Sciences Applied to Adult Health Care Post-Graduate Programme, Faculdade de Medicina, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil; Outpatient Clinic of Viral Hepatitis, Instituto Alfa de Gastroenterologia, Faculdade de Medicina, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil.
Faculdade de Medicina, Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Brazil.
Clin Nutr. 2021 Mar;40(3):1281-1288. doi: 10.1016/j.clnu.2020.08.011. Epub 2020 Aug 15.
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.
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).
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 (R).
The predictive equation with an optimal R 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. R = 0.93, standard error of the estimate = 2.6 Kg and coefficient of variation = 20.0%, p < 0.001.
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.
骨骼肌量减少在慢性肝病中非常常见，影响 30.0-70.0%的肝硬化患者。鉴于肌肉减少在肝脏疾病中的相关性，一种实用的筛查工具，用于早期检测骨骼肌量减少，具有至关重要的意义。
使用生物电阻抗分析（BIA）作为参考方法，为慢性丙型肝炎（CHC）患者开发并验证一种简单的人体测量预测方程，用于估计去脂体重。
我们前瞻性地纳入了 209 例 CHC 患者，随机分为两组，其中 158 例患者纳入模型建立组（推导样本），51 例患者纳入验证组（验证样本）。使用向后逐步多元回归法建立预测方程，然后在验证样本中进一步探索最合适和最简单的推导预测方程的一致性和偏差。使用决定系数（R）评估预测方程的准确性。
具有最佳 R 值的预测方程为：去脂体重（Kg）=性别×0.17+身高（m）×16.83+体重（Kg）×0.62+腰围（cm）×（-0.15）+体重（Kg）×性别×（-0.30）+性别×腰围（cm）×0.14-6.23；其中性别=1 代表女性，0 代表男性。R=0.93，估计的标准误差=2.6 Kg，变异系数=20.0%，p<0.001。
我们使用 BIA 开发并交叉验证的用于估计去脂体重的人体测量预测方程具有较高的决定系数、较低的估计标准误差和最低的变异系数。本研究表明，预测方程可能是一种可靠且有用的替代方法，可用于临床评估 CHC 患者的去脂体重。
