Abstract
Funding Acknowledgements
Type of funding sources: None.
Introduction
Acute myocardial infarction (AMI) and sudden cardiac death (SCD) are major cardiovascular adverse outcomes in patients with type 2 diabetic mellitus. Although there are many risk scores on composite outcomes of major cardiovascular adverse outcomes or cardiovascular mortality for diabetic patients, these existing scores did not account for the difference in pathogenesis and prognosis between acute coronary syndrome and lethal ventricular arrhythmias. Furthermore, recent studies reported that HbA1c and lipid levels, which were often accounted for in these risk scores, have J/U-shaped relationships with adverse outcomes.
Purpose
The present study aims to evaluate the application of incorporating non-linear J/U-shaped relationships between mean HbA1c and cholesterol levels into risk scores for predicting for AMI and non-AMI related SCD respectively, amongst type 2 diabetes mellitus patients.
Methods
This was a territory-wide cohort study of patients with type 2 diabetes mellitus above the age 40 and free from prior AMI and SCD, with or without prescriptions of anti-diabetic agents between January 1st, 2009 to December 31st, 2009 at government-funded hospitals and clinics in Hong Kong. Risk scores were developed for predicting incident AMI and non-AMI related SCD. The performance of conditional inference survival forest (CISF) model compared to that of random survival forests (RSF) model and multivariate Cox model.
Results
This study included 261308 patients (age = 66.0 ± 11.8 years old, male = 47.6%, follow-up duration = 3552 ± 1201 days, diabetes duration = 4.77 ± 2.29 years). Mean HbA1c and high-density lipoprotein-cholesterol (HDL-C) were significant predictors of AMI under multivariate Cox regression and were linearly associated with AMI. Mean HbA1c and total cholesterol were significant multivariate predictors with a J-shaped relationship with non-AMI related SCD. The AMI and SCD risk scores had an area-under-the-curve (AUC) of 0.666 (95% confidence interval (CI)= [0.662, 0.669]) and 0.677 (95% CI= [0.673, 0.682]), respectively. CISF significantly improves prediction performance of both outcomes compared to RSF and multivariate Cox models.
Conclusions
A holistic combination of demographic, clinical, and laboratory indices can be used for the risk stratification of type 2 diabetic patients against AMI and SCD.
Improved Framingham Risk Scores of Patients with Type 2 Diabetes Mellitus in the Beijing Community: A 10-Year Prospective Study of the Effects of Multifactorial Interventions on Cardiovascular Risk Factors (The Beijing Communities Diabetes Study 22)
