Derivation and validation of a simple anthropometric equation to predict fat-free mass in patients with chronic hepatitis C.

BACKGROUND: Loss of skeletal muscle mass is very common in chronic liver diseases and affects 30.0-70.0% of the patients with cirrhosis. Given the relevance of muscle wasting in hepatic diseases, a practical screening tool for earlier detection of skeletal muscle mass loss is of utmost significance. AIMS: To develop and validate a simple anthropometric prediction equation for fat-free mass estimation by using Bioelectrical Impedance Analysis (BIA) as a reference method in patients with chronic hepatitis C (CHC). METHODS: We prospectively, included 209 CHC patients, randomly allocated into two groups, 158 patients in a development model (derivation sample) and 51 patients in a validation group (validation sample). Predictive equations were developed using backward stepwise multiple regression and the most adequate and simplest derived predictive equation was further explored for agreement and bias in the validation sample. The accuracy of the predictive equation was evaluated using the coefficient of determination (R2). RESULTS: The predictive equation with an optimal R2 was Fat-Free Mass (Kg) = Sex × 0.17 + Height (m) × 16.83 + Weight (Kg) × 0.62 + Waist Circumference (cm) × (-0.15) + Weight (Kg) × Sex × (-0.30) + Sex × Waist Circumference (cm) × 0.14-6.23; where sex = 1 for female and 0 for male. R2 = 0.93, standard error of the estimate = 2.6 Kg and coefficient of variation = 20.0%, p < 0.001. CONCLUSIONS: Our developed and cross-validated anthropometric prediction equation for fat-free mass estimation by using BIA attained a high coefficient of determination, a low standard error of the estimate, and lowermost coefficient of variation. This study indicates that predictive equations may be reliable and useful alternative methods for clinical evaluation of fat-free mass in patients with CHC.

Skeletal muscle mass index and phase angle are decreased in individuals with dependence on alcohol and other substances.

OBJECTIVE: The aim of this study was to evaluate whether low skeletal muscle mass index (SMI) and low phase angle (PhA) are associated with demographic, clinical, lifestyle, and nutritional status in patients dependent on alcohol and other substances. METHODS: We prospectively included 63 individuals dependent on alcohol and other substances and 71 age- and sex-matched healthy controls. Body composition was assessed by bioelectrical impedance analysis. Subjective global assessment was used to evaluate malnutrition. All included participants underwent a psychiatric evaluation, including the administration of the Mini-International Neuropsychiatric Interview. Univariate and multivariate analysis were performed to evaluate associations between low skeletal muscle mass index (SMI) and low phase angle (PhA) and nutritional, lifestyle, and alcohol use and cocaine/crack use variables, controlling for sex and age. RESULTS: Low SMI and low PhA were identified in 11.1% and 44.5% of the substance dependents, respectively. Low midarm muscle circumference (r = 0.58; P < 0.001), low midarm muscle area (r = 051; P < 0.001), and reduced PhA (r = 0.59; P < 0.001) were positively correlated with low SMI. Multivariate analysis showed that heavy alcohol consumption (≥80 g·d· ≥5 y-1; odds ratio [OR], 2.33; 95% confidence interval [CI], 1.12-4.84; P = 0.02) and sedentary lifestyle (OR, 4.39; 95% CI, 1.29-14.89; P = 0.02) were independently associated with reduced SMI. Low PhA was independently associated with heavy alcohol consumption (OR, 3.64; 95% CI, 1.62-8.15; P = 0.002) and cocaine or crack use (OR, 3.97; 95% CI, 1.05-15.11; P = 0.04) in multivariate analysis. CONCLUSIONS: Low SMI and low PhA are independently associated with heavy alcohol consumption. Low PhA is independently associated with cocaine or crack use.