Prediction of the long-term risk of adverse cardiovascular events after an episode of acute coronary syndrome in patients with type 2 diabetes

Aim. To determine independent predictors of adverse cardiovascular events (ACE) and to develop a long-term (12 months) prognostic model after an episode of acute coronary syndrome (ACS) in patients with type 2 diabetes (T2D).

Material and methods. The study included 120 T2D patients hospitalized due to ACS in the period from January 2016 to February 2017. All patients underwent standard diagnostic tests. Twelve months after ACS, the incidence of ACE in T2D patients was assessed: cardiovascular mortality, myocardial infarction, emergency surgical revascularization. Additionally, we analyzed composite endpoint (CEP), including all of the adverse outcomes listed. Patients were divided into 2 groups: group 1 (n=34) — patients with ACE; group 2 (n=86) — patients without ACE. Factors associated with the CEP were then included in the logistic regression to determine independent predictors of ACE. In order to predict the development of CEP in patients with ACS and T2D, a logit model was created. To process the model, a ROC analysis was performed.

Results. Independent factors associated with ACE for 12 months in T2D patients after an ACS were established: MI of moderate severity (D.M. Aronov classification); hypertriglyceridemia; decreased heart rate variability (SDNN <0 ms); segments with significant coronary stenosis in the amount of ≥3; no surgical revascularization during acute MI. Based on independent factors, a logit model was developed for assessing 12-month risk of ACE in T2D patients after an ACS.

Conclusion. The developed risk prediction model for T2D patients after ACS, based on accessible diagnostic tests, allows to determine the probability of ACE within 12 months.

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