{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,8]],"date-time":"2026-10-08T08:55:42Z","timestamp":1791449742991,"version":"4.3.3"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T00:00:00Z","timestamp":1787961600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100001003","name":"Boehringer Ingelheim GmbH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001003","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Aims<\/jats:title>\n                    <jats:p>Accurate stroke risk stratification is central to anticoagulation decision-making in patients with atrial fibrillation (AF), but conventional scores may not fully capture risk heterogeneity. We aimed to develop and externally validate an interpretable weighted score using a time-to-event framework.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods and results<\/jats:title>\n                    <jats:p>GLORIA-AF Phase II\/III data were used to evaluate 17 baseline predictors using LASSO-penalized Cox regression with stability selection; coefficients were converted into integer weights. Performance was assessed using discrimination, calibration, integrated discrimination improvement (IDI), continuous net reclassification improvement (NRI), and decision curve analysis. External validation was performed in EORP-AF and APHRS-AF registries. Among 20 517 patients included in the derivation cohort [mean (SD) age, 69.9 (10.3) years; 9196 women (44.8%)], 487 (2.4%) had stroke, and 17 397 (84.8%) were receiving anticoagulation at baseline. Ten selected predictors formed a 0\u201323-point score. The derived score achieved a C-index of 0.661 (95% CI, 0.636\u20130.685), higher than CHA2DS2-VA (0.626; P &amp;lt; 0.001), CHA2DS2-VASc (0.615; P &amp;lt; 0.001), and the unweighted score (P = 0.016), with no significant difference from the full Cox or machine learning models. In external validation (8309 patients; 147 strokes), the C-index was 0.652 (95% CI, 0.614\u20130.690) vs. 0.616 for CHA2DS2-VA (95% CI, 0.598\u20130.634; P &amp;lt; 0.001). IDI\/NRI, calibration, and decision curve analyses supported improved risk differentiation, close calibration, and generally greater net benefit than CHA2DS2-VA. The score retained higher discrimination than CHA2DS2-VA among patients without baseline anticoagulation (P &amp;lt; 0.001).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The GLORIA-AF Stroke Weighted Risk Score provides risk refinement beyond CHA2DS2-VA while retaining discrimination consistent with more complex models. External validation supports its transportability and potential adjunctive role in guideline-directed thromboembolic risk assessment.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/europace\/euag236","type":"journal-article","created":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T13:57:09Z","timestamp":1788011829000},"source":"Crossref","is-referenced-by-count":0,"title":["Development and validation of the GLORIA-AF Stroke Weighted Risk Score for patients with atrial fibrillation"],"prefix":"10.1093","volume":"28","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-7250-7759","authenticated-orcid":false,"given":"Yifan","family":"Xie","sequence":"first","affiliation":[{"name":"Institute of Life Course and Medical Sciences, University of Liverpool , William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX ,","place":["UK"]},{"name":"Faculty of Environment, Science and Economy, University of Exeter , Exeter ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0772-2575","authenticated-orcid":false,"given":"Wenhui","family":"Li","sequence":"additional","affiliation":[{"name":"Institute of Life Course and Medical Sciences, University of Liverpool , William Henry Duncan Building, 6 West Derby Street, Liverpool L7 8TX ,","place":["UK"]},{"name":"Faculty of Environment, Science and Economy, University of Exeter , Exeter ,","place":["UK"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7344-2174","authenticated-orcid":false,"given":"Yanda","family":"Meng","sequence":"additional","affiliation":[{"name":"Bioengineering Program, Division of Biomedical Sciences, King Abdullah University of Science and Technology , Thuwal ,","place":["Saudi 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,","place":["The Netherlands"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9820-4815","authenticated-orcid":false,"given":"Giuseppe","family":"Boriani","sequence":"additional","affiliation":[{"name":"Cardiology Division, Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia , Modena ,","place":["Italy"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7461-2793","authenticated-orcid":false,"given":"Tze-Fan","family":"Chao","sequence":"additional","affiliation":[{"name":"Cardiovascular Center, Taipei Veterans General Hospital , No. 201, Sec. 2, Shih-Pai Road, Taipei 112201 ,","place":["Taiwan"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7566-1626","authenticated-orcid":false,"given":"Gregory Y H","family":"Lip","sequence":"additional","affiliation":[{"name":"Institute of Life Course and Medical 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