{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T05:02:32Z","timestamp":1790226152157,"version":"4.1.0"},"reference-count":44,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T00:00:00Z","timestamp":1790208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurol."],"abstract":"<jats:p>\n                    The purpose of this study was to characterize the co-occurrence patterns of co-recorded conditions in ischemic and hemorrhagic stroke and identify co-recorded conditions using a large national dataset of fatal, subtype-confirmed stroke cases from Brazil. We analyzed 598,186 natural deaths recorded in the Brazilian Mortality Information System (SIM) between 2000 and 2019, comprising 288,724 (48.3%) hemorrhagic and 309,462 (51.7%) ischemic stroke. Hierarchical clustering was performed to identify co-recorded condition clusters, while association rule mining using the Apriori algorithm uncovered hidden patterns of disease co-occurrence. Logistic regression, random forest, and XGBoost models were developed to classify stroke subtype based on demographic characteristics and co-recorded condition profiles. Ischemic stroke patients had significantly higher co-recorded condition burden (median 2, IQR 1\u20133) compared to hemorrhagic stroke (median 1, IQR 1\u20132;\n                    <jats:italic>p<\/jats:italic>\n                    \u202f&amp;lt;\u202f0.001). For hemorrhagic stroke, 12 association rules were identified; the strongest involved co-occurrence of infectious and respiratory diseases (e.g., {hypertension\u202f=\u202fYes, infectious_disease\u202f=\u202fYes}\u202f\u2192\u202f{respiratory_disease\u202f=\u202fYes}, lift\u202f=\u202f2.57) and of endocrine\/metabolic conditions with hypertension (lift\u202f=\u202f1.67), whereas the rule {mental_disorders\u202f=\u202fYes}\u202f\u2192\u202f{hypertension\u202f=\u202fYes} (lift\u202f=\u202f1.27, confidence\u202f=\u202f53.9%) was the weakest of the 12 rules. In contrast, ischemic stroke yielded 8 rules reflecting associations among infectious, respiratory, genitourinary, and endocrine\/metabolic conditions. The logistic regression model achieved an AUC of 0.768 for predicting stroke subtype, with consistent performance across sensitivity analyses. Age-standardized analyses showed that ischemic stroke proportion increased from 48.8 to 51.5% over 20\u202fyears, with approximately half of the crude increase attributable to population aging (crude ischemic proportion reached 54.7%). Co-recorded condition burden increased substantially in both subtypes (\u22653 co-recorded conditions in ischemic stroke: 24.8\u201333.3%). We observed that hemorrhagic and ischemic stroke have different co-occurrence patterns of co-recorded conditions: hemorrhagic stroke exhibited simpler co-occurrence patterns centered on hypertension together with infectious, respiratory, and endocrine\/metabolic conditions, while ischemic stroke was characterized by clustered cardiovascular and metabolic multimorbidity. These findings warrant further investigation in prospective studies.\n                  <\/jats:p>","DOI":"10.3389\/fneur.2026.1854246","type":"journal-article","created":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T04:38:28Z","timestamp":1790224708000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Co-recorded conditions in ischemic and hemorrhagic stroke: a 20-year national analysis of 598,186 natural deaths with machine learning"],"prefix":"10.3389","volume":"17","author":[{"given":"Junlin","family":"Ge","sequence":"first","affiliation":[{"name":"Department of Neurology, Yuechi County People\u2019s Hospital","place":["Guang\u2019an City, Sichuan Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hangang","family":"Jiang","sequence":"additional","affiliation":[{"name":"Department of Neurology, Yuechi County People\u2019s Hospital","place":["Guang\u2019an City, Sichuan Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Fu","sequence":"additional","affiliation":[{"name":"Department of Neurology, Yuechi County People\u2019s Hospital","place":["Guang\u2019an City, Sichuan Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hua","family":"Tian","sequence":"additional","affiliation":[{"name":"Department of Neurology, Yuechi County People\u2019s Hospital","place":["Guang\u2019an City, Sichuan Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wencheng","family":"Yuan","sequence":"additional","affiliation":[{"name":"Department of Neurology, Yuechi County People\u2019s Hospital","place":["Guang\u2019an City, Sichuan Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingyun","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Neurology, Yuechi County People\u2019s Hospital","place":["Guang\u2019an City, Sichuan Province, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,24]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"795","DOI":"10.1016\/S1474-4422(21)00252-0","article-title":"Global, regional, and national burden of stroke and its risk factors, 1990-2019: a systematic analysis for the global burden of disease study 2019","volume":"20","year":"2021","journal-title":"Lancet Neurol"},{"key":"ref2","doi-asserted-by":"publisher","first-page":"1811","DOI":"10.1016\/S0140-6736(25)01917-8","article-title":"Global burden of 292 causes of death in 204 countries and territories and 660 subnational locations, 1990-2023: a systematic analysis for the global burden of disease study 2023","volume":"406","year":"2025","journal-title":"Lancet"},{"key":"ref3","doi-asserted-by":"publisher","first-page":"946","DOI":"10.1177\/17474930221123175","article-title":"Global stroke statistics 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