Key result
Gender-specific stroke risk prediction models incorporating age, smoking, blood pressure, albuminuria, and diabetes demonstrated good discrimination with C-statistics of 0.761 for women and 0.765 for men in an American Indian population.
Population
3,483 American Indian adults aged 45 to 74 years, free of stroke at baseline, from southwestern Oklahoma…
Design
Cohort
Follow-up
average 15.04 years (inter-quartile range 9.7 - 20.2 years)
Authors
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May support tailored stroke risk assessment in American Indians; leaves open external validation before clinical adoption.
Cohort (n=3,483)
Yes
Effect estimate: C-statistic 0.761 (women) and 0.765 (men)
A newly developed stroke risk prediction model tailored for American Indians demonstrated good discrimination and calibration, providing a population-specific tool for stroke risk assessment.
Wang et al. (2017) conducted a cohort in Stroke risk prediction (n=3,483). Multiple cardiovascular risk factors (including albuminuria and diabetes) vs. Baseline risk was evaluated on Incident stroke prediction (C-statistic) (C-statistic 0.761 (women) and 0.765 (men)). Gender-specific stroke risk prediction models incorporating age, smoking, blood pressure, albuminuria, and diabetes demonstrated good discrimination with C-statistics of 0.761 for women and 0.765 for men in an American Indian population.
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