Interrelation between the relative fat mass index and other obesity indices in predicting clinical severity and prognosis of acute myocardial infarction

Introduction

Central obesity is directly associated with insulin resistance, dyslipidemia and inflammation, which lead to atherosclerotic vascular disease [1]. There is a positive association of central obesity, as well as a negative association of overall obesity, with higher mortality in acute coronary syndrome, as body mass index (BMI) does not adequately discriminate the difference between body fat and lean muscle mass [2]. The newest obesity parameter, the relative fat mass index (RFMI), was more accurate for body fat-defined obesity and more accurate than BMI for those with a high body fat percentage [3].

Aim

We investigated the unknown interrelation between the RFMI and other obesity indices in predicting clinical severity and prognosis of acute ST-elevation myocardial infarction (STEMI) treated with primary percutaneous coronary intervention (PCI).

Material and methods

This prospective study, approved by the appropriate ethics committee, included 250 patients with acute STEMI treated with primary PCI. The inclusion criteria were: presenting within 12 h from the onset of symptoms (history of chest pain/discomfort lasting for 10–20 min or more, not responding fully to nitroglycerine), persistent ST-segment elevation on electrocardiography (ECG) in at least two consecutive leads or (presumed) new left bundle branch block (LBBB), and elevated cardiac laboratory biomarkers (cardiac troponin T (cTnT) and creatine kinase (CK)). The diagnosis of acute STEMI was established and primary PCI performed using the European Society of Cardiology criteria [4, 5]. After primary PCI, patients were classified into two groups (with/without RFMI obesity) which were analyzed by baseline, as well as severity and prognostic parameters of acute STEMI.
Baseline demographic and medical history parameters included gender, age, hypertension, dyslipidemia, hyperglycemia, anthropometry, smoking, known family history of cardiovascular events (MI, stroke), previous MI, previous PCI and coronary artery bypass grafting (CABG). Anthropometric baseline data included BMI, waist circumference (WC), waist-to-hip (WHR) and waist-to-height ratio (WHtR). RFMI was calculated using the equation RFMI = 64 – (20 × height/waist) + (12 × sex), where sex = 0 for men and 1 for women [3]. Increased RFMI values were defined as ≥ 25%, ≥ 28% and ≥ 30% for males aged 20–39, 40–59 and 60–79 years, respectively. For females, increased RFMI values were defined as...


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