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Relative Fat Mass Index can be solution for obesity paradox in coronary artery disease severity prediction calculated by SYNTAX Score


Background The relation between body mass index (BMI) and coronary artery disease (CAD) extension remains controversial. A new score was developed to estimate body fat percentage (BFP) known as Relative Fat Mass (RFM) Index. This study aimed to evaluate the value of RFM Index in predicting the severity of the CAD, compared with other anthropometric measurements.

Methods A total of 325 patients with chronic CAD were investigated. RFM, BFP, BMI and other anthropometric characteristics of patients were measured before angiography. CAD severity was determined by SYNergy between percutaneous coronary intervention with TAXus and cardiac surgery trial (SYNTAX) Score. The association between SYNTAX Score and variables was evaluated using linear regression models. In order to compare the model performance, R-squared (R2), Akaike’s information criterion, Bayesian information criterion and root mean square error were used.

Results Univariate linear regression outcome variable, SYNTAX was used to determine whether there was any relationship between variables. Independent variables were included in the multivariable linear logistic regression models. The analysis showed that in model 1, RFM (β coefficient: 2.31 (0.90 to 3.71), p=0.001)), diabetes mellitus (β coefficient: 3.72 (1.67 to 3.76), p=0.004)), haemoglobin (β coefficient: −2.12 (−3.70 to −0.53), p=0.03) and age (β coefficient: 1.83 (0.29 to 3.37), p=0.02)) were statistically significant. The adjusted R2 values in model 1 were higher than model 2 (BFP) and model 3 (BMI) (0.155, 0.137 and 0.130, respectively), and χ2 values of RFM were higher than BFP and BMI (10.5, 3.4 and 1.0, respectively).

Conclusion RFM Index is a more reliable and compatible marker of obesity in showing the severity of CAD compared to BMI.

  • adult cardiology
  • coronary heart disease
  • ischaemic heart disease
  • public health
  • diabetes & endocrinology

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