Background: Although the presence of both obesity and reduced muscle mass presents a dual metabolic burden and additively has a negative effect on a variety of cardiometabolic parameters, data regarding the associations between their combined effects and left ventricular diastolic function are limited. This study investigated the association between the ratio of skeletal muscle mass to visceral fat area (SVR) and left ventricular diastolic dysfunction (LVDD) in patients with preserved ejection fraction using random forest machine learning. Methods: In total, 1,070 participants with preserved left ventricular ejection fraction who underwent comprehensive health examinations, including transthoracic echocardiography and bioimpedance body composition analysis, were enrolled. SVR was calculated as an index of sarcopenic obesity by dividing the appendicular skeletal muscle mass by the visceral fat area. Results: In the random forest model, age and SVR were the most powerful predictors of LVDD. Multivariate logistic regression analysis demonstrated that older age (adjusted odds ratio [OR], 1.11; 95% confidence interval [CI], 1.07 to 1.15) and lower SVR (adjusted OR, 0.08; 95% CI, 0.01 to 0.57) were independent risk factors for LVDD.SVR showed a significant improvement in predictive performance and fair predictability for LVDD, with the highest area under the curve noted in both men and women, with statistical significance. In non-obese and metabolically healthy individuals, the lowest SVR tertile was associated with a greater risk of LVDD compared to the highest SVR tertile. Conclusion Decreased muscle mass and increased visceral fat were significantly associated with LVDD compared to obesity, body fat composition, and body muscle composition indices.

Background: Although the presence of both obesity and reduced muscle mass presents a dual metabolic burden and additively has a negative effect on a variety of cardiometabolic parameters, data regarding the associations between their combined effects and left ventricular diastolic function are limited. This study investigated the association between the ratio of skeletal muscle mass to visceral fat area (SVR) and left ventricular diastolic dysfunction (LVDD) in patients with preserved ejection fraction using random forest machine learning. Methods: In total, 1,070 participants with preserved left ventricular ejection fraction who underwent comprehensive health examinations, including transthoracic echocardiography and bioimpedance body composition analysis, were enrolled. SVR was calculated as an index of sarcopenic obesity by dividing the appendicular skeletal muscle mass by the visceral fat area. Results: In the random forest model, age and SVR were the most powerful predictors of LVDD. Multivariate logistic regression analysis demonstrated that older age (adjusted odds ratio [OR], 1.11; 95% confidence interval [CI], 1.07 to 1.15) and lower SVR (adjusted OR, 0.08; 95% CI, 0.01 to 0.57) were independent risk factors for LVDD.SVR showed a significant improvement in predictive performance and fair predictability for LVDD, with the highest area under the curve noted in both men and women, with statistical significance. In non-obese and metabolically healthy individuals, the lowest SVR tertile was associated with a greater risk of LVDD compared to the highest SVR tertile. Conclusion Decreased muscle mass and increased visceral fat were significantly associated with LVDD compared to obesity, body fat composition, and body muscle composition indices.

Background: Although the presence of both obesity and reduced muscle mass presents a dual metabolic burden and additively has a negative effect on a variety of cardiometabolic parameters, data regarding the associations between their combined effects and left ventricular diastolic function are limited. This study investigated the association between the ratio of skeletal muscle mass to visceral fat area (SVR) and left ventricular diastolic dysfunction (LVDD) in patients with preserved ejection fraction using random forest machine learning. Methods: In total, 1,070 participants with preserved left ventricular ejection fraction who underwent comprehensive health examinations, including transthoracic echocardiography and bioimpedance body composition analysis, were enrolled. SVR was calculated as an index of sarcopenic obesity by dividing the appendicular skeletal muscle mass by the visceral fat area. Results: In the random forest model, age and SVR were the most powerful predictors of LVDD. Multivariate logistic regression analysis demonstrated that older age (adjusted odds ratio [OR], 1.11; 95% confidence interval [CI], 1.07 to 1.15) and lower SVR (adjusted OR, 0.08; 95% CI, 0.01 to 0.57) were independent risk factors for LVDD.SVR showed a significant improvement in predictive performance and fair predictability for LVDD, with the highest area under the curve noted in both men and women, with statistical significance. In non-obese and metabolically healthy individuals, the lowest SVR tertile was associated with a greater risk of LVDD compared to the highest SVR tertile. Conclusion Decreased muscle mass and increased visceral fat were significantly associated with LVDD compared to obesity, body fat composition, and body muscle composition indices.