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Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study
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. METHODS AND RESULTS: A total of 3483...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538319/ https://www.ncbi.nlm.nih.gov/pubmed/28775914 http://dx.doi.org/10.4236/wjcd.2017.75014 |
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author | Wang, Wenyu Zhang, Ying Lee, Elisa T. Howard, Barbara V. Devereux, Richard B. Cole, Shelley A. Best, Lyle G. Welty, Thomas K. Rhoades, Everett Yeh, Jeunliang Ali, Tauqeer Kizer, Jorge R. Kamel, Hooman Shara, Nawar Wiebers, David O. Stoner, Julie A. |
author_facet | Wang, Wenyu Zhang, Ying Lee, Elisa T. Howard, Barbara V. Devereux, Richard B. Cole, Shelley A. Best, Lyle G. Welty, Thomas K. Rhoades, Everett Yeh, Jeunliang Ali, Tauqeer Kizer, Jorge R. Kamel, Hooman Shara, Nawar Wiebers, David O. Stoner, Julie A. |
author_sort | Wang, Wenyu |
collection | PubMed |
description | 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. 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. 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. 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. |
format | Online Article Text |
id | pubmed-5538319 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
record_format | MEDLINE/PubMed |
spelling | pubmed-55383192017-08-01 Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study Wang, Wenyu Zhang, Ying Lee, Elisa T. Howard, Barbara V. Devereux, Richard B. Cole, Shelley A. Best, Lyle G. Welty, Thomas K. Rhoades, Everett Yeh, Jeunliang Ali, Tauqeer Kizer, Jorge R. Kamel, Hooman Shara, Nawar Wiebers, David O. Stoner, Julie A. World J Cardiovasc Dis Article 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. 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. 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. 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. 2017-05-27 2017-05 /pmc/articles/PMC5538319/ /pubmed/28775914 http://dx.doi.org/10.4236/wjcd.2017.75014 Text en http://creativecommons.org/licenses/by/4.0/ This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Wenyu Zhang, Ying Lee, Elisa T. Howard, Barbara V. Devereux, Richard B. Cole, Shelley A. Best, Lyle G. Welty, Thomas K. Rhoades, Everett Yeh, Jeunliang Ali, Tauqeer Kizer, Jorge R. Kamel, Hooman Shara, Nawar Wiebers, David O. Stoner, Julie A. Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study |
title | Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study |
title_full | Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study |
title_fullStr | Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study |
title_full_unstemmed | Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study |
title_short | Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study |
title_sort | risk factors and prediction of stroke in a population with high prevalence of diabetes: the strong heart study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5538319/ https://www.ncbi.nlm.nih.gov/pubmed/28775914 http://dx.doi.org/10.4236/wjcd.2017.75014 |
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