Development of a cardiovascular diseases risk prediction model and tools for Chinese patients with type 2 diabetes mellitus: A population‐based retrospective cohort study. Issue 2 (25th August 2017)

• Record Type: Journal Article
• Authors: Wan, Eric Yuk Fai; Fong, Daniel Yee Tak; Fung, Colman Siu Cheung; Yu, Esther Yee Tak; Chin, Weng Yee; Chan, Anca Ka Chun; Lam, Cindy Lo Kuen
• Is Part Of: Diabetes, obesity & metabolism. Volume 20:Issue 2(2018)
• Page Start: 309
• Page End: 318
• Publication Date: 2017-08-25
• Subjects: cardiovascular diseases -- prediction -- primary care -- risk -- type 2 diabetes mellitus; Diabetes -- Periodicals; Obesity -- Periodicals; Metabolism -- Disorders -- Periodicals; Clinical pharmacology -- Periodicals; 616.462
• DOI: 10.1111/dom.13066
• Languages: English
• ISSNs: 1462-8902

Abstract

Abstract : Aims: 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. Methods: 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. Results: 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. Conclusion: 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.