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Optimization of sudden cardiac death prevention in type 2 diabetes in France : a public health simulation study on a realistic virtual population

Abstract : Type 2 diabetes (T2D) has increasingly become a common metabolic condition, associated with numerous micro and macro-vascular complications. Diabetic patients are at about two-time higher risk of sudden cardiac death (SCD), compared to non-diabetic ones. Pharmacologic intervention (anti-platelet, anti-hypertensive, lipid lowering, and to a lesser extent, anti-diabetic agents) appear to be the most efficient and economic candidate to prevent this event at long term, yet treatment effects have not well addressed. We aimed to optimize their use and estimate their impact on public health via analysis, synthesis and modeling studies.This work engaged three phases: First, to construct a risk score to predict SCD risk in T2D from the INDANA database. Second, to perform the meta-analyses/systematic reviews of different therapeutic strategies in order to estimate their effects on SCD risk. Finally, to simulate therapeutic strategies on a generated French diabetic realistic virtual population (RVP) of T2D, by estimating the occurrence of SCD with and without treatments, thus their absolute benefits, through the Number of Events Prevented (NEP) due to treatment, and the Number of patients Needed to be Treated to prevent one SCD (NNT).We built a 7-risk factor to predict 5-year risk of SCD in patients with hypertension (+/-diabetes) and collected the best evidence on drugs’ effects. Integrating and simulating altogether on a generated French diabetic RVP suggested that for every 57 individuals of the 10% highest predicted SCD risk, the co-prescription of angiotensin converting enzyme inhibitor-aspirin-empagliflozin could prevent one SCD in 5 years. For the whole population, the corresponding number was 135. In perspectives, this approach could help better transposing clinical trial results into practice and facilitating clinical decision at both public health and individual levels
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Submitted on : Monday, February 12, 2018 - 2:02:05 PM
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  • HAL Id : tel-01706965, version 1



Hai-Ha Le. Optimization of sudden cardiac death prevention in type 2 diabetes in France : a public health simulation study on a realistic virtual population. Pharmacology. Université de Lyon, 2017. English. ⟨NNT : 2017LYSE1188⟩. ⟨tel-01706965⟩



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