Predictive model for early complications of acute myocardial infarction in patients with type 2 diabetes mellitus

Abstract

Introduction:Early complications of acute myocardial infarction (AMI) are one of the leading causes of death among patients with type 2 diabetes mellitus (DM). Clinical and laboratory characteristics and noninvasive methods need to be integrated to better identify early complications of AMI and further develop a treatment strategy. The aim of the study was to predict the development of early complications after AMI in type 2 DM patients, which could improve the quality of preventive and curative measures for this group of patients. Methods: In total, 109 patients with ST-elevation myocardial infarction (STEMI) and type 2 DM were included in the study: 75 men and 34 women. The training set (n = 74) was selected to study variables associated with the probability of early complications after AMI in type 2 DM patients. The model reproducibility was then checked on the validation set (n = 35). All patients underwent percutaneous coronary intervention (PCI). The training set identified 26 patients with early complications and 48 patients without early complications of AMI. The validation set identified 18 patients with early complications and 17 patients without early complications of AMI. The model for predicting early AMI complications was calculated using binary logistic regression. Results: The developed mathematical model for predicting early complications of AMI was as follows: Р = [1+ exp(-(0.030 × C1q tumor necrosis factor-related protein 3 (CTRP 3) (ng/ml) + 1.414 × respiratory rate (RR) (breaths per minute) + 0.322 × body mass index (BMI) (kg/m2) + 0.091× heart rate (HR) (beats per minute) -50.800))] −1 . The model yielded the highest results under the receiver operating characteristic curve for predicting early complications of AMI among the diabetic patients in both the training and validation groups (0.962 and 0.928, respectively). Conclusions : This study has shown that integral measurements of circulating CTRP 3 content, RR, BMI, and HR upon admission of STEMI patients with type 2 DM after PCI could predict early complications of AMI. These findings suggest a new approach to stratify the risk of early AMI complications in type 2 DM patients after successful coronary revascularization.

Predictive model for recurrent myocardial infarction in patients with type 2 diabetes mellitus

“…Moreover, hypertension, DM, increased systolic blood pressure, along with higher glucose levels have been believed to be associated with an increase in FABP4 circulating levels (Tsai et al, 2021). Finally, the authors have revealed lower serum concentration of CTRP3 in CHD patients, especially in acute MI (Si et al, 2020;Koteliukh et al, 2022). Therefore, the constructed prognostic model predicted the probability of the recurrent MI absence with a high accuracy of 98.4% and the probability of the recurrent MI with an accuracy of 92.3% in patients with 2 types DM within a year based on the measurement findings on the 1st and 14th day of observation.…”

Predictive Model for Acute Heart Failure in Patients with Acute Myocardial Infarction and Type 2 Diabetes Mellitus Based on Energy and Adipokine Metabolism Indicators

“…Low serum levels of CTRP3 were observed in patients with HF and reduced LV EF [25]. The authors underlined decreased CTRP3 serum levels in patients with CAD, especially in AMI [26], [27].…”