Department of Family Medicine and Primary Care, The University of Hong Kong, Ap Lei Chau, Hong Kong.
Department of Surgery, School of Nursing, The University of Hong Kong, Ap Lei Chau, Hong Kong.
Diabetes Obes Metab. 2018 Feb;20(2):309-318. doi: 10.1111/dom.13066. Epub 2017 Aug 25.
Evidence-based cardiovascular diseases (CVD) risk prediction models and tools specific for Chinese patients with type 2 diabetes mellitus (T2DM) are currently unavailable. This study aimed to develop and validate a CVD risk prediction model for Chinese T2DM patients.
A retrospective cohort study was conducted with 137 935 Chinese patients aged 18 to 79 years with T2DM and without prior history of CVD, who had received public primary care services between January 1, 2010 and December 31, 2010. Using the derivation cohort over a median follow-up of 5 years, the interaction effect between predictors and age were derived using Cox proportional hazards regression with a forward stepwise approach. Harrell's C statistic and calibration plot were used on the validation cohort to assess the discrimination and calibration of the models. The web calculator and chart were developed based on the developed models.
For both genders, predictors for higher risk of CVD were older age, smoking, longer diabetes duration, usage of anti-hypertensive drug and insulin, higher body mass index, haemoglobin A1c (HbA1c), systolic and diastolic blood pressure, a total cholesterol to high-density lipoprotein-cholesterol (TC/HDL-C) ratio and urine albumin to creatinine ratio, and lower estimated glomerular filtration rate. Interaction factors with age demonstrated a greater weighting of TC/HDL-C ratio in both younger females and males, and smoking status and HbA1c in younger males.
The developed models, translated into a web calculator and color-coded chart, served as evidence-based visual aids that facilitate clinicians to estimate quickly the 5-year CVD risk for Chinese T2DM patients and to guide intervention.
目前缺乏针对中国 2 型糖尿病(T2DM)患者的基于证据的心血管疾病(CVD)风险预测模型和工具。本研究旨在开发和验证适用于中国 T2DM 患者的 CVD 风险预测模型。
本回顾性队列研究纳入了 137935 例年龄在 18 至 79 岁、无 CVD 病史且接受过公共初级保健服务的中国 T2DM 患者,这些患者于 2010 年 1 月 1 日至 2010 年 12 月 31 日期间就诊。通过对中位随访 5 年的推导队列,采用逐步向前的 Cox 比例风险回归方法得出预测因素与年龄之间的交互作用。使用验证队列的 Harrell's C 统计量和校准图评估模型的区分度和校准度。基于开发的模型开发了网络计算器和图表。
对于两性,CVD 风险较高的预测因素包括年龄较大、吸烟、糖尿病病程较长、使用抗高血压药物和胰岛素、体重指数较高、糖化血红蛋白(HbA1c)、收缩压和舒张压、总胆固醇与高密度脂蛋白胆固醇(TC/HDL-C)比值以及尿白蛋白与肌酐比值,以及估算肾小球滤过率较低。与年龄的交互因素显示,年轻女性和男性的 TC/HDL-C 比值权重更大,年轻男性的吸烟状况和 HbA1c 权重更大。
开发的模型转化为网络计算器和彩色图表,作为基于证据的可视化工具,可帮助临床医生快速估计中国 T2DM 患者 5 年内 CVD 风险,并指导干预。