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Risk scores for predicting incidence of type 2 diabetes in the Chinese population: the Kailuan prospective study

机译:开lu前瞻性研究预测中国人群2型糖尿病的风险评分

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Few risk scores have been specifically developed to identify individuals at high risk of type 2 diabetes in China. In the present study, we aimed to develop such risk scores, based on simple clinical variables. We studied a population-based cohort of 73,987 adults, aged 18 years and over. After 5.35?±?1.59 years of follow-up, 4,726 participants (9.58%) in the exploration cohort developed type 2 diabetes and 2,327 participants (9.44%) in the validation cohort developed type 2 diabetes. Age, gender, body mass index, family history of diabetes, education, blood pressure, and resting heart rate were selected to form the concise score with an area under the receiver operating characteristic curve (AUC) of 0.67. The variables in the concise score combined with fasting plasma glucose (FPG), and triglyceride (TG) or use of lipid-lowering drugs constituted the accurate score with an AUC value of 0.77. The utility of the two scores was confirmed in the validation cohort with AUCs of 0.66 and 0.77, respectively. In summary, the concise score, based on non-laboratory variables, could be used to identify individuals at high risk of developing diabetes within Chinese population; the accurate score, which also uses FPG and TG data, is better at identifying such individuals.
机译:很少有专门针对中国2型糖尿病高危人群的风险评分。在本研究中,我们旨在基于简单的临床变量来制定此类风险评分。我们研究了73987名年龄在18岁以上的成年人的人群。经过5.35±1.59年的随访,探索队列中的4,726名参与者(9.58%)患上了2型糖尿病,而验证队列中的2,327名参与者(9.44%)患了2型糖尿病。选择年龄,性别,体重指数,糖尿病家族史,受教育程度,血压和静息心率,以形成简洁的评分,受试者工作特征曲线(AUC)下的面积为0.67。简明评分中的变量与空腹血糖(FPG)和甘油三酸酯(TG)或使用降脂药的组合构成了准确评分,其AUC值为0.77。这两个分数的效用在验证队列中得到了确认,AUC分别为0.66和0.77。总之,基于非实验室变量的简洁评分可用于识别中国人群中罹患糖尿病的高风险人群;准确的分数也使用FPG和TG数据,可以更好地识别此类人员。

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