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10 January 2020 : Clinical Research  

Body Mass Index and Major Adverse Cardiovascular Events: A Secondary Analysis Based on a Retrospective Cohort Study

Xiaobo Liu1ABCDEFG, Peng Liu2ABCDEFG*

DOI: 10.12659/MSM.919700

Med Sci Monit 2020; 26:e919700


BACKGROUND: The association between body mass index (BMI) and major adverse cardiovascular events (MACE) has not been clarified and is controversial. Therefore, the purpose of present study is to explore the association between BMI and MACE.

MATERIAL AND METHODS: This was a secondary analysis of a retrospective cohort study in which 204 participants who were diagnosed with stable coronary artery disease (CAD) and received elective percutaneous coronary intervention (PCI) were recruited. According to the BMI, patients were divided into 3 categories – underweight (BMI <18.5 kg/m²), normal BMI (18.5 ≤BMI <25 kg/m²), and overweight (BMI ≥25 kg/m²)], and the patients were followed up. The primary endpoint was MACE.

RESULTS: After a median follow-up of 783 days, MACE events had occurred in 18 participants. After controlling for potential confounding factors, no difference was observed in MACE between the underweight group and the normal BMI group (OR=1.73, 95% CI 0.42 to 7.17); but there were significantly fewer MACE in the overweight group than in the normal BMI group (OR=0.17; 95% CI: 0.03 to 0.84). Pearson correlation analysis showed that BMI was positively correlated with hemoglobin (r=0.2102) and albumin (r=0.2780), but negatively correlated with high-density lipoprotein cholesterol (r=–0.2052). The receiver operating characteristic curve (ROC) showed that the best threshold for BMI to predict MACE was 24.23, the area under the curve was 0.729, sensitivity was 0.893, and the specificity was 0.460.

CONCLUSIONS: Our study shows that overweight patient with stable CAD have lower risk of MACE after PCI, and the optimal threshold for predicting MACE is 24.23.

Keywords: Body Mass Index, Cardiovascular Abnormalities, percutaneous coronary intervention, Aged, Cardiovascular Diseases, Middle Aged, Multivariate Analysis, ROC Curve, Regression Analysis, Retrospective Studies

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Dinah V. Parums

DOI: 10.12659/MSM.943312

Med Sci Monit 2023; 29:e943312


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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750