{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T14:38:24Z","timestamp":1786113504165,"version":"build-2736575974"},"reference-count":30,"publisher":"Ovid Technologies (Wolters Kluwer Health)","issue":"7","content-domain":{"domain":["www.ahajournals.org"],"crossmark-restriction":true},"short-container-title":["Stroke"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>BACKGROUND:<\/jats:title>\n                    <jats:p>As life expectancy rises, identifying causes and risk factors for incident acute ischemic stroke (AIS) among the oldest-old (\u226580 years) is increasingly important. We examined whether the effect of age at stroke on AIS subtype is mediated by embolic risk factors and whether these factors improve AIS prediction.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS:<\/jats:title>\n                    <jats:p>\n                      Stroke-free participants from the ARIC study (Atherosclerosis Risk in Communities) who developed AIS between visit 5 (2011\u20132013) and visit 10 (2023) were included for causal analysis; Stroke-free participants at visit 5 were included for prediction analysis. In logistics regression models, the association between age at stroke-onset (\u226580 versus &lt;80 years) and adjudicated AIS subtype (embolic ischemic stroke versus thrombotic ischemic stroke) was determined. Bootstrapped mediation analyses (1000-iterations) tested whether atrial fibrillation, myocardial infarction, coronary heart disease, heart failure, and electro\/echocardiogram measures mediated the age-AIS subtype relationship. C statistics were calculated for AIS prediction (Predicting Risk of Cardiovascular Disease Events, CHA\n                      <jats:sub>2<\/jats:sub>\n                      DS\n                      <jats:sub>2<\/jats:sub>\n                      -VASc) and compared preinclusion and postinclusion of embolic risk factors.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS:<\/jats:title>\n                    <jats:p>\n                      Of 6213 stroke-free participants at visit 5, 277 (4.4%) developed AIS during a median (Q1\u2013Q3) of 5.1 (2.6\u20137.1) years (median [Q1\u2013Q3] age: 76 [72\u201380] years; median [Q1\u2013Q3] age at AIS: 81 [77\u201386] years; 62% female; 99 embolic ischemic stroke and 178 thrombotic ischemic stroke). Individuals with AIS \u226580 years had higher odds of embolic ischemic stroke (versus thrombotic ischemic stroke) compared with those aged &lt;80 years (odds ratio, 1.90 [95% CI, 1.09\u20133.31]). The effect of age at stroke-onset on embolic ischemic stroke was mediated by atrial fibrillation (44%;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.03), an abnormal left atrium volume index (45%;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.048), or an abnormal P-wave axis (43%;\n                      <jats:italic toggle=\"yes\">P<\/jats:italic>\n                      =0.04). The predictive performance for AIS \u226580 years using the Predicting Risk of Cardiovascular Disease Events equation (N=5702, C statistic, 0.49 [95% CI, 0.45\u20130.53]), or CHA\n                      <jats:sub>2<\/jats:sub>\n                      DS\n                      <jats:sub>2<\/jats:sub>\n                      -VASc score (N=5739, C statistic, 0.57 [95% CI, 0.55\u20130.59]) was poor, but inclusion of embolic risk factors improved the performance (Predicting Risk of Cardiovascular Disease Events: C statistics, 0.77 [95% CI, 0.74\u20130.80]; CHA\n                      <jats:sub>2<\/jats:sub>\n                      DS\n                      <jats:sub>2<\/jats:sub>\n                      -VASc: C statistics, 0.63 [95% CI, 0.59\u20130.67]).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS:<\/jats:title>\n                    <jats:p>These findings suggest that identification and control of embolic risk factors are critical to reduce stroke risk as people age, and better stroke-specific prediction tools are needed.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1161\/strokeaha.125.054194","type":"journal-article","created":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T09:00:12Z","timestamp":1777539612000},"page":"2076-2084","update-policy":"https:\/\/doi.org\/10.1161\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Late-Life Incident Stroke in the Atherosclerosis Risk in Communities Study: Etiology and Prediction"],"prefix":"10.1161","volume":"57","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-9322-1106","authenticated-orcid":true,"given":"Jing","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Neurology (J.W., M.C.J.), The Johns Hopkins University School of Medicine, Baltimore, MD."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marco","family":"Egle","sequence":"additional","affiliation":[{"name":"Cognition and Neuroepidemiology Section, National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD (M.E., R.F.G.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-1846-3217","authenticated-orcid":true,"given":"Zhenghao","family":"Jin","sequence":"additional","affiliation":[{"name":"Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD (Z.J.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8564-8986","authenticated-orcid":true,"given":"Kamakshi","family":"Lakshminarayan","sequence":"additional","affiliation":[{"name":"Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis (K.L.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1603-282X","authenticated-orcid":true,"given":"Chiadi E.","family":"Ndumele","sequence":"additional","affiliation":[{"name":"Department of Cardiology (C.E.N.), The Johns Hopkins University School of Medicine, Baltimore, MD."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4598-0669","authenticated-orcid":true,"given":"Josef","family":"Coresh","sequence":"additional","affiliation":[{"name":"Department of Population Health, New York University Grossman School of Medicine (J.C.)."}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9504-1256","authenticated-orcid":true,"given":"Rebecca F.","family":"Gottesman","sequence":"additional","affiliation":[{"name":"Cognition and Neuroepidemiology Section, National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD (M.E., 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