Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study.
Risk Factors and Prediction of Stroke in a Population with High Prevalence of Diabetes: The Strong Heart Study.
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DOI：
10.4236/wjcd.2017.75014
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发表时间：
2017-05
期刊：
影响因子：
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通讯作者：
Stoner JA
中科院分区：
文献类型：
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作者：
Wang W;Zhang Y;Lee ET;Howard BV;Devereux RB;Cole SA;Best LG;Welty TK;Rhoades E;Yeh J;Ali T;Kizer JR;Kamel H;Shara N;Wiebers DO;Stoner JA
美国印第安人的糖尿病患病率和卒中发病率均高于美国白人和黑人，基于印第安人数据的中风风险预测模型具有临床和公共卫生价值。共有3,483名(2,043名女性)强心脏研究参与者在至2010年期间因卒中事件被跟踪研究。总体而言，确定了297例中风病例(179名女性)。以基线记录的卒中缓解时间和危险因素为指标的Cox模型用于建立卒中风险预测模型。分别使用类似的C统计量(C)和Hosmer-Lemesow统计量(HL)对所开发的卒中风险预测模型进行区分和校准评估，并使用自举方法进行内部验证。年龄、吸烟、饮酒、腰围、高血压、抗高血压治疗、空腹血糖、糖尿病药物、高密度脂蛋白/低密度脂蛋白、尿白蛋白/肌酐比值、冠心病/心衰、房颤或左室肥厚、父母卒中病史是发生卒中的最佳危险因素。模型对女性的预测结果为C=0.761和HL=4.668(p=0.792)，对男性的预测结果为C=0.765和HL=9.171(p=0.328)，显示出良好的区分性和校准性。我们的中风风险预测模型提供了为美国印第安人设计的中风风险评估机制。这些模型也可能对其他肥胖和/或糖尿病高发人群有用，用于筛查个人发生中风的风险并设计预防计划。
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. 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. 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. 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. 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.