, 1.88)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.60 (1.26, 2.02)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top" colspan="7">Categorical</td>
</tr>
<tr>
<td align="left" valign="top">Q1</td>
<td align="left" valign="top">1.71 (1.47, 1.99)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">2.15 (1.83, 2.53)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.80 (1.47, 2.22)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Q2-Q3</td>
<td align="left" valign="top">Ref</td>
<td/>
<td align="left" valign="top">Ref</td>
<td/>
<td align="left" valign="top">Ref</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">Q4</td>
<td align="left" valign="top">1.32 (1.12, 1.56)</td>
<td align="left" valign="top">&#x003C;0.001</td>
<td align="left" valign="top">1.16 (0.98, 1.37)</td>
<td align="left" valign="top">&#x003C;0.08</td>
<td align="left" valign="top">1.35 (1.10, 1.66)</td>
<td align="left" valign="top">0.005</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Model 1: No covariates were adjusted.</p>
<p>Model 2: Age, gender.</p>
<p>Model 3: Age, gender, NIHSS, Uremia, Deep vein thrombosis, Fatty liver, Diabetes, Hypertension, Coronary disease.</p>
<p>Atrial fibrillation, Cerebral herniation, Hydrocephalus, Hyperlipidemia, Hypoproteinemia, Anterior cerebral artery.</p>
<p>Middle cerebral artery, Posterior cerebral artery, Vertebral artery, Basilar artery, Platelet count, Red blood cell count.</p>
<p>LDL-C, Creatinine, Urea, and Fibrinogen.</p>
<p>Q, quartiles; OR, odds ratio; 95% CI, 95% confidence interval.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec12">
<title>Restricted cubic spline (RCS) analysis</title>
<p>In our multivariate Logistic regression analysis, we identified a possible nonlinear association between the SUA levels and PSE risk. To further validate the association between the SUA levels and PSE risk, we employed RCS analysis. Our results demonstrated a U-shaped association between the SUA levels and PSE risk in Models 1, 2 and 3 (<italic>p</italic> value for nonlinearity &#x003C;0.001) (<xref ref-type="fig" rid="fig1">Figure 1</xref>). In addition to this, we further fitted the association between the serum uric acid levels at admission and PSE risk using a two-piecewise multivariate logistic regression model and found two different slopes. We identified an inflection point at approximately 335.3&#x202F;&#x03BC;mol/L (<xref ref-type="fig" rid="fig1">Figure 1</xref>). Below this threshold (SUA&#x202F;&#x003C;&#x202F;335.3&#x202F;&#x03BC;mol/L), SUA levels were negatively associated with PSE risk, while above this threshold, they were positively associated. On the left side of the inflection point, the OR was 0.992 (95% CI: 0.989&#x2013;0.996, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001). On the right side of the inflection point, the ORs was 1.009 (95% CI: 1.007&#x2013;1.012, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001) (<xref ref-type="table" rid="tab3">Table 3</xref>). This indicates that the risk of PSE started to decrease by 0.8% per 1&#x202F;&#x03BC;mol/L SUA change until a level of 335.3&#x202F;&#x03BC;mol/L. Then the risk of PSE started to increase by 0.9% per 1&#x202F;&#x03BC;mol/L SUA change (<italic>p</italic>-value for non-linearity &#x003C;0.0001).</p>
<fig position="float" id="fig1">
<label>Figure 1</label>
<caption>
<p>Nonlinear association between serum uric acid at admission and post-stroke epilepsy (PSE) in restricted cubic spline models. The solid red curve denotes the estimated odds ratio (OR) and the shaded area the 95% confidence interval; the horizontal dashed line indicates OR&#x202F;=&#x202F;1, and the vertical dashed line marks the reference SUA level (335.3&#x202F;&#x03BC;mol/L). The histogram below shows the distribution of SUA <bold>(A)</bold> Unadjusted model. <bold>(B)</bold> Model adjusted for age and sex. <bold>(C)</bold> Fully adjusted model including age, sex, NIHSS at admission; comorbidities (uremia, deep vein thrombosis, fatty liver, diabetes, hypertension, coronary disease, atrial fibrillation, cerebral herniation, hydrocephalus, hyperlipidemia, hypoproteinemia); major cerebral artery stenosis/occlusion (anterior, middle, posterior cerebral; vertebral; basilar); and laboratory measures (platelet count, red blood cell count, LDL-C, creatinine, urea, fibrinogen). Nonlinearity was assessed with a likelihood ratio test; <italic>p</italic>&#x202F;&#x003C;&#x202F;0.001 for all panels.</p>
</caption>
<graphic xlink:href="fneur-17-1759537-g001.tif" mimetype="image" mime-subtype="tiff">
<alt-text content-type="machine-generated">A set of three graphs labeled A, B, and C show the relationship between serum uric acid (SUA) levels and the odds ratio of PSE. Each graph includes a red curve with a shaded area indicating confidence intervals, showing a U-shaped non-linear relationship, with a reference point at 335.3 micromoles per liter. The graphs indicate a p-value for non-linearity of less than 0.001. The x-axis represents SUA in micromoles per liter, and the y-axis is the odds ratio of PSE. Each panel includes a histogram of SUA distribution below the main curve.</alt-text>
</graphic>
</fig>
<table-wrap position="float" id="tab3">
<label>Table 3</label>
<caption>
<p>Threshold effect of serum uric acid levels on secondary epilepsy risk in acute ischemic stroke patients.<xref ref-type="table-fn" rid="tfn2"><sup>a</sup></xref></p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top">Epilepsy</th>
<th align="center" valign="top">OR (95%CI)</th>
<th align="center" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Fitting by the standard linear regression</td>
<td align="center" valign="top">1.002 (1.001,1.004)</td>
<td align="char" valign="top" char=".">0.003</td>
</tr>
<tr>
<td align="left" valign="top">Fitting model by two-piecewise linear regression</td>
<td/>
<td/>
</tr>
<tr>
<td align="left" valign="top">Inflection point</td>
<td align="center" valign="top">335.3</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">SUA&#x202F;&#x003C;&#x202F;IP</td>
<td align="center" valign="top">0.992 (0.989,0.996)</td>
<td align="char" valign="top" char=".">&#x003C;0.001</td>
</tr>
<tr>
<td align="left" valign="top">SUA&#x202F;&#x2265;&#x202F;IP</td>
<td align="center" valign="top">1.009 (1.007, 1.012)</td>
<td align="char" valign="top" char=".">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">p for Log-likelihood ratio</td>
<td/>
<td align="char" valign="top" char=".">&#x003C;0.0001</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn id="tfn2">
<label>a</label>
<p>Adjusted for all covariates in <xref ref-type="table" rid="tab1">Table 1</xref>.</p>
</fn>
<p>SUA, serum uric acid; OR, odds ratio; 95% CI, 95% confidence interval; IP, Inflection point.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec13">
<title>Analysis of the association between SUA and PSE after PSM</title>
<p>To simplify analysis, the Q2 and Q3 groups (quartiles 2&#x2013;3, 305.3 to 373.9&#x202F;&#x03BC;mol/L) were combined due to their comparable risks of PSE. Propensity score matching (PSM) significantly improved the balance of covariates between comparison groups, as demonstrated in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S1</xref>. Most variables achieved adequate balance with standardized mean differences (SMDs) below 0.2 after matching, except for Creatinine and Urea, which slightly exceeded the commonly accepted threshold (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref>). Despite this residual imbalance, propensity score-matched logistic regression models (both unadjusted and adjusted) consistently demonstrated a U-shaped association between serum uric acid (SUA) levels and PSE risk. Compared to the Q2&#x2013;Q3 group, participants in Q1 showed an adjusted odds ratio (OR) of 1.94 (95% CI: 1.56&#x2013;2.42), while those in Q4 exhibited an adjusted OR of 1.33 (95% CI: 1.02&#x2013;1.74) (<xref ref-type="table" rid="tab4">Table 4</xref>). Furthermore, RCS analyses supported the U-shaped association across all three models (Model 1, Model 2, and Model 3) in the post-PSM dataset, with <italic>p</italic> values for nonlinearity consistently &#x003C;0.001 (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S2</xref>).</p>
<table-wrap position="float" id="tab4">
<label>Table 4</label>
<caption>
<p>Association between serum uric acid levels and epilepsy in the propensity score-matched cohort.</p>
</caption>
<table frame="hsides" rules="groups">
<thead>
<tr>
<th align="left" valign="top" rowspan="2">Serum uric acid, &#x03BC;mol/L</th>
<th align="left" valign="top" colspan="2">Model 1</th>
<th align="left" valign="top" colspan="2">Model 2</th>
<th align="left" valign="top" colspan="2">Model 3</th>
</tr>
<tr>
<th align="left" valign="top">OR (95%CI)</th>
<th align="left" valign="top"><italic>p</italic>-value</th>
<th align="left" valign="top">OR (95%CI)</th>
<th align="left" valign="top"><italic>p</italic>-value</th>
<th align="left" valign="top">OR (95%CI)</th>
<th align="left" valign="top"><italic>p</italic>-value</th>
</tr>
</thead>
<tbody>
<tr>
<td align="left" valign="top">Q1</td>
<td align="left" valign="top">1.79 (1.48, 2.16)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.98 (1.64, 2.40)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.94 (1.56, 2.42)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
</tr>
<tr>
<td align="left" valign="top">Q2-3</td>
<td align="left" valign="top">Ref</td>
<td/>
<td align="left" valign="top">Ref</td>
<td/>
<td align="left" valign="top">Ref</td>
<td/>
</tr>
<tr>
<td align="left" valign="top">Q4</td>
<td align="left" valign="top">1.39 (1.14, 1.69)</td>
<td align="left" valign="top">&#x003C;0.0001</td>
<td align="left" valign="top">1.02 (0.83, 1.26)</td>
<td align="left" valign="top">0.82</td>
<td align="left" valign="top">1.33 (1.02, 1.74)</td>
<td align="left" valign="top">0.03</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<p>Model 1: No covariates were adjusted.</p>
<p>Model 2: Age and gender were adjusted.</p>
<p>Model 3: Age, gender, NIHSS, Uremia, Deep vein thrombosis, Fatty liver, Diabetes, Hypertension, Coronary disease.</p>
<p>Atrial fibrillation, Cerebral herniation, Hydrocephalus, Hyperlipidemia, Hypoproteinemia, Anterior cerebral artery.</p>
<p>Middle cerebral artery, Posterior cerebral artery, Vertebral artery, Basilar artery, Platelet count, Red blood cell count.</p>
<p>LDL-C, Creatinine, Urea, and Fibrinogen were adjusted.</p>
<p>Q, quartiles; OR, odds ratio; 95% CI, 95% confidence interval.</p>
</table-wrap-foot>
</table-wrap>
</sec>
<sec id="sec14">
<title>Sensitivity analysis</title>
<p>To ensure the robustness of our findings and exclude potential confounding effects, a sensitivity analysis was conducted by excluding patients with uremia, hydrocephalus, or cerebral herniation - conditions that might influence SUA levels and/or epilepsy risk (<xref ref-type="bibr" rid="ref22 ref23 ref24">22&#x2013;24</xref>). The results, presented in <xref ref-type="supplementary-material" rid="SM1">Supplementary Table S5</xref>, remained consistent with the primary analysis. Univariate analysis showed a significant association between SUA quintiles and PSE, with SUA Q1 and Q4 exhibiting elevated ORs compared to the reference group (Q3). Specifically, SUA Q1 had an OR of 2.12 (95% CI: 1.97&#x2013;2.59, <italic>p</italic>&#x202F;&#x003C;&#x202F;0.0001), while SUA Q4 had an ORs of 1.59 (95% CI: 1.29&#x2013;1.97, p&#x202F;&#x003C;&#x202F;0.0001). Multivariable analysis revealed adjusted ORs of 2.52 (95% CI: 1.95&#x2013;3.24, p&#x202F;&#x003C;&#x202F;0.0001) for SUA Q1 and 1.68 (95% CI: 1.33&#x2013;2.12, p&#x202F;&#x003C;&#x202F;0.0001) for SUA Q4, further corroborating the U-shaped relationship observed in the main analysis.</p>
</sec>
</sec>
<sec sec-type="discussion" id="sec15">
<title>Discussion</title>
<p>The present study provides compelling evidence of a U-shaped relationship between SUA levels and the risk of PSE in patients with acute ischemic stroke. Using data from a large cohort, we demonstrated that both low (Q1: &#x003C;305.3&#x202F;&#x03BC;mol/L) and high (Q4: &#x003E;373.9&#x202F;&#x03BC;mol/L) SUA levels were associated with significantly increased risks of PSE compared to the moderate levels (Q2-Q3: 305.3&#x2013;373.9&#x202F;&#x03BC;mol/L). After adjusting for multiple confounders, including demographic factors, stroke severity (NIHSS score), comorbidities, and laboratory markers, the adjusted ORs for the Q1 and Q4 groups were 2.32 (95% CI: 1.79&#x2013;2.99) and 1.60 (95% CI: 1.26&#x2013;2.02), respectively. This pattern was confirmed through RCS analyses, which identified an inflection point at 335.3&#x202F;&#x03BC;mol/L. Moreover, the robustness of these findings was reinforced by PSM and sensitivity analyses. After PSM, the non-linear association remained statistically significant. Notably, a significant interaction between SUA quartiles and sex was observed (P for interaction &#x003C; 2.2&#x202F;&#x00D7;&#x202F;10<sup>&#x2212;16</sup>), suggesting that the overall association reflects an average effect and is more pronounced in men (<xref ref-type="supplementary-material" rid="SM1">Supplementary Tables S1, S2</xref>). Given the close link between SUA and renal function, we adjusted for urea, creatinine, and uremia (Model 3) and performed PSM; however, slight post-matching imbalance in renal biomarkers remained (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref>), and residual confounding cannot be excluded. Collectively, our results underscore the dual role of SUA as both a potential protective factor and a risk factor for PSE, depending on its concentration.</p>
<p>This non-linear relationship can be mechanistically explained by the dual biological properties of uric acid (<xref ref-type="bibr" rid="ref16">16</xref>, <xref ref-type="bibr" rid="ref25">25</xref>). On one hand, SUA acts as a potent endogenous antioxidant, capable of scavenging reactive oxygen species (ROS) and inhibiting lipid peroxidation (<xref ref-type="bibr" rid="ref26">26</xref>, <xref ref-type="bibr" rid="ref27">27</xref>). This antioxidant capacity is particularly relevant in the context of ischemic stroke, where oxidative stress contributes significantly to neuronal damage and subsequent epileptogenesis (<xref ref-type="bibr" rid="ref28">28</xref>). Moderate SUA levels may thus confer neuroprotection by mitigating oxidative injury, thereby reducing the likelihood of PSE. On the other hand, at high concentrations, SUA can crystallize and trigger inflammatory pathways, such as the NLRP3 inflammasome, leading to the release of pro-inflammatory cytokines (e.g., IL-1&#x03B2;, IL-18) (<xref ref-type="bibr" rid="ref29">29</xref>). Chronic inflammation is a known driver of epileptogenesis, as it promotes neuronal hyperexcitability and synaptic reorganization (<xref ref-type="bibr" rid="ref30 ref31 ref32">30&#x2013;32</xref>). Additionally, elevated SUA is often linked to metabolic disorders (e.g., hyperuricemia, gout) and renal impairment (<xref ref-type="bibr" rid="ref15">15</xref>, <xref ref-type="bibr" rid="ref33">33</xref>), which may independently exacerbate stroke outcomes and increase susceptibility to seizures.</p>
<p>Conversely, very low SUA levels may reflect a state of compromised antioxidant defense (<xref ref-type="bibr" rid="ref34">34</xref>). Inadequate ROS scavenging could leave neurons vulnerable to oxidative damage, facilitating excitotoxic neuronal death and aberrant synaptic plasticity&#x2014;key processes in epilepsy development (<xref ref-type="bibr" rid="ref35">35</xref>, <xref ref-type="bibr" rid="ref36">36</xref>). The identified inflection point (335.3&#x202F;&#x03BC;mol/L) is consistent with this dual-role hypothesis, suggesting that the balance between antioxidant and pro-inflammatory milieus may vary across SUA levels.</p>
<p>Clinically, these findings suggest that SUA could serve as a valuable biomarker for PSE risk stratification. Patients with SUA levels outside the range associated with the lowest predicted odds in our data may warrant further investigation in future studies. For instance, low and high SUA levels may reflect different underlying biological profiles (e.g., oxidative stress&#x2013;related vs. inflammatory/metabolic states). These mechanistic hypotheses require validation in experimental studies and prospective cohorts.</p>
<p>Our results both corroborate and extend the existing literature on SUA and neurological outcomes (<xref ref-type="bibr" rid="ref37">37</xref>). Several studies have highlighted the neuroprotective role of SUA in stroke recovery. For example, Chamorro et al. (<xref ref-type="bibr" rid="ref38">38</xref>) reported that higher SUA levels were associated with improved functional outcomes after acute ischemic stroke, attributing this to SUA&#x2019;s antioxidant properties. Similarly, Dhanesha et al. (<xref ref-type="bibr" rid="ref39">39</xref>) found that SUA administration reduced infarct size and improved neurological recovery in animal models of stroke. These studies support our observation that moderate SUA levels (Q2-Q3) are protective against PSE.</p>
<p>However, our discovery of increased PSE risk at high SUA levels appears to contradict some prior reports. This discrepancy may stem from differences in outcome measures: while earlier studies focused on short-term functional recovery, our work specifically examined PSE-a long-term complication influenced by chronic inflammation and neuronal hyperexcitability. Importantly, recent evidence has begun to acknowledge the &#x201C;paradoxical&#x201D; role of SUA. Zhang et al. (<xref ref-type="bibr" rid="ref40">40</xref>) reported that high SUA levels were associated with increased risk of post-stroke complications, including epilepsy. Similarly, Weir et al. (<xref ref-type="bibr" rid="ref41">41</xref>) identified SUA as a predictor of poor outcomes in stroke patients, particularly among those with pre-existing comorbidities. Wang et al. demonstrated that aberrant serum uric acid levels, whether excessively elevated or markedly reduced, are associated with an increased risk of epilepsy secondary to cerebral infarction, supporting SUA as a clinically relevant biomarker associated with PSE risk (<xref ref-type="bibr" rid="ref14">14</xref>). These studies highlight the complex interplay between SUA, inflammation, and oxidative stress in the post-stroke brain.</p>
<p>Unique to our study is the characterization of this non-linear association using flexible modeling (RCS) and robustness checks (PSM and sensitivity analyses), which strengthens confidence that the pattern is not solely driven by measured confounding. In contrast to prior research that primarily focused on overall stroke outcomes, our study specifically investigates PSE, a clinically significant but underexplored complication of stroke.</p>
<p>While our study provides important insights, several limitations must be acknowledged. First, the observational design limits our ability to infer causality between SUA levels and PSE risk. Second, despite PSM and multivariable adjustments, slight post-matching imbalance in renal biomarkers persisted (<xref ref-type="supplementary-material" rid="SM1">Supplementary Figure S1</xref>), and confounding by renal function and other unmeasured factors cannot be fully ruled out. Third, excluding patients who died in the ultra-early phase may shift the sample toward survivors with milder disease, thereby limiting the generalizability of the observed SUA&#x2013;PSE association. Likewise, excluding patients with severe comorbidities (e.g., uremia, hydrocephalus, or cerebral herniation) may further limit the applicability of our findings to broader stroke populations, as these patients may exhibit distinct SUA&#x2013;PSE dynamics. Additionally, SUA levels were measured at a single time point, which does not capture potential temporal fluctuations or the cumulative effects of SUA over time. Longitudinal studies are needed to better understand how changes in SUA levels influence PSE development. Moreover, the study population was derived from a single center, which may limit the external validity of our findings to other regions or healthcare settings. Finally, the original publication did not report detailed diagnostic criteria for post-stroke epilepsy (e.g., EEG confirmation, ICD coding rules, exclusion of acute symptomatic seizures) or a prespecified adjudication workflow; therefore, we used the dataset-labeled outcome as provided. This may introduce outcome misclassification, which should be considered when interpreting the estimated associations. Future research should aim to elucidate the mechanisms underlying the U-shaped relationship between SUA and PSE through experimental and longitudinal studies. Investigating the role of SUA modulation in animal models of stroke and epilepsy could provide valuable mechanistic insights. Additionally, randomized clinical trials evaluating interventions to optimize SUA levels in stroke patients are warranted. Expanding the study population to include diverse stroke subtypes and severity levels will enhance the generalizability of future findings. Finally, integrating genetic, metabolic, and dietary data could provide a more comprehensive understanding of the factors influencing SUA-PSE dynamics.</p>
</sec>
<sec sec-type="conclusions" id="sec16">
<title>Conclusion</title>
<p>Our study builds on existing evidence and provides novel insights into the association between serum uric acid (SUA) and post-stroke epilepsy (PSE). We observed a non-linear relationship, with the lowest predicted odds of PSE at intermediate SUA levels, suggesting that SUA may reflect heterogeneous biological states relevant to post-stroke neuroinflammation and oxidative stress. These findings are hypothesis-generating and warrant validation in prospective cohorts and mechanistic studies.</p>
</sec>
</body>
<back>
<sec sec-type="data-availability" id="sec17">
<title>Data availability statement</title>
<p>Publicly available datasets were analyzed in this study. This data can be found at: <ext-link xlink:href="https://doi.org/10.5061/dryad.w0vt4b92c" ext-link-type="uri">https://doi.org/10.5061/dryad.w0vt4b92c</ext-link>.</p>
</sec>
<sec sec-type="ethics-statement" id="sec18">
<title>Ethics statement</title>
<p>The studies involving humans were approved by Strengthening the Reporting of Observational Studies in Epidemiology and Dryad&#x2019;s Terms of Service. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation was not required from the participants or the participants&#x2019; legal guardians/next of kin because Its availability for public use was granted by the original authors, enabling secondary analysis while adhering to ethical research standards, including compliance with STROBE guidelines and Dryad&#x2019;s Terms of Service. Written informed consent was not obtained from the individual(s) for the publication of any potentially identifiable images or data included in this article because its availability for public use was granted by the original authors, enabling secondary analysis while adhering to ethical research standards, including compliance with STROBE guidelines and Dryad&#x2019;s Terms of Service.</p>
</sec>
<sec sec-type="author-contributions" id="sec19">
<title>Author contributions</title>
<p>DL: Writing &#x2013; original draft, Validation. HP: Writing &#x2013; original draft. YiZ: Writing &#x2013; original draft. MW: Writing &#x2013; original draft, Investigation. HJ: Data curation, Writing &#x2013; original draft. BS: Writing &#x2013; original draft, Methodology. YuZ: Methodology, Writing &#x2013; original draft. GD: Writing &#x2013; original draft, Validation. NL: Writing &#x2013; review &#x0026; editing. JF: Writing &#x2013; review &#x0026; editing. CZ: Validation, Writing &#x2013; review &#x0026; editing.</p>
</sec>
<ack>
<title>Acknowledgments</title>
<p>The authors express their gratitude to the Dryad Digital Repository for providing the data.</p>
</ack>
<sec sec-type="COI-statement" id="sec20">
<title>Conflict of interest</title>
<p>The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec sec-type="ai-statement" id="sec21">
<title>Generative AI statement</title>
<p>The author(s) declared that Generative AI was not used in the creation of this manuscript.</p>
<p>Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.</p>
</sec>
<sec sec-type="disclaimer" id="sec22">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
<sec sec-type="supplementary-material" id="sec23">
<title>Supplementary material</title>
<p>The Supplementary material for this article can be found online at: <ext-link xlink:href="https://www.frontiersin.org/articles/10.3389/fneur.2026.1759537/full#supplementary-material" ext-link-type="uri">https://www.frontiersin.org/articles/10.3389/fneur.2026.1759537/full#supplementary-material</ext-link></p>
<supplementary-material xlink:href="Image_1.pdf" id="SM1" mimetype="application/pdf" xmlns:xlink="http://www.w3.org/1999/xlink"/>
</sec>
<ref-list>
<title>References</title>
<ref id="ref1"><label>1.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><collab id="coll1">GBD 2021 Diseases and Injuries Collaborators</collab></person-group>. <article-title>Global incidence, prevalence, years lived with disability (YLDs), disability-adjusted life-years (DALYs), and healthy life expectancy (HALE) for 371 diseases and injuries in 204 countries and territories and 811 subnational locations, 1990-2021: a systematic analysis for the global burden of disease study 2021</article-title>. <source>Lancet</source>. (<year>2024</year>) <volume>403</volume>:<fpage>2133</fpage>&#x2013;<lpage>61</lpage>. doi: <pub-id pub-id-type="doi">10.1016/S0140-6736(24)00757-8</pub-id></mixed-citation></ref>
<ref id="ref2"><label>2.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Pitkanen</surname><given-names>A</given-names></name> <name><surname>Roivainen</surname><given-names>R</given-names></name> <name><surname>Lukasiuk</surname><given-names>K</given-names></name></person-group>. <article-title>Development of epilepsy after ischaemic stroke</article-title>. <source>Lancet Neurol</source>. (<year>2016</year>) <volume>15</volume>:<fpage>185</fpage>&#x2013;<lpage>97</lpage>. doi: <pub-id pub-id-type="doi">10.1016/S1474-4422(15)00248-3</pub-id>, <pub-id pub-id-type="pmid">26597090</pub-id></mixed-citation></ref>
<ref id="ref3"><label>3.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Neri</surname><given-names>S</given-names></name> <name><surname>Gasparini</surname><given-names>S</given-names></name> <name><surname>Pascarella</surname><given-names>A</given-names></name> <name><surname>Santangelo</surname><given-names>D</given-names></name> <name><surname>Cianci</surname><given-names>V</given-names></name> <name><surname>Mammi</surname><given-names>A</given-names></name> <etal/></person-group>. <article-title>Epilepsy in cerebrovascular diseases: a narrative review</article-title>. <source>Curr Neuropharmacol</source>. (<year>2023</year>) <volume>21</volume>:<fpage>1634</fpage>&#x2013;<lpage>45</lpage>. doi: <pub-id pub-id-type="doi">10.2174/1570159X20666220706113925</pub-id>, <pub-id pub-id-type="pmid">35794769</pub-id></mixed-citation></ref>
<ref id="ref4"><label>4.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bentes</surname><given-names>C</given-names></name> <name><surname>Rodrigues</surname><given-names>FB</given-names></name> <name><surname>Sousa</surname><given-names>D</given-names></name> <name><surname>Duarte</surname><given-names>GS</given-names></name> <name><surname>Franco</surname><given-names>AC</given-names></name> <name><surname>Marques</surname><given-names>R</given-names></name> <etal/></person-group>. <article-title>Frequency of post-stroke electroencephalographic epileptiform activity&#x2014;a systematic review and meta-analysis of observational studies</article-title>. <source>Eur Stroke J</source>. (<year>2017</year>) <volume>2</volume>:<fpage>361</fpage>&#x2013;<lpage>8</lpage>. doi: <pub-id pub-id-type="doi">10.1177/2396987317731004</pub-id>, <pub-id pub-id-type="pmid">31008328</pub-id></mixed-citation></ref>
<ref id="ref5"><label>5.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Galovic</surname><given-names>M</given-names></name> <name><surname>Ferreira-Atuesta</surname><given-names>C</given-names></name> <name><surname>Abraira</surname><given-names>L</given-names></name> <name><surname>Dohler</surname><given-names>N</given-names></name> <name><surname>Sinka</surname><given-names>L</given-names></name> <name><surname>Brigo</surname><given-names>F</given-names></name> <etal/></person-group>. <article-title>Seizures and epilepsy after stroke: epidemiology, biomarkers and management</article-title>. <source>Drugs Aging</source>. (<year>2021</year>) <volume>38</volume>:<fpage>285</fpage>&#x2013;<lpage>99</lpage>. doi: <pub-id pub-id-type="doi">10.1007/s40266-021-00837-7</pub-id>, <pub-id pub-id-type="pmid">33619704</pub-id></mixed-citation></ref>
<ref id="ref6"><label>6.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>C</given-names></name> <name><surname>Cui</surname><given-names>T</given-names></name> <name><surname>Wang</surname><given-names>L</given-names></name> <name><surname>Zhu</surname><given-names>Q</given-names></name> <name><surname>Wang</surname><given-names>A</given-names></name> <name><surname>Yuan</surname><given-names>Y</given-names></name> <etal/></person-group>. <article-title>Prognostic significance of uric acid change in acute ischemic stroke patients with reperfusion therapy</article-title>. <source>Eur J Neurol</source>. (<year>2021</year>) <volume>28</volume>:<fpage>1218</fpage>&#x2013;<lpage>24</lpage>. doi: <pub-id pub-id-type="doi">10.1111/ene.14643</pub-id>, <pub-id pub-id-type="pmid">33176022</pub-id></mixed-citation></ref>
<ref id="ref7"><label>7.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>Z</given-names></name> <name><surname>Lin</surname><given-names>Y</given-names></name> <name><surname>Liu</surname><given-names>Y</given-names></name> <name><surname>Chen</surname><given-names>Y</given-names></name> <name><surname>Wang</surname><given-names>B</given-names></name> <name><surname>Li</surname><given-names>C</given-names></name> <etal/></person-group>. <article-title>Serum uric acid levels and outcomes after acute ischemic stroke</article-title>. <source>Mol Neurobiol</source>. (<year>2016</year>) <volume>53</volume>:<fpage>1753</fpage>&#x2013;<lpage>9</lpage>. doi: <pub-id pub-id-type="doi">10.1007/s12035-015-9134-1</pub-id>, <pub-id pub-id-type="pmid">25744569</pub-id></mixed-citation></ref>
<ref id="ref8"><label>8.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>A</given-names></name> <name><surname>Tian</surname><given-names>X</given-names></name> <name><surname>Zuo</surname><given-names>Y</given-names></name> <name><surname>Chen</surname><given-names>S</given-names></name> <name><surname>Mo</surname><given-names>D</given-names></name> <name><surname>Zhang</surname><given-names>L</given-names></name> <etal/></person-group>. <article-title>Effect of changes in serum uric acid on the risk of stroke and its subtypes</article-title>. <source>Nutr Metab Cardiovasc Dis</source>. (<year>2022</year>) <volume>32</volume>:<fpage>167</fpage>&#x2013;<lpage>75</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.numecd.2021.09.017</pub-id>, <pub-id pub-id-type="pmid">34857424</pub-id></mixed-citation></ref>
<ref id="ref9"><label>9.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>X</given-names></name> <name><surname>Huang</surname><given-names>ZC</given-names></name> <name><surname>Lu</surname><given-names>TS</given-names></name> <name><surname>You</surname><given-names>SJ</given-names></name> <name><surname>Cao</surname><given-names>YJ</given-names></name> <name><surname>Liu</surname><given-names>CF</given-names></name></person-group>. <article-title>Prognostic significance of uric acid levels in ischemic stroke patients</article-title>. <source>Neurotox Res</source>. (<year>2016</year>) <volume>29</volume>:<fpage>10</fpage>&#x2013;<lpage>20</lpage>. doi: <pub-id pub-id-type="doi">10.1007/s12640-015-9561-9</pub-id>, <pub-id pub-id-type="pmid">26376636</pub-id></mixed-citation></ref>
<ref id="ref10"><label>10.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Jiang</surname><given-names>Z</given-names></name> <name><surname>Chen</surname><given-names>J</given-names></name> <name><surname>Wu</surname><given-names>S</given-names></name> <name><surname>Ji</surname><given-names>S</given-names></name> <name><surname>Yang</surname><given-names>Y</given-names></name> <name><surname>Fang</surname><given-names>W</given-names></name> <etal/></person-group>. <article-title>Serum uric acid levels associated with outcomes of neurodegenerative disorders and brain health: findings from the UK biobank</article-title>. <source>J Nutr Health Aging</source>. (<year>2024</year>) <volume>28</volume>:<fpage>100319</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jnha.2024.100319</pub-id></mixed-citation></ref>
<ref id="ref11"><label>11.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>P</given-names></name> <name><surname>Wang</surname><given-names>R</given-names></name> <name><surname>Qu</surname><given-names>Y</given-names></name> <name><surname>Guo</surname><given-names>ZN</given-names></name> <name><surname>Zhen</surname><given-names>Q</given-names></name> <name><surname>Yang</surname><given-names>Y</given-names></name></person-group>. <article-title>Serum uric acid levels and outcome of acute ischemic stroke: a dose-response Meta-analysis</article-title>. <source>Mol Neurobiol</source>. (<year>2024</year>) <volume>61</volume>:<fpage>1704</fpage>&#x2013;<lpage>13</lpage>. doi: <pub-id pub-id-type="doi">10.1007/s12035-023-03634-y</pub-id>, <pub-id pub-id-type="pmid">37759105</pub-id></mixed-citation></ref>
<ref id="ref12"><label>12.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wan</surname><given-names>Y</given-names></name> <name><surname>Kang</surname><given-names>Q</given-names></name> <name><surname>Wang</surname><given-names>Y</given-names></name> <name><surname>Lu</surname><given-names>X</given-names></name> <name><surname>Li</surname><given-names>J</given-names></name> <name><surname>Nie</surname><given-names>H</given-names></name> <etal/></person-group>. <article-title>Association of serum uric acid levels with risk of epilepsy: a national population-based study</article-title>. <source>Epilepsy Behav</source>. (<year>2024</year>) <volume>159</volume>:<fpage>109991</fpage>. doi: <pub-id pub-id-type="doi">10.1016/j.yebeh.2024.109991</pub-id>, <pub-id pub-id-type="pmid">39181106</pub-id></mixed-citation></ref>
<ref id="ref13"><label>13.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>M</given-names></name> <name><surname>Wang</surname><given-names>Y</given-names></name> <name><surname>Wang</surname><given-names>K</given-names></name> <name><surname>Yin</surname><given-names>R</given-names></name> <name><surname>Pan</surname><given-names>X</given-names></name> <name><surname>Ma</surname><given-names>A</given-names></name></person-group>. <article-title>Association between uric acid and the prognosis of acute ischemic stroke: a systematic review and meta-analysis</article-title>. <source>Nutr Metab Cardiovasc Dis</source>. (<year>2021</year>) <volume>31</volume>:<fpage>3016</fpage>&#x2013;<lpage>23</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.numecd.2021.07.031</pub-id>, <pub-id pub-id-type="pmid">34625360</pub-id></mixed-citation></ref>
<ref id="ref14"><label>14.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wang</surname><given-names>D</given-names></name> <name><surname>Hu</surname><given-names>B</given-names></name> <name><surname>Dai</surname><given-names>Y</given-names></name> <name><surname>Sun</surname><given-names>J</given-names></name> <name><surname>Liu</surname><given-names>Z</given-names></name> <name><surname>Feng</surname><given-names>Y</given-names></name> <etal/></person-group>. <article-title>Serum uric acid is highly associated with epilepsy secondary to cerebral infarction</article-title>. <source>Neurotox Res</source>. (<year>2019</year>) <volume>35</volume>:<fpage>63</fpage>&#x2013;<lpage>70</lpage>. doi: <pub-id pub-id-type="doi">10.1007/s12640-018-9930-2</pub-id>, <pub-id pub-id-type="pmid">30022372</pub-id></mixed-citation></ref>
<ref id="ref15"><label>15.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Tong</surname><given-names>X</given-names></name> <name><surname>Lyu</surname><given-names>C</given-names></name> <name><surname>Guo</surname><given-names>M</given-names></name> <name><surname>Gu</surname><given-names>J</given-names></name> <name><surname>Zhao</surname><given-names>Y</given-names></name></person-group>. <article-title>Serum uric acid as a predictor of mortality in patients with stroke: results from National Health and nutrition examination survey 2007-2016</article-title>. <source>Front Neurol</source>. (<year>2024</year>) <volume>15</volume>:<fpage>1383300</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fneur.2024.1383300</pub-id>, <pub-id pub-id-type="pmid">38988602</pub-id></mixed-citation></ref>
<ref id="ref16"><label>16.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Fang</surname><given-names>P</given-names></name> <name><surname>Li</surname><given-names>X</given-names></name> <name><surname>Luo</surname><given-names>JJ</given-names></name> <name><surname>Wang</surname><given-names>H</given-names></name> <name><surname>Yang</surname><given-names>XF</given-names></name></person-group>. <article-title>A double-edged sword: uric acid and neurological disorders</article-title>. <source>Brain Disord Ther</source>. (<year>2013</year>) <volume>2</volume>:<fpage>109</fpage>. doi: <pub-id pub-id-type="doi">10.4172/2168-975X.1000109</pub-id>, <pub-id pub-id-type="pmid">24511458</pub-id></mixed-citation></ref>
<ref id="ref17"><label>17.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Liu</surname><given-names>J</given-names></name> <name><surname>He</surname><given-names>H</given-names></name> <name><surname>Wang</surname><given-names>Y</given-names></name> <name><surname>Du</surname><given-names>J</given-names></name> <name><surname>Liang</surname><given-names>K</given-names></name> <name><surname>Xue</surname><given-names>J</given-names></name> <etal/></person-group>. <article-title>Predictive models for secondary epilepsy in patients with acute ischemic stroke within one year</article-title>. <source>eLife</source>. <volume>13</volume>:<fpage>RP98759</fpage>. doi: <pub-id pub-id-type="doi">10.7554/eLife.98759</pub-id></mixed-citation></ref>
<ref id="ref18"><label>18.</label><mixed-citation publication-type="other"><person-group person-group-type="author"><name><surname>Boussiala</surname><given-names>M.</given-names></name></person-group> <source>Applied linear statistical models</source>. <publisher-loc>New York</publisher-loc>: <publisher-name>McGraw-Hill Press</publisher-name>. (<year>2020</year>).</mixed-citation></ref>
<ref id="ref19"><label>19.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Lusa</surname><given-names>L</given-names></name> <name><surname>Ahlin</surname><given-names>C</given-names></name></person-group>. <article-title>Restricted cubic splines for modelling periodic data</article-title>. <source>PLoS One</source>. (<year>2020</year>) <volume>15</volume>:<fpage>e0241364</fpage>. doi: <pub-id pub-id-type="doi">10.1371/journal.pone.0241364</pub-id>, <pub-id pub-id-type="pmid">33112926</pub-id></mixed-citation></ref>
<ref id="ref20"><label>20.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ho</surname><given-names>DE</given-names></name> <name><surname>Imai</surname><given-names>K</given-names></name> <name><surname>King</surname><given-names>G</given-names></name> <name><surname>Stuart</surname><given-names>EA</given-names></name></person-group>. <article-title>MatchIt: nonparametric preprocessing for parametric causal inference</article-title>. <source>J Stat Softw</source>. (<year>2011</year>) <volume>42</volume>:<fpage>1</fpage>&#x2013;<lpage>28</lpage>. doi: <pub-id pub-id-type="doi">10.18637/jss.v042.i08</pub-id></mixed-citation></ref>
<ref id="ref21"><label>21.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Austin</surname><given-names>PC</given-names></name></person-group>. <article-title>Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies</article-title>. <source>Pharm Stat</source>. (<year>2011</year>) <volume>10</volume>:<fpage>150</fpage>&#x2013;<lpage>61</lpage>. doi: <pub-id pub-id-type="doi">10.1002/pst.433</pub-id>, <pub-id pub-id-type="pmid">20925139</pub-id></mixed-citation></ref>
<ref id="ref22"><label>22.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Herman</surname><given-names>ST</given-names></name> <name><surname>Abend</surname><given-names>NS</given-names></name> <name><surname>Bleck</surname><given-names>TP</given-names></name> <name><surname>Chapman</surname><given-names>KE</given-names></name> <name><surname>Drislane</surname><given-names>FW</given-names></name> <name><surname>Emerson</surname><given-names>RG</given-names></name> <etal/></person-group>. <article-title>Consensus statement on continuous EEG in critically ill adults and children, part I: indications</article-title>. <source>J Clin Neurophysiol</source>. (<year>2015</year>) <volume>32</volume>:<fpage>87</fpage>&#x2013;<lpage>95</lpage>. doi: <pub-id pub-id-type="doi">10.1097/wnp.0000000000000166</pub-id>, <pub-id pub-id-type="pmid">25626778</pub-id></mixed-citation></ref>
<ref id="ref23"><label>23.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Bobulescu</surname><given-names>IA</given-names></name> <name><surname>Moe</surname><given-names>OW</given-names></name></person-group>. <article-title>Renal transport of uric acid: evolving concepts and uncertainties</article-title>. <source>Adv Chronic Kidney Dis</source>. (<year>2012</year>) <volume>19</volume>:<fpage>358</fpage>&#x2013;<lpage>71</lpage>. doi: <pub-id pub-id-type="doi">10.1053/j.ackd.2012.07.009</pub-id>, <pub-id pub-id-type="pmid">23089270</pub-id></mixed-citation></ref>
<ref id="ref24"><label>24.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mandal</surname><given-names>AK</given-names></name> <name><surname>Mount</surname><given-names>DB</given-names></name></person-group>. <article-title>The molecular physiology of uric acid homeostasis</article-title>. <source>Annu Rev Physiol</source>. (<year>2015</year>) <volume>77</volume>:<fpage>323</fpage>&#x2013;<lpage>45</lpage>. doi: <pub-id pub-id-type="doi">10.1146/annurev-physiol-021113-170343</pub-id></mixed-citation></ref>
<ref id="ref25"><label>25.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Wu</surname><given-names>SH</given-names></name> <name><surname>Shu</surname><given-names>XO</given-names></name> <name><surname>Milne</surname><given-names>G</given-names></name> <name><surname>Xiang</surname><given-names>YB</given-names></name> <name><surname>Zhang</surname><given-names>X</given-names></name> <name><surname>Cai</surname><given-names>Q</given-names></name> <etal/></person-group>. <article-title>Uric acid correlates to oxidation and inflammation in opposite directions in women</article-title>. <source>Biomarkers</source>. (<year>2015</year>) <volume>20</volume>:<fpage>225</fpage>&#x2013;<lpage>31</lpage>. doi: <pub-id pub-id-type="doi">10.3109/1354750X.2015.1068852</pub-id>, <pub-id pub-id-type="pmid">26301880</pub-id></mixed-citation></ref>
<ref id="ref26"><label>26.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Glantzounis</surname><given-names>GK</given-names></name> <name><surname>Tsimoyiannis</surname><given-names>EC</given-names></name> <name><surname>Kappas</surname><given-names>AM</given-names></name> <name><surname>Galaris</surname><given-names>DA</given-names></name></person-group>. <article-title>Uric acid and oxidative stress</article-title>. <source>Curr Pharm Des</source>. (<year>2005</year>) <volume>11</volume>:<fpage>4145</fpage>&#x2013;<lpage>51</lpage>. doi: <pub-id pub-id-type="doi">10.2174/138161205774913255</pub-id></mixed-citation></ref>
<ref id="ref27"><label>27.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Ames</surname><given-names>BN</given-names></name> <name><surname>Cathcart</surname><given-names>R</given-names></name> <name><surname>Schwiers</surname><given-names>E</given-names></name> <name><surname>Hochstein</surname><given-names>P</given-names></name></person-group>. <article-title>Uric acid provides an antioxidant defense in humans against oxidant- and radical-caused aging and cancer: a hypothesis</article-title>. <source>Proc Natl Acad Sci USA</source>. (<year>1981</year>) <volume>78</volume>:<fpage>6858</fpage>&#x2013;<lpage>62</lpage>. doi: <pub-id pub-id-type="doi">10.1073/pnas.78.11.6858</pub-id>, <pub-id pub-id-type="pmid">6947260</pub-id></mixed-citation></ref>
<ref id="ref28"><label>28.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Otani</surname><given-names>N</given-names></name> <name><surname>Hoshiyama</surname><given-names>E</given-names></name> <name><surname>Ouchi</surname><given-names>M</given-names></name> <name><surname>Takekawa</surname><given-names>H</given-names></name> <name><surname>Suzuki</surname><given-names>K</given-names></name></person-group>. <article-title>Uric acid and neurological disease: a narrative review</article-title>. <source>Front Neurol</source>. (<year>2023</year>) <volume>14</volume>. <comment>1664-2295 (Print)</comment>:<fpage>1164756</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fneur.2023.1164756</pub-id>, <pub-id pub-id-type="pmid">37333005</pub-id></mixed-citation></ref>
<ref id="ref29"><label>29.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Martinon</surname><given-names>F</given-names></name> <name><surname>Petrilli</surname><given-names>V</given-names></name> <name><surname>Mayor</surname><given-names>A</given-names></name> <name><surname>Tardivel</surname><given-names>A</given-names></name> <name><surname>Tschopp</surname><given-names>J</given-names></name></person-group>. <article-title>Gout-associated uric acid crystals activate the NALP3 inflammasome</article-title>. <source>Nature</source>. (<year>2006</year>) <volume>440</volume>:<fpage>237</fpage>&#x2013;<lpage>41</lpage>. doi: <pub-id pub-id-type="doi">10.1038/nature04516</pub-id>, <pub-id pub-id-type="pmid">16407889</pub-id></mixed-citation></ref>
<ref id="ref30"><label>30.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Semple</surname><given-names>BD</given-names></name> <name><surname>Dill</surname><given-names>LK</given-names></name> <name><surname>O'brien</surname><given-names>TJ</given-names></name></person-group>. <article-title>Immune challenges and seizures: how do early life insults influence epileptogenesis?</article-title> <source>Front Pharmacol</source>. (<year>2020</year>) <volume>11</volume>:<fpage>2</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fphar.2020.00002</pub-id>, <pub-id pub-id-type="pmid">32116690</pub-id></mixed-citation></ref>
<ref id="ref31"><label>31.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Frigerio</surname><given-names>F</given-names></name> <name><surname>Pasqualini</surname><given-names>G</given-names></name> <name><surname>Craparotta</surname><given-names>I</given-names></name> <name><surname>Marchini</surname><given-names>S</given-names></name> <name><surname>Van Vliet</surname><given-names>EA</given-names></name> <name><surname>Foerch</surname><given-names>P</given-names></name> <etal/></person-group>. <article-title>N-3 docosapentaenoic acid-derived protectin D1 promotes resolution of neuroinflammation and arrests epileptogenesis</article-title>. <source>Brain</source>. (<year>2018</year>) <volume>141</volume>:<fpage>3130</fpage>&#x2013;<lpage>43</lpage>. doi: <pub-id pub-id-type="doi">10.1093/brain/awy247</pub-id>, <pub-id pub-id-type="pmid">30307467</pub-id></mixed-citation></ref>
<ref id="ref32"><label>32.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Misra</surname><given-names>S</given-names></name> <name><surname>Khan</surname><given-names>EI</given-names></name> <name><surname>Lam</surname><given-names>TT</given-names></name> <name><surname>Mazumder</surname><given-names>R</given-names></name> <name><surname>Gururangan</surname><given-names>K</given-names></name> <name><surname>Hickman</surname><given-names>LB</given-names></name> <etal/></person-group>. <article-title>Common pathways of epileptogenesis in patients with epilepsy post-brain injury: findings from a systematic review and Meta-analysis</article-title>. <source>Neurology</source>. (<year>2023</year>) <volume>101</volume>:<fpage>e2243</fpage>&#x2013;<lpage>56</lpage>. doi: <pub-id pub-id-type="doi">10.1212/WNL.0000000000207749</pub-id>, <pub-id pub-id-type="pmid">37550071</pub-id></mixed-citation></ref>
<ref id="ref33"><label>33.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chamorro</surname><given-names>A</given-names></name> <name><surname>Obach</surname><given-names>V</given-names></name> <name><surname>Cervera</surname><given-names>A</given-names></name> <name><surname>Revilla</surname><given-names>M</given-names></name> <name><surname>Deulofeu</surname><given-names>R</given-names></name> <name><surname>Aponte</surname><given-names>JH</given-names></name></person-group>. <article-title>Prognostic significance of uric acid serum concentration in patients with acute ischemic stroke</article-title>. <source>Stroke</source>. (<year>2002</year>) <volume>33</volume>:<fpage>1048</fpage>&#x2013;<lpage>52</lpage>. doi: <pub-id pub-id-type="doi">10.1161/hs0402.105927</pub-id>, <pub-id pub-id-type="pmid">11935059</pub-id></mixed-citation></ref>
<ref id="ref34"><label>34.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>&#x015E;eng&#x00FC;ld&#x00FC;r</surname><given-names>E</given-names></name> <name><surname>Demir</surname><given-names>MC</given-names></name> <name><surname>Selki</surname><given-names>K</given-names></name></person-group>. <article-title>Prevalence and clinical significance of hypouricemia in the emergency department</article-title>. <source>Medicine (Baltimore)</source>. (<year>2024</year>) <volume>103</volume>:<fpage>e41105</fpage>. doi: <pub-id pub-id-type="doi">10.1097/md.0000000000041105</pub-id>, <pub-id pub-id-type="pmid">39969343</pub-id></mixed-citation></ref>
<ref id="ref35"><label>35.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Mehta</surname><given-names>A</given-names></name> <name><surname>Prabhakar</surname><given-names>M</given-names></name> <name><surname>Kumar</surname><given-names>P</given-names></name> <name><surname>Deshmukh</surname><given-names>R</given-names></name> <name><surname>Sharma</surname><given-names>PL</given-names></name></person-group>. <article-title>Excitotoxicity: bridge to various triggers in neurodegenerative disorders</article-title>. <source>Eur J Pharmacol</source>. (<year>2013</year>) <volume>698</volume>:<fpage>6</fpage>&#x2013;<lpage>18</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.ejphar.2012.10.032</pub-id>, <pub-id pub-id-type="pmid">23123057</pub-id></mixed-citation></ref>
<ref id="ref36"><label>36.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Armada-Moreira</surname><given-names>A</given-names></name> <name><surname>Gomes</surname><given-names>JI</given-names></name> <name><surname>Pina</surname><given-names>CC</given-names></name> <name><surname>Savchak</surname><given-names>OK</given-names></name> <name><surname>Goncalves-Ribeiro</surname><given-names>J</given-names></name> <name><surname>Rei</surname><given-names>N</given-names></name> <etal/></person-group>. <article-title>Going the extra (synaptic) mile: excitotoxicity as the road toward neurodegenerative diseases</article-title>. <source>Front Cell Neurosci</source>. (<year>2020</year>) <volume>14</volume>:<fpage>90</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fncel.2020.00090</pub-id>, <pub-id pub-id-type="pmid">32390802</pub-id></mixed-citation></ref>
<ref id="ref37"><label>37.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>&#x015E;eng&#x00FC;ld&#x00FC;r</surname><given-names>E</given-names></name> <name><surname>Demir</surname><given-names>MC</given-names></name></person-group>. <article-title>Evaluation of the association of serum uric acid levels and stroke in emergency department patients</article-title>. <source>Duzce Med J</source>. (<year>2024</year>) <volume>26</volume>:<fpage>112</fpage>&#x2013;<lpage>7</lpage>. doi: <pub-id pub-id-type="doi">10.18678/dtfd.1457023</pub-id></mixed-citation></ref>
<ref id="ref38"><label>38.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Chamorro</surname><given-names>A</given-names></name> <name><surname>Amaro</surname><given-names>S</given-names></name> <name><surname>Castellanos</surname><given-names>M</given-names></name> <name><surname>Gomis</surname><given-names>M</given-names></name> <name><surname>Urra</surname><given-names>X</given-names></name> <name><surname>Blasco</surname><given-names>J</given-names></name> <etal/></person-group>. <article-title>Uric acid therapy improves the outcomes of stroke patients treated with intravenous tissue plasminogen activator and mechanical thrombectomy</article-title>. <source>Int J Stroke</source>. (<year>2017</year>) <volume>12</volume>:<fpage>377</fpage>&#x2013;<lpage>82</lpage>. doi: <pub-id pub-id-type="doi">10.1177/1747493016684354</pub-id>, <pub-id pub-id-type="pmid">28345429</pub-id></mixed-citation></ref>
<ref id="ref39"><label>39.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Dhanesha</surname><given-names>N</given-names></name> <name><surname>Vazquez-Rosa</surname><given-names>E</given-names></name> <name><surname>Cintron-Perez</surname><given-names>CJ</given-names></name> <name><surname>Thedens</surname><given-names>D</given-names></name> <name><surname>Kort</surname><given-names>AJ</given-names></name> <name><surname>Chuong</surname><given-names>V</given-names></name> <etal/></person-group>. <article-title>Treatment with uric acid reduces infarct and improves neurologic function in female mice after transient cerebral ischemia</article-title>. <source>J Stroke Cerebrovasc Dis</source>. (<year>2018</year>) <volume>27</volume>:<fpage>1412</fpage>&#x2013;<lpage>6</lpage>. doi: <pub-id pub-id-type="doi">10.1016/j.jstrokecerebrovasdis.2017.12.043</pub-id>, <pub-id pub-id-type="pmid">29398531</pub-id></mixed-citation></ref>
<ref id="ref40"><label>40.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Zhang</surname><given-names>W</given-names></name> <name><surname>Cheng</surname><given-names>Z</given-names></name> <name><surname>Fu</surname><given-names>F</given-names></name> <name><surname>Zhan</surname><given-names>Z</given-names></name></person-group>. <article-title>Serum uric acid and prognosis in acute ischemic stroke: a dose-response meta-analysis of cohort studies</article-title>. <source>Front Aging Neurosci</source>. (<year>2023</year>) <volume>15</volume>:<fpage>1223015</fpage>. doi: <pub-id pub-id-type="doi">10.3389/fnagi.2023.1223015</pub-id>, <pub-id pub-id-type="pmid">37727320</pub-id></mixed-citation></ref>
<ref id="ref41"><label>41.</label><mixed-citation publication-type="journal"><person-group person-group-type="author"><name><surname>Weir</surname><given-names>CJ</given-names></name> <name><surname>Muir</surname><given-names>SW</given-names></name> <name><surname>Walters</surname><given-names>MR</given-names></name> <name><surname>Lees</surname><given-names>KR</given-names></name></person-group>. <article-title>Serum urate as an independent predictor of poor outcome and future vascular events after acute stroke</article-title>. <source>Stroke</source>. (<year>2003</year>) <volume>34</volume>:<fpage>1951</fpage>&#x2013;<lpage>6</lpage>. doi: <pub-id pub-id-type="doi">10.1161/01.STR.0000081983.34771.D2</pub-id></mixed-citation></ref>
</ref-list>
<fn-group>
<fn fn-type="custom" custom-type="edited-by" id="fn0003">
<p>Edited by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/659849/overview">Arjune Sen</ext-link>, University of Oxford, United Kingdom</p>
</fn>
<fn fn-type="custom" custom-type="reviewed-by" id="fn0004">
<p>Reviewed by: <ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/337064/overview">Hip&#x00F3;lito Nzwalo</ext-link>, University of Algarve, Portugal</p>
<p><ext-link ext-link-type="uri" xlink:href="https://loop.frontiersin.org/people/2043885/overview">Mehmet Cihat Demir</ext-link>, Duzce University, T&#x00FC;rkiye</p>
</fn>
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<fn-group>
<fn id="fn0001">
<label>1</label>
<p><ext-link xlink:href="https://doi.org/10.5061/dryad.w0vt4b92c" ext-link-type="uri">https://doi.org/10.5061/dryad.w0vt4b92c</ext-link></p>
</fn>
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