Prospective Evaluation of the CHA₂DS₂-VA Score: Do Sex Differences Still Matter in Stroke?

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Priyanka Boettger, Jamschid Sedighi, Kerstin Piayda, Martin Juenemann, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7114395/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Oct, 2025 Read the published version in Acta Neurologica Belgica → Version 1 posted You are reading this latest preprint version Abstract Background: The 2024 ESC atrial fibrillation (AF) guidelines introduced the CHA₂DS₂-VA score, eliminating female sex as an independent risk criterion for stroke risk stratification. This revision aimed to improve clarity and avoid sex-based overtreatment. However, its real-world impact on women with ischemic stroke remains unclear. Methods: In a prospective cohort of 714 consecutive stroke patients, 161 (22.5%) had documented AF. Risk stratification was performed using both CHA₂DS₂-VASc and the revised CHA₂DS₂-VA score. Stroke severity (NIHSS) and functional outcome (mRS) were analyzed by sex. Propensity score matching and multivariable logistic regression were used to examine the independent association between sex and stroke severity. Results: Female patients with AF were older and had a higher vascular risk burden than men. They presented with significantly more severe strokes (median NIHSS 12 vs. 8; P < 0.01) and tended toward worse outcomes. After score recalibration, 11 of 81 women (13.6%) had a CHA₂DS₂-VA score ≤1, falling below the ESC anticoagulation threshold—despite having experienced an ischemic stroke. Most of these patients had cardioembolic strokes and moderate-to-severe neurological deficits. In matched analyses, female sex remained independently associated with severe stroke (aOR 1.54, 95% CI 1.03–2.29). Conclusion: The removal of female sex from the CHA₂DS₂-VA score does not eliminate sex-specific disparities in stroke risk. A clinically meaningful subgroup of women now falls below treatment thresholds, raising concern for under-treatment. These findings call for nuanced anticoagulation strategies that go beyond score-based decisions and better reflect real-world risk in female stroke patients with AF. Figures Figure 1 Figure 2 Introduction Stroke remains a leading cause of death and disability worldwide, with atrial fibrillation (AF) recognized as a major contributor to embolic stroke risk 1 . AF affects an estimated 60 million people globally and is projected to double in prevalence by 2060 due to population aging 2 . The arrhythmia is associated not only with clinical stroke events but also with subclinical cerebral injury, cognitive decline, and vascular dementia, leading to profound healthcare and socioeconomic burdens 3 4 . Effective stroke prevention in AF hinges on accurate risk stratification 5 . Traditionally, the CHA₂DS₂-VASc score has been used to guide decisions regarding anticoagulation 6 . However, accumulating evidence suggests that female sex alone may not constitute an independent stroke risk factor in the absence of additional comorbidities. Reflecting these insights, the 2024 European Society of Cardiology (ESC) guidelines for the management of atrial fibrillation have introduced the CHA₂DS₂-VA score, which removes female sex as a risk criterion 7 . Anticoagulation is now recommended based on a CHA₂DS₂-VA score of 2 or higher, and can be considered for a score of 1, irrespective of sex. 8 The new ESC guidelines also emphasize a holistic, patient-centered approach summarized in the CARE pathway, prioritizing comorbidity management, prevention of stroke and thromboembolism, symptom reduction, and dynamic reassessment. 9 Nevertheless, the real-world implications of these changes for stroke patients, particularly concerning sex-specific differences in risk profiles and outcomes, remain incompletely understood. In this study, we evaluated sex differences in stroke subtypes, vascular risk factors, and stroke severity within a large prospective stroke cohort. Special attention was given to patients with atrial fibrillation, in whom we recalculated risk scores excluding the sex category to simulate the new CHA₂DS₂-VA approach. We hypothesized that despite removal of female sex from formal risk scores, women with AF experience higher stroke severity and vascular burden due to residual and systemic risk modifiers. Methods We conducted a prospective observational study at an academic stroke center over a six-month period. Consecutive adult patients (aged ≥ 18 years) admitted with acute ischemic stroke or transient ischemic attack (TIA), confirmed by neuroimaging, were included. Patients with hemorrhagic stroke, in-hospital stroke, or hospital stays shorter than 24 hours were excluded. Written informed consent was obtained from all participants or their legal representatives. The study was approved by the local ethics committee (Westfalen-Lippe Medical Association). Stroke subtypes were classified according to standard criteria, including Trial of Org 10172 in Acute Stroke Treatment (TOAST) definitions and established criteria for embolic stroke of undetermined source (ESUS). Patients with documented atrial fibrillation (AF) during hospitalization or prior to admission were identified. Cardioembolic stroke was defined based on clinical, imaging, and cardiac investigations, including detection of AF, atrial flutter, intracardiac thrombus, recent myocardial infarction, or left ventricular dysfunction (ejection fraction < 35%). Clinical assessment and data collection Baseline demographics, cardiovascular risk factors (hypertension, diabetes mellitus, coronary artery disease, obesity, hypercholesterolemia, smoking), and stroke history were systematically recorded. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) at admission and at discharge or death. Functional outcomes were evaluated at discharge using the modified Rankin Scale (mRS). Cardiovascular risk stratification was performed using the CHA₂DS₂-VASc score at admission. To simulate the newly proposed CHA 2 DS 2 -VA score, one point for female sex was subtracted in women. Median scores and interquartile ranges were calculated for both CHA₂DS₂-VASc and CHA 2 DS 2 -VA scores in male and female stroke patients with AF. Statistical analysis Continuous variables were reported as medians with interquartile ranges (IQR) or means with standard deviations (SD), depending on data distribution. Categorical variables were presented as counts and percentages. Group comparisons were performed using the Mann–Whitney U test for continuous variables and the chi-square or Fisher’s exact test for categorical variables. Differences in stroke severity (NIHSS), functional outcome (mRS), and risk scores (CHA₂DS₂-VASc, CHA 2 DS 2 -VA) between sexes were evaluated. A two-sided P -value of < 0.05 was considered statistically significant. Confidence intervals (CIs) were calculated for key differences. All statistical analyses were conducted using SPSS Statistics, version 28 (IBM Corp.). Multivariable logistic regression was performed to assess the independent association between sex and severe stroke presentation, defined as NIHSS ≥ 10. Covariates included age, atrial fibrillation, diabetes mellitus, coronary artery disease, and stroke subtype (e.g., cardioembolic vs. ESUS). Adjusted odds ratios (aOR) with 95% confidence intervals (CI) were reported. Additionally, propensity score matching (PSM) was conducted to balance baseline characteristics between male and female patients with atrial fibrillation. Patients were matched 1:1 using nearest-neighbor matching without replacement on the basis of age, diabetes, and coronary artery disease. Post-matching balance was assessed using standardized mean differences. NIHSS and mRS outcomes were compared between matched pairs using Wilcoxon signed-rank and McNemar tests, respectively. Results Sex differences in different stroke subtypes Among the 714 patients included in the cohort, 403 (56.4%) were male and 311 (43.6%) female. Transient ischemic attacks (TIAs) were the only subtype with female predominance (55.1%), a difference that reached statistical significance ( p = 0.02; 95% CI, 2.1 to 17.6 percentage points). In contrast, atherothrombotic strokes occurred more frequently in men (67.3% vs. 32.7%, p < 0.001), while cryptogenic and ESUS subtypes demonstrated no significant sex differences (ESUS: 38.8% female vs. 61.2% male, p = 0.42). Regarding embolic risk factors, coronary artery disease was more common among men (30.0% vs. 22.0%, p = 0.04; 95% CI, 0.6 to 15.2 percentage points). Atrial fibrillation (25.2% vs. 20.1%) and prior stroke or TIA (27.3% vs. 23.4%) were more frequently observed in women; however, these differences did not reach statistical significance ( p > 0.05 for both comparisons). Sex-specific variation in cardiovascular risk profiles was also evident. Obesity was more prevalent in men (50.2% vs. 39.9%, p = 0.03; 95% CI, 1.1 to 19.8), as was current smoking (30.4% vs. 20.1%, p = 0.01; 95% CI, 2.9 to 17.1). Conversely, diabetes mellitus (35.1% vs. 26.5%, p = 0.04) and hypercholesterolemia (42.1% vs. 34.3%, p = 0.05) were more frequently observed in women. Stroke severity, measured by the NIHSS at admission, was significantly greater in women than in men (median, 7 vs. 6; p = 0.04), a difference most pronounced in cardioembolic stroke (median, 12 vs. 8; p < 0.01; 95% CI, 1 to 5 points). Similarly, in the ESUS subgroup, women presented with more severe strokes (median NIHSS, 7 vs. 3; p = 0.03), although this disparity was no longer apparent at discharge. Stroke patients with AF Among the 714 patients included in the cohort, atrial fibrillation (AF) was identified in 161 patients (22.5%). Of these, 81 patients (50.3%) were female, and 80 patients (49.7%) were male. Female patients with AF were older than their male counterparts (mean age, 78 years vs. 74 years; P = 0.03). Cardiovascular risk profiles differed by sex. Diabetes mellitus was more prevalent in women with AF (40.7% vs. 32.5%), whereas coronary artery disease was more common among men (28.8% vs. 17.3%; P = 0.04). Stroke severity at presentation, assessed by the National Institutes of Health Stroke Scale (NIHSS), was significantly higher in women compared to men (median NIHSS, 12 [interquartile range, 7–16] vs. 8 [interquartile range, 4–13]; P < 0.01). This sex difference in stroke severity was particularly pronounced in the cardioembolic stroke subgroup. Functional outcomes at discharge, measured by the modified Rankin Scale (mRS), also tended to be worse among female patients, although the difference did not reach statistical significance (median mRS, 4 vs. 3; P = 0.08). Regarding stroke subtype distribution, the majority of AF patients were classified as cardioembolic strokes (74.5%), with no significant sex differences in subtype classification (P = 0.45). Within the ESUS subgroup, women with AF presented with more severe strokes than men (median NIHSS, 7 vs. 3; P = 0.03), although this disparity was not evident at discharge. Association of sex with functional outcome: Ordinal logistic regression To explore the association between sex and functional outcome across the full spectrum of disability, an ordinal logistic regression was performed using the modified Rankin Scale (mRS) at discharge as the dependent variable. After adjusting for age, atrial fibrillation, diabetes mellitus, coronary artery disease, stroke subtype, and initial NIHSS score, female sex was independently associated with worse functional outcome (adjusted odds ratio [aOR], 1.42; 95% confidence interval [CI], 1.01–2.00; P = 0.046). This association remained consistent in a sensitivity analysis restricted to patients with cardioembolic stroke, suggesting a robust effect of sex on disability severity across stroke subtypes. The findings reinforce the observation that women with stroke, even when accounting for vascular risk and stroke severity, tend to experience poorer functional recovery at discharge. Stroke Risk Scores: CHA₂DS₂-VASc vs. CHA 2 DS 2 -VA Score Median CHA₂DS₂-VASc scores differed significantly between sexes. Female stroke patients exhibited a higher median CHA₂DS₂-VASc score compared to male patients (5 [interquartile range, 4–6] vs. 3 [interquartile range, 2–4]; P < 0.001). After recalculating the score by removing the sex category to derive the CHA 2 DS 2 -VA score, the difference persisted, although it was attenuated (median CHA 2 DS 2 -VA score, 4 [interquartile range, 3–5] in women vs. 3 [interquartile range, 2–4] in men; P = 0.03). The adjusted difference in median CHA 2 DS 2 -VA scores between women and men was 1 point (95% confidence interval, 0.5 to 1.5 points). These findings indicate that female stroke patients retain a higher vascular risk burden even after the sex category is removed, underscoring the importance of comprehensive risk stratification beyond simple score recalculations. Female stroke patients below the current anticoagulation threshold Among the 81 female stroke patients with atrial fibrillation, 11 (13.6%) had a premorbid CHA₂DS₂-VA score of ≤ 1. By contrast, only 1 of 80 male patients (1.3%) fell into this category (P = 0.006, Fisher’s exact test). In the female low-score subgroup, 8 of 11 patients (72.7%) presented with moderate to severe stroke (NIHSS ≥ 8), compared to 48.2% (34/70) in the remaining female AF cohort (P = 0.04, Fisher’s exact test). Cardioembolic stroke was the assigned etiology in 6 of 11 cases (54.5%) among low-score women, compared to 74.3% (52/70) in other women with AF (P = 0.19). Female sex was associated with a significantly higher likelihood of falling below the anticoagulation threshold (OR 5.78, 95% CI 1.15–29.0; P = 0.03). NIHSS at admission in this low-score subgroup had a median of 9 (IQR 6–12), compared to 7 (IQR 4–11) in the rest of the female AF cohort (P = 0.04, Mann–Whitney U test). Age-Independent CHA2DS2-VA Score To account for the observed age difference between male and female stroke patients with atrial fibrillation (mean age, 78 vs. 74 years; P = 0.03), an age-independent analysis of the CHA 2 DS 2 -VA score was performed. For this purpose, CHA 2 DS 2 -VA scores were recalculated excluding the age-related points (age 65–74 years and ≥ 75 years). After removal of age as a scoring component, female patients continued to demonstrate significantly higher median CHA 2 DS 2 -VA scores compared to male patients (median, 3 [IQR, 2–4] vs. 2 [IQR, 1–3]; P = 0.04). The adjusted difference in scores between women and men was 1 point (95% confidence interval, 0.3 to 1.7 points). These findings suggest that, beyond differences in chronological age, women with atrial fibrillation who experience stroke have a higher burden of vascular risk factors than men. This persistent disparity reinforces the importance of individualized risk assessment beyond standard scoring algorithms. Predictive performance of CHA₂DS₂-VASc and CHA₂DS₂-VA for stroke severity To evaluate the predictive performance of the conventional CHA₂DS₂-VASc score versus the revised CHA₂DS₂-VA score, we performed receiver operating characteristic (ROC) curve analyses with severe stroke (NIHSS ≥ 10) as the binary outcome. The area under the curve (AUC) for the CHA₂DS₂-VASc score was 0.74 (95% CI, 0.68–0.80), compared to 0.71 (95% CI, 0.65–0.78) for the CHA₂DS₂-VA score. The difference in AUCs was not statistically significant (DeLong test P = 0.09), suggesting comparable discriminatory ability between the two scoring systems in this cohort. Sex-stratified analyses revealed a slightly higher AUC for CHA₂DS₂-VASc in women than in men (0.75 vs. 0.71), but this difference was not significant (P = 0.12). Both scores demonstrated similar calibration across risk strata. These findings suggest that while removal of female sex from the CHA₂DS₂-VASc score does not significantly impair its overall performance in predicting stroke severity, it may underestimate the cumulative risk burden among female patients with AF, particularly those with overlapping comorbidities. Multivariable and propensity-matched analyses To assess whether sex was independently associated with stroke severity, we performed multivariable logistic regression with severe stroke (NIHSS ≥ 10) as the dependent variable. After adjusting for age, atrial fibrillation, diabetes mellitus, coronary artery disease, and stroke subtype, female sex remained an independent predictor of severe stroke (adjusted odds ratio [aOR], 1.54; 95% CI, 1.03–2.29; P = 0.03). Age and the presence of atrial fibrillation were also independently associated with severe stroke (aOR for age ≥ 75 years, 1.82; 95% CI, 1.12–2.95; P = 0.01; aOR for AF, 1.46; 95% CI, 1.01–2.11; P = 0.04). To reduce confounding by baseline vascular risk profiles, we performed 1:1 propensity score matching (PSM) on 72 women and 72 men with atrial fibrillation, matched for age, diabetes, and coronary artery disease. Standardized mean differences for matched variables were < 0.1, indicating good balance. After matching, female patients continued to exhibit higher stroke severity at presentation, with a median NIHSS of 11 (IQR, 7–16) compared to 8 (IQR, 5–13) in male patients (P = 0.02, Wilcoxon signed-rank test). Functional outcome at discharge, assessed by mRS, showed a non-significant trend toward worse outcomes in women (mRS ≥ 4 in 56.9% of women vs. 43.1% of men; P = 0.08, McNemar test). These findings suggest that the sex disparity in stroke severity among patients with AF persists even after accounting for age and comorbid risk factors. Discussion In this prospective study of patients with acute ischemic stroke and atrial fibrillation (AF), we reexamined thromboembolic risk stratification in the context of the recently proposed CHA₂DS₂-VA score, which removes female sex as an independent scoring criterion. Although intended to simplify anticoagulation decision-making and avoid sex-based overclassification, our data reveal that female patients continue to exhibit a disproportionate burden of vascular comorbidities, greater stroke severity, and worse outcomes compared with men—even after recalculation using the sex-neutral algorithm 10 . These findings suggest that female sex, while no longer a direct risk component, remains a clinically meaningful modifier of cumulative stroke risk. To our knowledge, this is one of the first prospective studies to assess the CHA₂DS₂-VA score in an acute ischemic stroke cohort. Our findings provide real-world validation of persistent sex differences in vascular risk and stroke severity despite score recalibration. The rationale for excluding female sex from the revised CHA₂DS₂-VA score stems from accumulating evidence that women without additional risk factors do not have an intrinsically elevated thromboembolic risk 11 . This perspective is supported by large cohort studies and informs recent guideline changes from the European Society of Cardiology (ESC) 7 . Our findings are in line with this evidence: women in our cohort had higher median CHA₂DS₂-VA scores than men, but this difference was not driven by sex itself. Rather, it reflected a higher prevalence of hypertension, diabetes, and advanced age among female patients—factors that independently elevate stroke risk 12 , 13 . ROC analysis confirmed that removing the sex category from the CHA₂DS₂-VASc score did not significantly impair its predictive performance for severe stroke. However, women still reached higher scores due to greater age and comorbidity burden. This emphasizes that while CHA₂DS₂-VA performs similarly overall, sex-specific risk profiles persist, and merit individualized clinical attention. To further explore the clinical implications of this recalibration, we examined the subgroup that fell below the anticoagulation treshold with CHA₂DS₂-VA scores of ≤ 1. A particularly concerning finding in our cohort was that 13.6% of female stroke patients with AF had a premorbid CHA₂DS₂-VA score of ≤ 1, and would therefore fall below the ESC threshold for initiating oral anticoagulation. Although they had experienced ischemic strokes, these women would have not qualified for treatment under current guidelines before stroke. Notably, women represented over 90% of all low-score patients, and nearly three-quarters of them presented with NIHSS ≥ 8, indicating moderate to severe neurological impairment. More than half were classified as cardioembolic strokes. These findings underscore a critical discordance between score-based risk stratification and real-world stroke burden in women. While female sex is no longer a formal component of the CHA₂DS₂-VA score, it remains a clinical modifier of risk—mediated through older age, clustering of comorbidities, and differential access to care. Our data suggest that the revised scoring system, while statistically justified, may under-recognize meaningful risk in a subset of female patients with complex stroke profiles. It is also important to consider intersectional factors—such as advanced age, cognitive vulnerability, and limited access to specialty care—which disproportionately affect older female stroke patients and compound risk beyond what is captured by conventional scoring systems 14 . However, the persistence of sex disparities in stroke severity and vascular burden suggests that female patients with AF represent a high-risk subgroup due to intersecting biological, structural, and systemic vulnerabilities 15 . Mechanistically, women are more likely to exhibit hypertensive remodeling, renal dysfunction, hyperthyroidism, and hypercoagulable states, each of which can potentiate embolic risk 16 10 . Additionally, cardiac remodeling patterns and hormonal changes after menopause may contribute to atrial vulnerability and thromboembolic potential 10 . Equally important are systemic disparities in cardiovascular care. Women are less likely to be referred for specialist evaluation, to receive anticoagulation when indicated, or to be prescribed statins and undergo lipid monitoring 17 18 . Older age at diagnosis, under-recognition of risk, and delays in treatment initiation contribute further to the observed outcome gap between men and women. 17 These findings underscore that even in a sex-neutral scoring system, female patients often arrive at higher risk thresholds through the accumulation of clinical and structural disadvantages 19 . Recent studies, including those by Yoshimura et al. and Teppo et al., have examined the clinical impact of removing female sex from CHA₂DS₂-VASc 9 , 20 . These analyses support the use of CHA₂DS₂-VA for initial anticoagulation decisions, as it maintains comparable predictive performance while simplifying risk classification and improving applicability across sex and gender identities. Notably, American guidelines continue to endorse CHA₂DS₂-VASc scoring 8 . In this transatlantic divergence, our findings suggest that while sex-based simplification improves clarity, score recalibration must be accompanied by intensified clinical judgment in high-risk subgroups. In particular, it reduces unnecessary anticoagulation in younger women with no additional risk factors—an important step toward personalized and equitable care. While CHA₂DS₂-VA improves usability, our findings suggest it should function as a foundational tool, augmented by clinical judgment and awareness of unmeasured sex-specific vulnerabilities 21 . The CHA₂DS₂-VA score has since received a Class I, Level A recommendation in ESC guidelines 7 , with oral anticoagulation advised for patients scoring ≥ 2. Moreover, population-based screening for atrial fibrillation using non-invasive prolonged ECG monitoring is now recommended for individuals aged ≥ 75 years—or ≥ 65 years with CHA₂DS₂-VA risk factors—highlighting the need for earlier detection and tailored risk mitigation 22 23 . In this context, our findings reinforce two key principles: first, that female sex should no longer be viewed as a binary stroke risk factor; and second, that women with AF often present with a more complex risk profile, warranting proactive management 24 . Although the removal of sex from formal scoring frameworks reflects a data-driven evolution in practice, it does not negate the reality that women face persistent clinical vulnerabilities 22 . Therefore, CHA₂DS₂-VA should serve as a foundation—not a ceiling—for individualized stroke prevention strategies. Our findings underscore the need for equitable stroke prevention strategies that extend beyond score-based algorithms and address underlying disparities in diagnosis, treatment access, and long-term management among female patients with atrial fibrillation 25 . Future research should explore whether expanded risk models—integrating sex-associated comorbidities, atrial myopathy markers, and real-world treatment patterns—can improve prediction and guide tailored anticoagulation strategies in women with AF 26 , 27 . Sex may no longer count in the score, but it still counts in the clinic 28 . Limitations This study has several limitations. First, it was conducted at a single tertiary academic center, which may limit generalizability to other healthcare settings or more heterogeneous populations. Second, although we adjusted stroke risk calculations to simulate CHA₂DS₂-VA scoring, the analysis remains retrospective, and prospective validation of the new score in stroke cohorts is needed. Third, while baseline comorbidities were comprehensively recorded, residual confounding due to unmeasured factors such as socioeconomic status, frailty, and access to outpatient care cannot be excluded. Fourth, stroke severity and functional outcomes were assessed only at hospital discharge; longer-term outcomes such as recurrent stroke, mortality, and quality of life were not captured. Finally, although anticoagulation usage was recorded, detailed data on adherence, dosing, and quality of anticoagulation were not available, which may influence stroke outcomes independently of baseline risk scores. Future multicenter studies incorporating longitudinal follow-up and detailed assessment of therapeutic interventions are warranted to further elucidate sex-specific dynamics in stroke risk and prevention in AF. Conclusion In this prospective stroke cohort, female patients with atrial fibrillation exhibited a persistently higher vascular risk burden and greater stroke severity compared to male patients, even after recalculation of stroke risk using the sex-neutral CHA₂DS₂-VA score. While the removal of female sex as an independent risk factor simplifies decision-making for anticoagulation, our findings underscore that women with atrial fibrillation often present with more complex clinical profiles that merit careful individualized assessment. Sex-specific disparities in comorbidities, risk factor control, and stroke outcomes highlight the need for continued vigilance in the prevention and management of stroke among women with atrial fibrillation, beyond simple score-based stratification. Declarations Author Contribution P.B. conceived and designed the study, performed data interpretation, and wrote the main manuscript text. J.S. and K.P. contributed to data collection and statistical analysis. M.J. and O.A.O. supported clinical data validation and literature review. B.U. contributed to figure preparation and data visualization. S.S. and M.B. provided critical revisions and supervised the overall project. All authors reviewed, revised, and approved the final manuscript. Acknowledgement We thank the clinical colleagues and data analysts whose support made this work possible. Special appreciation goes to Prof. Buerke for critical feedback during manuscript development and to the research team members who handled the data with exceptional care and precision. Data Availability The datasets supporting the conclusions of this study are not publicly available due to patient privacy regulations but are available from the corresponding author upon reasonable request. References Di Carlo A, Bellino L, Consoli D, Mori F, Zaninelli A, Baldereschi M, Cattarinussi A, D'Alfonso MG, Gradia C, Sgherzi B et al (2019) Prevalence of atrial fibrillation in the Italian elderly population and projections from 2020 to 2060 for Italy and the European Union: the FAI Project. 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Neurol Clin 41:265–281. 10.1016/j.ncl.2022.10.001 Kostopoulou A, Zeljko HM, Bogossian H, Ciudin R, Costa F, Heijman J, Kochhaeuser S, Manola S, Scherr D, Sohal M et al (2020) Atrial fibrillation-related stroke in women: Evidence and inequalities in epidemiology, mechanisms, clinical presentation, and management. Clin Cardiol 43:14–23. 10.1002/clc.23284 Buhari H, Fang J, Han L, Austin PC, Dorian P, Jackevicius CA, Yu AYX, Kapral MK, Singh SM, Tu K et al (2024) Stroke risk in women with atrial fibrillation. Eur Heart J 45:104–113. 10.1093/eurheartj/ehad508 Yong CM, Tremmel JA, Lansberg MG, Fan J, Askari M, Turakhia MP (2020) Sex Differences in Oral Anticoagulation and Outcomes of Stroke and Intracranial Bleeding in Newly Diagnosed Atrial Fibrillation. J Am Heart Assoc 9:e015689. 10.1161/jaha.120.015689 Krittayaphong R, Apiyasawat S, Methavigul K, Komoltri C, Lip GYH (2025) Prediction of ischemic stroke by the CHA2DS2 -VA score in an Asian population: A report from the prospective nationwide COOL-AF registry. Heart Rhythm. 10.1016/j.hrthm.2025.04.062 Teppo K, Lip GYH, Airaksinen KEJ, Halminen O, Haukka J, Putaala J, Mustonen P, Linna M, Hartikainen J, Lehto M, Comparing (2024) CHA(2)DS(2)-VA and CHA(2)DS(2)-VASc scores for stroke risk stratification in patients with atrial fibrillation: a temporal trends analysis from the retrospective Finnish AntiCoagulation in Atrial Fibrillation (FinACAF) cohort. Lancet Reg Health Eur 43:100967. 10.1016/j.lanepe.2024.100967 Cove CL, Albert CM, Andreotti F, Badimon L, Van Gelder IC, Hylek EM (2014) Female sex as an independent risk factor for stroke in atrial fibrillation: possible mechanisms. Thromb Haemost 111:385–391. 10.1160/th13-04-0347 Kahwati LC, Asher GN, Kadro ZO, Keen S, Ali R, Coker-Schwimmer E, Jonas DE (2022) Screening for Atrial Fibrillation: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force. JAMA 327:368–383. 10.1001/jama.2021.21811 Lyth J, Svennberg E, Bernfort L, Aronsson M, Frykman V, Al-Khalili F, Friberg L, Rosenqvist M, Engdahl J, Levin L (2023) Cost-effectiveness of population screening for atrial fibrillation: the STROKESTOP study. Eur Heart J 44:196–204. 10.1093/eurheartj/ehac547 Bushnell C, McCullough LD, Awad IA, Chireau MV, Fedder WN, Furie KL, Howard VJ, Lichtman JH, Lisabeth LD, Piña IL et al (2014) Guidelines for the prevention of stroke in women: a statement for healthcare professionals from the American Heart Association/American Stroke Association. Stroke 45:1545–1588. 10.1161/01.str.0000442009.06663.48 Campora A, Lisi M, Pastore MC, Mandoli GE, Ferrari Chen YF, Pasquini A, Rubboli A, Henein MY, Cameli M (2024) Atrial Fibrillation, Atrial Myopathy, and Thromboembolism: The Additive Value of Echocardiography and Possible New Horizons for Risk Stratification. J Clin Med 13. 10.3390/jcm13133921 Nielsen PB, Overvad TF (2020) Female Sex as a Risk Modifier for Stroke Risk in Atrial Fibrillation: Using CHA2DS2-VASc versus CHA2DS2-VA for Stroke Risk Stratification in Atrial Fibrillation: A Note of Caution. Thromb Haemost 120:894–898. 10.1055/s-0040-1710014 Volgman AS, Benjamin EJ, Curtis AB, Fang MC, Lindley KJ, Naccarelli GV, Pepine CJ, Quesada O, Vaseghi M, Waldo AL et al (2021) Women and atrial fibrillation. J Cardiovasc Electrophysiol 32:2793–2807. 10.1111/jce.14838 Avgil Tsadok M, Jackevicius CA, Rahme E, Humphries KH, Behlouli H, Pilote L (2012) Sex differences in stroke risk among older patients with recently diagnosed atrial fibrillation. JAMA 307:1952–1958. 10.1001/jama.2012.3490 Tables Table 1 Baseline characteristics Table 1 presents demographic characteristics, cardiovascular comorbidities, and clinical parameters of the full stroke cohort (n=714), stratified by sex. Atrial fibrillation was present in 22.8% of the cohort (n=163), with a nearly equal distribution between men and women. Female patients were older and exhibited a higher prevalence of diabetes mellitus, whereas men had a higher burden of coronary artery disease and nicotine use. Total (n=714) Men (n=403) Women (n=311) Demographics Female sex, n (%) 311 (43.5%) 311 (100%) Age, years (mean ± SD) 73.6 ± 10.6 67.7 ± 8.9 81.3 ± 7.2 Comorbidities Previous TIA or stroke, n (%) 181 (25.4%) 101 (25.1%) 80 (25.7%) Nicotine abuse, n (%) 198 (26.3%) 121 (30.0%) 77 (24.8%) Obesity, n (%) 328 (46.0%) 203 (50.4%) 125 (40.2%) Hypertension, n (%) 537 (75.2%) 304 (75.4%) 233 (74.9%) Diabetes mellitus, n (%) 212 (28.3%) 104 (25.8%) 108 (34.7%) Atrial fibrillation, n (%) 163 (22.8%) 82 (20.3%) 80 (25.7%) Coronary artery disease, n (%) 191 (26.8%) 116 (28.8%) 75 (24.1%) Artificial heart valve, n (%) 41 (5.7%) 19 (4.7%) 22 (7.1%) Heart failure, n (%) 55 (7.7%) 33 (8.2%) 24 (7.7%) Hypercholesterinemia, n (%) 274 (38.4%) 144 (35.7%) 132 (42.4%) Embolic Risk and Stroke Severity CHA₂DS₂-VASc (mean) 5 3 4 CHA₂DS₂-VASc ≥1, n (%) 691 (96.8%) 380 (94.3%) 311 (100%) CHA₂DS₂-VASc ≥2, n (%) 523 (73.2%) 332 (82.4%) 292 (93.9%) CHA₂DS₂-VASc ≥5, n (%) 252 (35.3%) 92 (22.8%) 168 (54.0%) NIHSS at admission, mean ± SD 6.9 ± 4.3 6.4 ± 4.0 7.5 ± 4.6 NIHSS at discharge ± SD 3.6 ± 3.0 4.2 ± 3.5 2.9 ± 2.3 Table 2 Distribution of CHA₂DS₂-VA Scores in Female and Male Stroke Patients with Atrial Fibrillation The table displays the distribution of CHA₂DS₂-VA scores among female (n = 81) and male (n = 80) patients with ischemic stroke and documented atrial fibrillation. CHA₂DS₂-VA scores were calculated by removing the sex category from the conventional CHA₂DS₂-VASc score. A total of 11 out of 81 women (13.6%) had a CHA₂DS₂-VA score ≤1, compared to only 1 of 80 men (1.3%). This distribution underlies the significantly increased likelihood of female patients falling below the anticoagulation threshold (OR 5.78; 95% CI, 1.15–29.0). The data highlight the potential implications of the updated ESC anticoagulation guidelines on sex-specific risk classification. CHA₂DS₂-VASc Score CHA₂DS₂-VA Score Number of women Number of men 1 0 3 1 2 1 8 2 3 2 12 10 4 3 18 14 5 4 24 24 6 5 12 20 7 6 6 9 Table 3 Stroke Subtypes according to sex This table displays the distribution of ischemic stroke subtypes stratified by sex in the full cohort (N = 714). While men comprised the majority of all stroke cases (56.4%), women were overrepresented in transient ischemic attacks (TIA), accounting for 55.1% of TIA cases. In contrast, atherosclerotic, cryptogenic, and ESUS strokes were more frequently observed in men. The proportion of female patients was highest in the TIA and lacunar subtypes, and lowest in large-artery atherosclerosis. These findings reflect distinct sex-related patterns in stroke etiology. Stroke Subtype Total (n) Female (n, %) Male (n, %) All Strokes 714 311 (43.6%) 403 (56.4%) TIA 185 102 (55.1%) 83 (44.9%) Cryptogenic 163 61 (37.4%) 102 (62.6%) ESUS 98 38 (38.8%) 60 (61.2%) Atherosclerotic 110 36 (32.7%) 74 (67.3%) Cardioembolic 209 90 (43.1%) 119 (56.9%) Lacunar 40 18 (45.0%) 22 (55.0%) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Oct, 2025 Read the published version in Acta Neurologica Belgica → Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7114395","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":495864384,"identity":"43318aa4-7e23-4fc9-a2b4-a0a74475630c","order_by":0,"name":"Priyanka Boettger","email":"data:image/png;base64,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","orcid":"","institution":"University of Giessen","correspondingAuthor":true,"prefix":"","firstName":"Priyanka","middleName":"","lastName":"Boettger","suffix":""},{"id":495864385,"identity":"104f475a-edab-4ab5-9b10-f273dc0b6f5e","order_by":1,"name":"Jamschid Sedighi","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Jamschid","middleName":"","lastName":"Sedighi","suffix":""},{"id":495864386,"identity":"429329e0-66f6-4ac5-88fa-8297d83ee21d","order_by":2,"name":"Kerstin Piayda","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Kerstin","middleName":"","lastName":"Piayda","suffix":""},{"id":495864387,"identity":"a2b7cc74-9bea-42a4-bfad-c41bb345043a","order_by":3,"name":"Martin Juenemann","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Martin","middleName":"","lastName":"Juenemann","suffix":""},{"id":495864388,"identity":"20123f6c-3735-47b0-83ca-69c629ba46f8","order_by":4,"name":"Omar Alhaj Omar","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Omar","middleName":"Alhaj","lastName":"Omar","suffix":""},{"id":495864389,"identity":"d2bf8044-5a2a-4c38-96c3-e9a699b19fa2","order_by":5,"name":"Bernhard Unsoeld","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Bernhard","middleName":"","lastName":"Unsoeld","suffix":""},{"id":495864390,"identity":"e16e1706-8578-423a-94a0-481a1ef7cf21","order_by":6,"name":"Samuel Sossalla","email":"","orcid":"","institution":"University of Giessen","correspondingAuthor":false,"prefix":"","firstName":"Samuel","middleName":"","lastName":"Sossalla","suffix":""},{"id":495864391,"identity":"58d35d53-067a-4345-910f-c70c169d0f41","order_by":7,"name":"Michael Buerke","email":"","orcid":"","institution":"St. Marien Hospital","correspondingAuthor":false,"prefix":"","firstName":"Michael","middleName":"","lastName":"Buerke","suffix":""}],"badges":[],"createdAt":"2025-07-13 16:08:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7114395/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7114395/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s13760-025-02916-7","type":"published","date":"2025-10-13T15:57:03+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":88644740,"identity":"e9d01fbc-6a5b-410f-bcb8-5c19ccf1fafc","added_by":"auto","created_at":"2025-08-08 16:20:58","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":62013,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePredictive performance of CHA₂DS₂-VASc and CHA₂DS₂-VA scores for severe stroke.\u003c/strong\u003e Receiver operating characteristic (ROC) curves comparing the ability of the CHA₂DS₂-VASc and CHA₂DS₂-VA scores to predict severe stroke (NIHSS ≥10). As expected, the two scores demonstrated highly similar predictive performance (AUC 0.76 vs. 0.72), reflecting the fact that they differ only by 1 point in women. The difference in AUCs was not statistically significant (DeLong P = 0.09), supporting the overall comparability of both scores.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7114395/v1/8daa059ae70d4d264e4ac260.jpg"},{"id":88644741,"identity":"8d0932c4-692a-47e5-b9a4-cebf72cdce9f","added_by":"auto","created_at":"2025-08-08 16:20:58","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45055,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSex Differences in NIHSS Scores at Admission and Discharge\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBoxplots showing NIHSS scores stratified by sex at hospital admission and discharge. Female patients exhibited higher median NIHSS scores at both timepoints compared to male patients. Dots represent individual values; diamonds indicate outliers. The analysis highlights a sex disparity in stroke severity and functional outcome across the acute care episode.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7114395/v1/3970b54abf43bbd59984df90.jpg"},{"id":93955911,"identity":"f3ba231c-043f-4dfa-a237-553a2fd5b47a","added_by":"auto","created_at":"2025-10-20 16:06:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1087570,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7114395/v1/ea62efcc-5a9b-40a7-859a-04a61ca8f220.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eProspective Evaluation of the CHA₂DS₂-VA Score: Do Sex Differences Still Matter in Stroke?\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStroke remains a leading cause of death and disability worldwide, with atrial fibrillation (AF) recognized as a major contributor to embolic stroke risk \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. AF affects an estimated 60\u0026nbsp;million people globally and is projected to double in prevalence by 2060 due to population aging \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. The arrhythmia is associated not only with clinical stroke events but also with subclinical cerebral injury, cognitive decline, and vascular dementia, leading to profound healthcare and socioeconomic burdens \u003csup\u003e3 4\u003c/sup\u003e. Effective stroke prevention in AF hinges on accurate risk stratification \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Traditionally, the CHA₂DS₂-VASc score has been used to guide decisions regarding anticoagulation \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, accumulating evidence suggests that female sex alone may not constitute an independent stroke risk factor in the absence of additional comorbidities. Reflecting these insights, the 2024 European Society of Cardiology (ESC) guidelines for the management of atrial fibrillation have introduced the CHA₂DS₂-VA score, which removes female sex as a risk criterion \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Anticoagulation is now recommended based on a CHA₂DS₂-VA score of 2 or higher, and can be considered for a score of 1, irrespective of sex. \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eThe new ESC guidelines also emphasize a holistic, patient-centered approach summarized in the CARE pathway, prioritizing comorbidity management, prevention of stroke and thromboembolism, symptom reduction, and dynamic reassessment.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Nevertheless, the real-world implications of these changes for stroke patients, particularly concerning sex-specific differences in risk profiles and outcomes, remain incompletely understood. In this study, we evaluated sex differences in stroke subtypes, vascular risk factors, and stroke severity within a large prospective stroke cohort. Special attention was given to patients with atrial fibrillation, in whom we recalculated risk scores excluding the sex category to simulate the new CHA₂DS₂-VA approach. We hypothesized that despite removal of female sex from formal risk scores, women with AF experience higher stroke severity and vascular burden due to residual and systemic risk modifiers.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe conducted a prospective observational study at an academic stroke center over a six-month period. Consecutive adult patients (aged ≥ 18 years) admitted with acute ischemic stroke or transient ischemic attack (TIA), confirmed by neuroimaging, were included. Patients with hemorrhagic stroke, in-hospital stroke, or hospital stays shorter than 24 hours were excluded. Written informed consent was obtained from all participants or their legal representatives. The study was approved by the local ethics committee (Westfalen-Lippe Medical Association).\u003c/p\u003e\u003cp\u003eStroke subtypes were classified according to standard criteria, including Trial of Org 10172 in Acute Stroke Treatment (TOAST) definitions and established criteria for embolic stroke of undetermined source (ESUS). Patients with documented atrial fibrillation (AF) during hospitalization or prior to admission were identified. Cardioembolic stroke was defined based on clinical, imaging, and cardiac investigations, including detection of AF, atrial flutter, intracardiac thrombus, recent myocardial infarction, or left ventricular dysfunction (ejection fraction \u0026lt; 35%).\u003c/p\u003e\u003cp\u003e\u003cb\u003eClinical assessment and data collection\u003c/b\u003e\u003c/p\u003e\u003cp\u003eBaseline demographics, cardiovascular risk factors (hypertension, diabetes mellitus, coronary artery disease, obesity, hypercholesterolemia, smoking), and stroke history were systematically recorded. Stroke severity was assessed using the National Institutes of Health Stroke Scale (NIHSS) at admission and at discharge or death. Functional outcomes were evaluated at discharge using the modified Rankin Scale (mRS). Cardiovascular risk stratification was performed using the CHA₂DS₂-VASc score at admission. To simulate the newly proposed CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, one point for female sex was subtracted in women. Median scores and interquartile ranges were calculated for both CHA₂DS₂-VASc and CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA scores in male and female stroke patients with AF.\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eContinuous variables were reported as medians with interquartile ranges (IQR) or means with standard deviations (SD), depending on data distribution. Categorical variables were presented as counts and percentages. Group comparisons were performed using the Mann–Whitney U test for continuous variables and the chi-square or Fisher’s exact test for categorical variables. Differences in stroke severity (NIHSS), functional outcome (mRS), and risk scores (CHA₂DS₂-VASc, CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA) between sexes were evaluated. A two-sided \u003cem\u003eP\u003c/em\u003e-value of \u0026lt; 0.05 was considered statistically significant. Confidence intervals (CIs) were calculated for key differences. All statistical analyses were conducted using SPSS Statistics, version 28 (IBM Corp.). Multivariable logistic regression was performed to assess the independent association between sex and severe stroke presentation, defined as NIHSS ≥ 10. Covariates included age, atrial fibrillation, diabetes mellitus, coronary artery disease, and stroke subtype (e.g., cardioembolic vs. ESUS). Adjusted odds ratios (aOR) with 95% confidence intervals (CI) were reported. Additionally, propensity score matching (PSM) was conducted to balance baseline characteristics between male and female patients with atrial fibrillation. Patients were matched 1:1 using nearest-neighbor matching without replacement on the basis of age, diabetes, and coronary artery disease. Post-matching balance was assessed using standardized mean differences. NIHSS and mRS outcomes were compared between matched pairs using Wilcoxon signed-rank and McNemar tests, respectively.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eSex differences in different stroke subtypes\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong the 714 patients included in the cohort, 403 (56.4%) were male and 311 (43.6%) female. Transient ischemic attacks (TIAs) were the only subtype with female predominance (55.1%), a difference that reached statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02; 95% CI, 2.1 to 17.6 percentage points). In contrast, atherothrombotic strokes occurred more frequently in men (67.3% vs. 32.7%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while cryptogenic and ESUS subtypes demonstrated no significant sex differences (ESUS: 38.8% female vs. 61.2% male, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.42).\u003c/p\u003e\u003cp\u003eRegarding embolic risk factors, coronary artery disease was more common among men (30.0% vs. 22.0%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04; 95% CI, 0.6 to 15.2 percentage points). Atrial fibrillation (25.2% vs. 20.1%) and prior stroke or TIA (27.3% vs. 23.4%) were more frequently observed in women; however, these differences did not reach statistical significance (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05 for both comparisons).\u003c/p\u003e\u003cp\u003eSex-specific variation in cardiovascular risk profiles was also evident. Obesity was more prevalent in men (50.2% vs. 39.9%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03; 95% CI, 1.1 to 19.8), as was current smoking (30.4% vs. 20.1%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01; 95% CI, 2.9 to 17.1). Conversely, diabetes mellitus (35.1% vs. 26.5%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04) and hypercholesterolemia (42.1% vs. 34.3%, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.05) were more frequently observed in women.\u003c/p\u003e\u003cp\u003eStroke severity, measured by the NIHSS at admission, was significantly greater in women than in men (median, 7 vs. 6; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04), a difference most pronounced in cardioembolic stroke (median, 12 vs. 8; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01; 95% CI, 1 to 5 points). Similarly, in the ESUS subgroup, women presented with more severe strokes (median NIHSS, 7 vs. 3; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), although this disparity was no longer apparent at discharge.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStroke patients with AF\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong the 714 patients included in the cohort, atrial fibrillation (AF) was identified in 161 patients (22.5%). Of these, 81 patients (50.3%) were female, and 80 patients (49.7%) were male. Female patients with AF were older than their male counterparts (mean age, 78 years vs. 74 years; P\u0026thinsp;=\u0026thinsp;0.03). Cardiovascular risk profiles differed by sex. Diabetes mellitus was more prevalent in women with AF (40.7% vs. 32.5%), whereas coronary artery disease was more common among men (28.8% vs. 17.3%; P\u0026thinsp;=\u0026thinsp;0.04).\u003c/p\u003e\u003cp\u003eStroke severity at presentation, assessed by the National Institutes of Health Stroke Scale (NIHSS), was significantly higher in women compared to men (median NIHSS, 12 [interquartile range, 7\u0026ndash;16] vs. 8 [interquartile range, 4\u0026ndash;13]; P\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This sex difference in stroke severity was particularly pronounced in the cardioembolic stroke subgroup. Functional outcomes at discharge, measured by the modified Rankin Scale (mRS), also tended to be worse among female patients, although the difference did not reach statistical significance (median mRS, 4 vs. 3; P\u0026thinsp;=\u0026thinsp;0.08).\u003c/p\u003e\u003cp\u003eRegarding stroke subtype distribution, the majority of AF patients were classified as cardioembolic strokes (74.5%), with no significant sex differences in subtype classification (P\u0026thinsp;=\u0026thinsp;0.45). Within the ESUS subgroup, women with AF presented with more severe strokes than men (median NIHSS, 7 vs. 3; P\u0026thinsp;=\u0026thinsp;0.03), although this disparity was not evident at discharge.\u003c/p\u003e\u003cp\u003e\u003cb\u003eAssociation of sex with functional outcome: Ordinal logistic regression\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo explore the association between sex and functional outcome across the full spectrum of disability, an ordinal logistic regression was performed using the modified Rankin Scale (mRS) at discharge as the dependent variable. After adjusting for age, atrial fibrillation, diabetes mellitus, coronary artery disease, stroke subtype, and initial NIHSS score, female sex was independently associated with worse functional outcome (adjusted odds ratio [aOR], 1.42; 95% confidence interval [CI], 1.01\u0026ndash;2.00; P\u0026thinsp;=\u0026thinsp;0.046). This association remained consistent in a sensitivity analysis restricted to patients with cardioembolic stroke, suggesting a robust effect of sex on disability severity across stroke subtypes. The findings reinforce the observation that women with stroke, even when accounting for vascular risk and stroke severity, tend to experience poorer functional recovery at discharge.\u003c/p\u003e\u003cp\u003e\u003cb\u003eStroke Risk Scores: CHA₂DS₂-VASc vs. CHA\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003eDS\u003c/b\u003e\u003csub\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sub\u003e\u003cb\u003e-VA Score\u003c/b\u003e\u003c/p\u003e\u003cp\u003eMedian CHA₂DS₂-VASc scores differed significantly between sexes. Female stroke patients exhibited a higher median CHA₂DS₂-VASc score compared to male patients (5 [interquartile range, 4\u0026ndash;6] vs. 3 [interquartile range, 2\u0026ndash;4]; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After recalculating the score by removing the sex category to derive the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, the difference persisted, although it was attenuated (median CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score, 4 [interquartile range, 3\u0026ndash;5] in women vs. 3 [interquartile range, 2\u0026ndash;4] in men; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03).\u003c/p\u003e\u003cp\u003eThe adjusted difference in median CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA scores between women and men was 1 point (95% confidence interval, 0.5 to 1.5 points). These findings indicate that female stroke patients retain a higher vascular risk burden even after the sex category is removed, underscoring the importance of comprehensive risk stratification beyond simple score recalculations.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFemale stroke patients below the current anticoagulation threshold\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAmong the 81 female stroke patients with atrial fibrillation, 11 (13.6%) had a premorbid CHA₂DS₂-VA score of \u0026le;\u0026thinsp;1. By contrast, only 1 of 80 male patients (1.3%) fell into this category (P\u0026thinsp;=\u0026thinsp;0.006, Fisher\u0026rsquo;s exact test). In the female low-score subgroup, 8 of 11 patients (72.7%) presented with moderate to severe stroke (NIHSS\u0026thinsp;\u0026ge;\u0026thinsp;8), compared to 48.2% (34/70) in the remaining female AF cohort (P\u0026thinsp;=\u0026thinsp;0.04, Fisher\u0026rsquo;s exact test). Cardioembolic stroke was the assigned etiology in 6 of 11 cases (54.5%) among low-score women, compared to 74.3% (52/70) in other women with AF (P\u0026thinsp;=\u0026thinsp;0.19).\u003c/p\u003e\u003cp\u003eFemale sex was associated with a significantly higher likelihood of falling below the anticoagulation threshold (OR 5.78, 95% CI 1.15\u0026ndash;29.0; P\u0026thinsp;=\u0026thinsp;0.03). NIHSS at admission in this low-score subgroup had a median of 9 (IQR 6\u0026ndash;12), compared to 7 (IQR 4\u0026ndash;11) in the rest of the female AF cohort (P\u0026thinsp;=\u0026thinsp;0.04, Mann\u0026ndash;Whitney U test).\u003c/p\u003e\u003cp\u003e\u003cb\u003eAge-Independent CHA2DS2-VA Score\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo account for the observed age difference between male and female stroke patients with atrial fibrillation (mean age, 78 vs. 74 years; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03), an age-independent analysis of the CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA score was performed. For this purpose, CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA scores were recalculated excluding the age-related points (age 65\u0026ndash;74 years and \u0026ge;\u0026thinsp;75 years).\u003c/p\u003e\u003cp\u003eAfter removal of age as a scoring component, female patients continued to demonstrate significantly higher median CHA\u003csub\u003e2\u003c/sub\u003eDS\u003csub\u003e2\u003c/sub\u003e-VA scores compared to male patients (median, 3 [IQR, 2\u0026ndash;4] vs. 2 [IQR, 1\u0026ndash;3]; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). The adjusted difference in scores between women and men was 1 point (95% confidence interval, 0.3 to 1.7 points). These findings suggest that, beyond differences in chronological age, women with atrial fibrillation who experience stroke have a higher burden of vascular risk factors than men. This persistent disparity reinforces the importance of individualized risk assessment beyond standard scoring algorithms.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePredictive performance of CHA₂DS₂-VASc and CHA₂DS₂-VA for stroke severity\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo evaluate the predictive performance of the conventional CHA₂DS₂-VASc score versus the revised CHA₂DS₂-VA score, we performed receiver operating characteristic (ROC) curve analyses with severe stroke (NIHSS\u0026thinsp;\u0026ge;\u0026thinsp;10) as the binary outcome. The area under the curve (AUC) for the CHA₂DS₂-VASc score was 0.74 (95% CI, 0.68\u0026ndash;0.80), compared to 0.71 (95% CI, 0.65\u0026ndash;0.78) for the CHA₂DS₂-VA score. The difference in AUCs was not statistically significant (DeLong test P\u0026thinsp;=\u0026thinsp;0.09), suggesting comparable discriminatory ability between the two scoring systems in this cohort. Sex-stratified analyses revealed a slightly higher AUC for CHA₂DS₂-VASc in women than in men (0.75 vs. 0.71), but this difference was not significant (P\u0026thinsp;=\u0026thinsp;0.12). Both scores demonstrated similar calibration across risk strata. These findings suggest that while removal of female sex from the CHA₂DS₂-VASc score does not significantly impair its overall performance in predicting stroke severity, it may underestimate the cumulative risk burden among female patients with AF, particularly those with overlapping comorbidities.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMultivariable and propensity-matched analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo assess whether sex was independently associated with stroke severity, we performed multivariable logistic regression with severe stroke (NIHSS\u0026thinsp;\u0026ge;\u0026thinsp;10) as the dependent variable. After adjusting for age, atrial fibrillation, diabetes mellitus, coronary artery disease, and stroke subtype, female sex remained an independent predictor of severe stroke (adjusted odds ratio [aOR], 1.54; 95% CI, 1.03\u0026ndash;2.29; P\u0026thinsp;=\u0026thinsp;0.03). Age and the presence of atrial fibrillation were also independently associated with severe stroke (aOR for age\u0026thinsp;\u0026ge;\u0026thinsp;75 years, 1.82; 95% CI, 1.12\u0026ndash;2.95; P\u0026thinsp;=\u0026thinsp;0.01; aOR for AF, 1.46; 95% CI, 1.01\u0026ndash;2.11; P\u0026thinsp;=\u0026thinsp;0.04). To reduce confounding by baseline vascular risk profiles, we performed 1:1 propensity score matching (PSM) on 72 women and 72 men with atrial fibrillation, matched for age, diabetes, and coronary artery disease. Standardized mean differences for matched variables were \u0026lt;\u0026thinsp;0.1, indicating good balance.\u003c/p\u003e\u003cp\u003eAfter matching, female patients continued to exhibit higher stroke severity at presentation, with a median NIHSS of 11 (IQR, 7\u0026ndash;16) compared to 8 (IQR, 5\u0026ndash;13) in male patients (P\u0026thinsp;=\u0026thinsp;0.02, Wilcoxon signed-rank test). Functional outcome at discharge, assessed by mRS, showed a non-significant trend toward worse outcomes in women (mRS\u0026thinsp;\u0026ge;\u0026thinsp;4 in 56.9% of women vs. 43.1% of men; P\u0026thinsp;=\u0026thinsp;0.08, McNemar test). These findings suggest that the sex disparity in stroke severity among patients with AF persists even after accounting for age and comorbid risk factors.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this prospective study of patients with acute ischemic stroke and atrial fibrillation (AF), we reexamined thromboembolic risk stratification in the context of the recently proposed CHA₂DS₂-VA score, which removes female sex as an independent scoring criterion. Although intended to simplify anticoagulation decision-making and avoid sex-based overclassification, our data reveal that female patients continue to exhibit a disproportionate burden of vascular comorbidities, greater stroke severity, and worse outcomes compared with men\u0026mdash;even after recalculation using the sex-neutral algorithm \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. These findings suggest that female sex, while no longer a direct risk component, remains a clinically meaningful modifier of cumulative stroke risk. To our knowledge, this is one of the first prospective studies to assess the CHA₂DS₂-VA score in an acute ischemic stroke cohort. Our findings provide real-world validation of persistent sex differences in vascular risk and stroke severity despite score recalibration.\u003c/p\u003e\u003cp\u003eThe rationale for excluding female sex from the revised CHA₂DS₂-VA score stems from accumulating evidence that women without additional risk factors do not have an intrinsically elevated thromboembolic risk\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This perspective is supported by large cohort studies and informs recent guideline changes from the European Society of Cardiology (ESC)\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Our findings are in line with this evidence: women in our cohort had higher median CHA₂DS₂-VA scores than men, but this difference was not driven by sex itself. Rather, it reflected a higher prevalence of hypertension, diabetes, and advanced age among female patients\u0026mdash;factors that independently elevate stroke risk \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. ROC analysis confirmed that removing the sex category from the CHA₂DS₂-VASc score did not significantly impair its predictive performance for severe stroke. However, women still reached higher scores due to greater age and comorbidity burden. This emphasizes that while CHA₂DS₂-VA performs similarly overall, sex-specific risk profiles persist, and merit individualized clinical attention. To further explore the clinical implications of this recalibration, we examined the subgroup that fell below the anticoagulation treshold with CHA₂DS₂-VA scores of \u0026le;\u0026thinsp;1.\u003c/p\u003e\u003cp\u003e A particularly concerning finding in our cohort was that 13.6% of female stroke patients with AF had a premorbid CHA₂DS₂-VA score of \u0026le;\u0026thinsp;1, and would therefore fall below the ESC threshold for initiating oral anticoagulation. Although they had experienced ischemic strokes, these women would have not qualified for treatment under current guidelines before stroke. Notably, women represented over 90% of all low-score patients, and nearly three-quarters of them presented with NIHSS\u0026thinsp;\u0026ge;\u0026thinsp;8, indicating moderate to severe neurological impairment. More than half were classified as cardioembolic strokes. These findings underscore a critical discordance between score-based risk stratification and real-world stroke burden in women. While female sex is no longer a formal component of the CHA₂DS₂-VA score, it remains a clinical modifier of risk\u0026mdash;mediated through older age, clustering of comorbidities, and differential access to care. Our data suggest that the revised scoring system, while statistically justified, may under-recognize meaningful risk in a subset of female patients with complex stroke profiles.\u003c/p\u003e\u003cp\u003eIt is also important to consider intersectional factors\u0026mdash;such as advanced age, cognitive vulnerability, and limited access to specialty care\u0026mdash;which disproportionately affect older female stroke patients and compound risk beyond what is captured by conventional scoring systems \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHowever, the persistence of sex disparities in stroke severity and vascular burden suggests that female patients with AF represent a high-risk subgroup due to intersecting biological, structural, and systemic vulnerabilities \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e. Mechanistically, women are more likely to exhibit hypertensive remodeling, renal dysfunction, hyperthyroidism, and hypercoagulable states, each of which can potentiate embolic risk \u003csup\u003e16 10\u003c/sup\u003e. Additionally, cardiac remodeling patterns and hormonal changes after menopause may contribute to atrial vulnerability and thromboembolic potential\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEqually important are systemic disparities in cardiovascular care. Women are less likely to be referred for specialist evaluation, to receive anticoagulation when indicated, or to be prescribed statins and undergo lipid monitoring \u003csup\u003e17 18\u003c/sup\u003e. Older age at diagnosis, under-recognition of risk, and delays in treatment initiation contribute further to the observed outcome gap between men and women. \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e These findings underscore that even in a sex-neutral scoring system, female patients often arrive at higher risk thresholds through the accumulation of clinical and structural disadvantages \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eRecent studies, including those by Yoshimura et al. and Teppo et al., have examined the clinical impact of removing female sex from CHA₂DS₂-VASc\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. These analyses support the use of CHA₂DS₂-VA for initial anticoagulation decisions, as it maintains comparable predictive performance while simplifying risk classification and improving applicability across sex and gender identities. Notably, American guidelines continue to endorse CHA₂DS₂-VASc scoring\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. In this transatlantic divergence, our findings suggest that while sex-based simplification improves clarity, score recalibration must be accompanied by intensified clinical judgment in high-risk subgroups. In particular, it reduces unnecessary anticoagulation in younger women with no additional risk factors\u0026mdash;an important step toward personalized and equitable care.\u003c/p\u003e\u003cp\u003eWhile CHA₂DS₂-VA improves usability, our findings suggest it should function as a foundational tool, augmented by clinical judgment and awareness of unmeasured sex-specific vulnerabilities\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. The CHA₂DS₂-VA score has since received a Class I, Level A recommendation in ESC guidelines\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, with oral anticoagulation advised for patients scoring\u0026thinsp;\u0026ge;\u0026thinsp;2. Moreover, population-based screening for atrial fibrillation using non-invasive prolonged ECG monitoring is now recommended for individuals aged\u0026thinsp;\u0026ge;\u0026thinsp;75 years\u0026mdash;or \u0026ge;\u0026thinsp;65 years with CHA₂DS₂-VA risk factors\u0026mdash;highlighting the need for earlier detection and tailored risk mitigation \u003csup\u003e22 23\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIn this context, our findings reinforce two key principles: first, that female sex should no longer be viewed as a binary stroke risk factor; and second, that women with AF often present with a more complex risk profile, warranting proactive management \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Although the removal of sex from formal scoring frameworks reflects a data-driven evolution in practice, it does not negate the reality that women face persistent clinical vulnerabilities \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. Therefore, CHA₂DS₂-VA should serve as a foundation\u0026mdash;not a ceiling\u0026mdash;for individualized stroke prevention strategies. Our findings underscore the need for equitable stroke prevention strategies that extend beyond score-based algorithms and address underlying disparities in diagnosis, treatment access, and long-term management among female patients with atrial fibrillation \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Future research should explore whether expanded risk models\u0026mdash;integrating sex-associated comorbidities, atrial myopathy markers, and real-world treatment patterns\u0026mdash;can improve prediction and guide tailored anticoagulation strategies in women with AF \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Sex may no longer count in the score, but it still counts in the clinic \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003e\u003cb\u003eLimitations\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, it was conducted at a single tertiary academic center, which may limit generalizability to other healthcare settings or more heterogeneous populations. Second, although we adjusted stroke risk calculations to simulate CHA₂DS₂-VA scoring, the analysis remains retrospective, and prospective validation of the new score in stroke cohorts is needed. Third, while baseline comorbidities were comprehensively recorded, residual confounding due to unmeasured factors such as socioeconomic status, frailty, and access to outpatient care cannot be excluded. Fourth, stroke severity and functional outcomes were assessed only at hospital discharge; longer-term outcomes such as recurrent stroke, mortality, and quality of life were not captured. Finally, although anticoagulation usage was recorded, detailed data on adherence, dosing, and quality of anticoagulation were not available, which may influence stroke outcomes independently of baseline risk scores. Future multicenter studies incorporating longitudinal follow-up and detailed assessment of therapeutic interventions are warranted to further elucidate sex-specific dynamics in stroke risk and prevention in AF.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this prospective stroke cohort, female patients with atrial fibrillation exhibited a persistently higher vascular risk burden and greater stroke severity compared to male patients, even after recalculation of stroke risk using the sex-neutral CHA₂DS₂-VA score. While the removal of female sex as an independent risk factor simplifies decision-making for anticoagulation, our findings underscore that women with atrial fibrillation often present with more complex clinical profiles that merit careful individualized assessment. Sex-specific disparities in comorbidities, risk factor control, and stroke outcomes highlight the need for continued vigilance in the prevention and management of stroke among women with atrial fibrillation, beyond simple score-based stratification.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eP.B. conceived and designed the study, performed data interpretation, and wrote the main manuscript text. J.S. and K.P. contributed to data collection and statistical analysis. M.J. and O.A.O. supported clinical data validation and literature review. B.U. contributed to figure preparation and data visualization. S.S. and M.B. provided critical revisions and supervised the overall project. All authors reviewed, revised, and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the clinical colleagues and data analysts whose support made this work possible. Special appreciation goes to Prof. Buerke for critical feedback during manuscript development and to the research team members who handled the data with exceptional care and precision.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets supporting the conclusions of this study are not publicly available due to patient privacy regulations but are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eDi Carlo A, Bellino L, Consoli D, Mori F, Zaninelli A, Baldereschi M, Cattarinussi A, D'Alfonso MG, Gradia C, Sgherzi B et al (2019) Prevalence of atrial fibrillation in the Italian elderly population and projections from 2020 to 2060 for Italy and the European Union: the FAI Project. 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JAMA 307:1952\u0026ndash;1958. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jama.2012.3490\u003c/span\u003e\u003cspan address=\"10.1001/jama.2012.3490\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1 Baseline characteristics\u0026nbsp;\u003c/strong\u003eTable 1 presents demographic characteristics, cardiovascular comorbidities, and clinical parameters of the full stroke cohort (n=714), stratified by sex. Atrial fibrillation was present in 22.8% of the cohort (n=163), with a nearly equal distribution between men and women. Female patients were older and exhibited a higher prevalence of diabetes mellitus, whereas men had a higher burden of coronary artery disease and nicotine use.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=714)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMen (n=403)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eWomen (n=311)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDemographics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eFemale sex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e311 (43.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e311 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eAge, years (mean \u0026plusmn; SD)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e73.6 \u0026plusmn; 10.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e67.7 \u0026plusmn; 8.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e81.3 \u0026plusmn; 7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ePrevious TIA or stroke, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e181 (25.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e101 (25.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e80 (25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eNicotine abuse, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e198 (26.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e121 (30.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e77 (24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eObesity, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e328 (46.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e203 (50.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e125 (40.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eHypertension, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e537 (75.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e304 (75.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e233 (74.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eDiabetes mellitus,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e212 (28.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e104 (25.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e108 (34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eAtrial fibrillation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e163 (22.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e82 (20.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e80 (25.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCoronary artery disease, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e191 (26.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e116 (28.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e75 (24.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eArtificial heart valve,\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e41 (5.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e19 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e22 (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eHeart failure, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e55 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e33 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e24 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eHypercholesterinemia, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e274 (38.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e144 (35.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e132 (42.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmbolic Risk and Stroke Severity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCHA₂DS₂-VASc (mean)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e5\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCHA₂DS₂-VASc \u0026ge;1,\u0026nbsp;\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e691 (96.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e380 (94.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e311 (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCHA₂DS₂-VASc \u0026ge;2,\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e523 (73.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e332 (82.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e292 (93.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCHA₂DS₂-VASc \u0026ge;5,\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e252 (35.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e92 (22.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e168 (54.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eNIHSS at admission, mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e6.9 \u0026plusmn; 4.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e6.4 \u0026plusmn; 4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e7.5 \u0026plusmn; 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eNIHSS at discharge \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e3.6 \u0026plusmn; 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e4.2 \u0026plusmn; 3.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e2.9 \u0026plusmn; 2.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Distribution of CHA₂DS₂-VA Scores in Female and Male Stroke Patients with Atrial Fibrillation\u003c/strong\u003e The table displays the distribution of CHA₂DS₂-VA scores among female (n = 81) and male (n = 80) patients with ischemic stroke and documented atrial fibrillation. CHA₂DS₂-VA scores were calculated by removing the sex category from the conventional CHA₂DS₂-VASc score. A total of 11 out of 81 women (13.6%) had a CHA₂DS₂-VA score \u0026le;1, compared to only 1 of 80 men (1.3%). This distribution underlies the significantly increased likelihood of female patients falling below the anticoagulation threshold (OR 5.78; 95% CI, 1.15\u0026ndash;29.0). The data highlight the potential implications of the updated ESC anticoagulation guidelines on sex-specific risk classification.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHA₂DS₂-VASc Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCHA₂DS₂-VA Score\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of women\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of men\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Stroke Subtypes according to sex\u0026nbsp;\u003c/strong\u003eThis table displays the distribution of ischemic stroke subtypes stratified by sex in the full cohort (N = 714). While men comprised the majority of all stroke cases (56.4%), women were overrepresented in transient ischemic attacks (TIA), accounting for 55.1% of TIA cases. In contrast, atherosclerotic, cryptogenic, and ESUS strokes were more frequently observed in men. The proportion of female patients was highest in the TIA and lacunar subtypes, and lowest in large-artery atherosclerosis. These findings reflect distinct sex-related patterns in stroke etiology.\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStroke Subtype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale (n, %)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll Strokes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e311 (43.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e403 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTIA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e102 (55.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e83 (44.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCryptogenic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e61 (37.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e102 (62.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eESUS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e38 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e60 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAtherosclerotic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e36 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e74 (67.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCardioembolic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e90 (43.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e119 (56.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 92px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLacunar\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e18 (45.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 73px;\"\u003e\n \u003cp\u003e22 (55.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7114395/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7114395/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e The 2024 ESC atrial fibrillation (AF) guidelines introduced the CHA₂DS₂-VA score, eliminating female sex as an independent risk criterion for stroke risk stratification. This revision aimed to improve clarity and avoid sex-based overtreatment. However, its real-world impact on women with ischemic stroke remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e In a prospective cohort of 714 consecutive stroke patients, 161 (22.5%) had documented AF. Risk stratification was performed using both CHA₂DS₂-VASc and the revised CHA₂DS₂-VA score. Stroke severity (NIHSS) and functional outcome (mRS) were analyzed by sex. Propensity score matching and multivariable logistic regression were used to examine the independent association between sex and stroke severity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e Female patients with AF were older and had a higher vascular risk burden than men. They presented with significantly more severe strokes (median NIHSS 12 vs. 8; \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01) and tended toward worse outcomes. After score recalibration, 11 of 81 women (13.6%) had a CHA₂DS₂-VA score ≤1, falling below the ESC anticoagulation threshold—despite having experienced an ischemic stroke. Most of these patients had cardioembolic strokes and moderate-to-severe neurological deficits. In matched analyses, female sex remained independently associated with severe stroke (aOR 1.54, 95% CI 1.03–2.29).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003e\u0026nbsp;The removal of female sex from the CHA₂DS₂-VA score does not eliminate sex-specific disparities in stroke risk. A clinically meaningful subgroup of women now falls below treatment thresholds, raising concern for under-treatment. These findings call for nuanced anticoagulation strategies that go beyond score-based decisions and better reflect real-world risk in female stroke patients with AF.\u003c/p\u003e","manuscriptTitle":"Prospective Evaluation of the CHA₂DS₂-VA Score: Do Sex Differences Still Matter in Stroke?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-08 16:20:54","doi":"10.21203/rs.3.rs-7114395/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"783e68ce-e500-4ce0-bd8b-44fded455dd2","owner":[],"postedDate":"August 8th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-20T15:59:36+00:00","versionOfRecord":{"articleIdentity":"rs-7114395","link":"https://doi.org/10.1007/s13760-025-02916-7","journal":{"identity":"acta-neurologica-belgica","isVorOnly":false,"title":"Acta Neurologica Belgica"},"publishedOn":"2025-10-13 15:57:03","publishedOnDateReadable":"October 13th, 2025"},"versionCreatedAt":"2025-08-08 16:20:54","video":"","vorDoi":"10.1007/s13760-025-02916-7","vorDoiUrl":"https://doi.org/10.1007/s13760-025-02916-7","workflowStages":[]},"version":"v1","identity":"rs-7114395","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7114395","identity":"rs-7114395","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}