Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study.

MedStar author(s):
Citation: World Journal of Cardiovascular Diseases. 7(5):145-162, 2017 MayPMID: 28775914Institution: MedStar Health Research InstituteForm of publication: Journal ArticleMedline article type(s): Journal ArticleSubject headings: PubMed-not-MEDLINE -- Not indexedYear: 2017ISSN:
  • 2164-5329
Name of journal: World Journal of Cardiovascular DiseasesAbstract: BACKGROUND AND OBJECTIVE: American Indians have a high prevalence of diabetes and higher incidence of stroke than that of whites and blacks in the U.S. Stroke risk prediction models based on data from American Indians would be of clinical and public health value.CONCLUSIONS: Our stroke risk prediction models provide a mechanism for stroke risk assessment designed for American Indians. The models may be also useful to other populations with high prevalence of obesity and/or diabetes for screening individuals for risk of incident stroke and designing prevention programs.DISCUSSION: The models produced a C = 0.761 and HL = 4.668 (p = 0.792) for women, and a C = 0.765 and HL = 9.171 (p = 0.328) for men, showing good discrimination and calibration.METHODS AND RESULTS: A total of 3483 (2043 women) Strong Heart Study participants free of stroke at baseline were followed from 1989 to 2010 for incident stroke. Overall, 297 stroke cases (179 women) were identified. Cox models with stroke-free time and risk factors recorded at baseline were used to develop stroke risk prediction models. Assessment of the developed stroke risk prediction models regarding discrimination and calibration was performed by an analogous C-statistic (C) and a version of the Hosmer-Lemeshow statistic (HL), respectively, and validated internally through use of Bootstrapping methods.RESULTS: Age, smoking status, alcohol consumption, waist circumference, hypertension status, an-tihypertensive therapy, fasting plasma glucose, diabetes medications, high/low density lipoproteins, urinary albumin/creatinine ratio, history of coronary heart disease/heart failure, atrial fibrillation, or Left ventricular hypertrophy, and parental history of stroke were identified as the significant optimal risk factors for incident stroke.All authors: Ali T, Best LG, Cole SA, Devereux RB, Howard BV, Kamel H, Kizer JR, Lee ET, Rhoades E, Shara N, Stoner JA, Wang W, Welty TK, Wiebers DO, Yeh J, Zhang YFiscal year: F { !#/&O2Digital Object Identifier: Date added to catalog: 2017-08-23
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Journal Article MedStar Authors Catalog Article 28775914 Available 28775914

BACKGROUND AND OBJECTIVE: American Indians have a high prevalence of diabetes and higher incidence of stroke than that of whites and blacks in the U.S. Stroke risk prediction models based on data from American Indians would be of clinical and public health value.

CONCLUSIONS: Our stroke risk prediction models provide a mechanism for stroke risk assessment designed for American Indians. The models may be also useful to other populations with high prevalence of obesity and/or diabetes for screening individuals for risk of incident stroke and designing prevention programs.

DISCUSSION: The models produced a C = 0.761 and HL = 4.668 (p = 0.792) for women, and a C = 0.765 and HL = 9.171 (p = 0.328) for men, showing good discrimination and calibration.

METHODS AND RESULTS: A total of 3483 (2043 women) Strong Heart Study participants free of stroke at baseline were followed from 1989 to 2010 for incident stroke. Overall, 297 stroke cases (179 women) were identified. Cox models with stroke-free time and risk factors recorded at baseline were used to develop stroke risk prediction models. Assessment of the developed stroke risk prediction models regarding discrimination and calibration was performed by an analogous C-statistic (C) and a version of the Hosmer-Lemeshow statistic (HL), respectively, and validated internally through use of Bootstrapping methods.

RESULTS: Age, smoking status, alcohol consumption, waist circumference, hypertension status, an-tihypertensive therapy, fasting plasma glucose, diabetes medications, high/low density lipoproteins, urinary albumin/creatinine ratio, history of coronary heart disease/heart failure, atrial fibrillation, or Left ventricular hypertrophy, and parental history of stroke were identified as the significant optimal risk factors for incident stroke.

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