pone.0258377.g002.tif (392.01 kB)
Development, calibration, and revision processes of the prediction model.
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posted on 2021-10-08, 17:30 authored by Beom Joon Kim, Keon-Joo Lee, Eun Lyeong Park, Kanta Tanaka, Masatoshi Koga, Sohei Yoshimura, Ryo Itabashi, Jae-Kwan Cha, Byung-Chul Lee, Hisanao Akiyama, Yoshinari Nagakane, Juneyoung Lee, Kazunori Toyoda, Hee-Joon BaeThe model’s predictive ability was compared to the 1-year cumulative incidence of recurrent stroke as stratified by the deciles of predicted risks. A. Observed and predicted probability of recurrent stroke in the developmental dataset (N = 5648). B. Observed and predicted probability in the external validation dataset (N = 3668) before and after calibrating the model’s overall slope. C. Observed and predicted probability in the external validation dataset (N = 3668) after revising the regression coefficients of the calibrated model.
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fine &# 8211detailed individual information3 ± 105648 registered cases16 %) diedconventional risk scores1165 japanese patientsacute ischemic strokedevelopmental dataset consistedexternal validation dataset66 ‒ 0predicting stroke recurrencemultivariable prediction modelkorean ais subjectsexternal validation setdeveloped prediction modeldevelopmental datasetstroke recurrencedeveloped using6 %)4483 koreanidentifying patientshigh riskcompeting riskais patientsstroke survivorsstroke mortalityrecurrent strokeindex strokefinal modelaf registeredxlink ">south korearevised usingnew strategiesmulticenter registriesmean ageincluding imagingevent outcomescontextual limitationsconfidence intervalclinical profilesatrial fibrillationalso created71 ).2 years1 year
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