Predictive Accuracy of Stroke Risk Prediction Models Across Black and White Race, Sex, and Age Groups

Stroke is the fifth-highest cause of death in the US and a leading cause of serious long-term disability with particularly high risk in Black individuals. Quality risk prediction algorithms, free of bias, are key for comprehensive prevention strategies. To compare the performance of stroke-specific...

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Bibliographic Details
Published in:	JAMA : the journal of the American Medical Association Vol. 329; no. 4; p. 306
Main Authors:	Hong, Chuan, Pencina, Michael J, Wojdyla, Daniel M, Hall, Jennifer L, Judd, Suzanne E, Cary, Michael, Engelhard, Matthew M, Berchuck, Samuel, Xian, Ying, D'Agostino, Sr, Ralph, Howard, George, Kissela, Brett, Henao, Ricardo
Format:	Journal Article
Language:	English
Published:	United States 24.01.2023
Subjects:	Age Factors Atherosclerosis - epidemiology Bias Black or African American Black People - statistics & numerical data Cardiovascular Diseases - epidemiology Computer Simulation - standards Computer Simulation - statistics & numerical data Female Healthcare Disparities - ethnology Healthcare Disparities - standards Healthcare Disparities - statistics & numerical data Humans Ischemic Attack, Transient - epidemiology Machine Learning - standards Male Middle Aged Prejudice - prevention & control Race Factors - statistics & numerical data Reproducibility of Results Retrospective Studies Risk Assessment - standards Sex Factors Stroke - diagnosis Stroke - epidemiology Stroke - ethnology United States - epidemiology White People - statistics & numerical data United States
ISSN:	1538-3598, 1538-3598
Online Access:	Get more information
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