ArticleFrontiers in neurology2026
Co-recorded conditions in ischemic and hemorrhagic stroke: a 20-year national analysis of 598,186 natural deaths with machine learning.
Article in Frontiers in neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
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 1-3) compared to hemorrhagic stroke (median 1, IQR 1-2;
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