All-cause mortality prediction models in type 2 diabetes: applicability in the early stage of disease

2型糖尿病全因死亡率预测模型:在疾病早期阶段的适用性

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Abstract

AIMS: The rate of all-cause mortality is twofold higher in type 2 diabetes than in the general population. Being able to identify patients with the highest risk from the very beginning of the disease would help tackle this burden. METHODS: We tested whether ENFORCE, an established prediction model of all-cause mortality in type 2 diabetes, performs well also in two independent samples of patients with early-stage disease prospectively followed up. RESULTS: ENFORCE's survival C-statistic was 0.81 (95%CI: 0.72-0.89) and 0.78 (95%CI: 0.68-0.87) in both samples. Calibration was also good. Very similar results were obtained with RECODe, an alternative prediction model of all-cause mortality in type 2 diabetes. CONCLUSIONS: In conclusion, our data show that two well-established prediction models of all-cause mortality in type 2 diabetes can also be successfully applied in the early stage of the disease, thus becoming powerful tools for educated and timely prevention strategies for high-risk patients.

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