Department of Internal Medicine, Botucatu Medical School, Universidade Estadual Paulista (UNESP), São Paulo, Brazil.
Department of Public Health, Botucatu Medical School, Universidade Estadual Paulista (UNESP), São Paulo, Brazil.
Nutr Diet. 2019 Nov;76(5):613-619. doi: 10.1111/1747-0080.12523. Epub 2019 Mar 14.
The present study aimed to identify variables associated with sarcopenia in cirrhotic outpatients using clinical data, anthropometric measures and lab tests. In a single centre prospective study, 261 cirrhotic outpatients were followed on average for 2 years. The diagnostic criteria of sarcopenia were applied according to the current guidelines, combining muscle strength and appendicular muscle mass index.
Age, sex, liver disease aetiology and the Model of End-Stage Liver Disease score were included as independent variables, as well as mid-arm circumference (MAC), body mass index and triceps skinfold. Multiple logistic regression was applied including all independent variables (maximum model). Then, the analysis was performed only with the variables that were significant in the first analysis (parsimonious model). Once the variable most related to sarcopenia was determined by the two models, the area under the receiver operator characteristic curve was calculated. Mortality rates were described for patients with and without sarcopenia.
Sarcopenia was diagnosed in 14 subjects (5.36%), and the variable best associated with sarcopenia was MAC (P < 0.01). The 1-year mortality rate of 35.71% found among subjects with sarcopenia was not significantly higher (P = 0.07) than the 15.38% observed among those without this condition.
Before examinations requiring ionising radiation, patients with cirrhosis can be submitted to simple screening tools to identify those who have a high risk of sarcopenia, thus promoting a cost-effective assessment.
本研究旨在通过临床数据、人体测量学指标和实验室检查,确定与肝硬化门诊患者肌少症相关的变量。在一项单中心前瞻性研究中,平均随访 261 名肝硬化门诊患者 2 年。根据当前指南,将肌肉力量和四肢骨骼肌指数结合起来应用肌少症诊断标准。
年龄、性别、肝病病因和终末期肝病模型评分被纳入独立变量,同时还包括上臂中部周长(MAC)、体重指数和三头肌皮褶厚度。应用多元逻辑回归分析所有独立变量(最大模型)。然后,仅对首次分析中具有统计学意义的变量进行分析(简约模型)。在两种模型确定与肌少症最相关的变量后,计算受试者工作特征曲线下面积。描述了有肌少症和无肌少症患者的死亡率。
诊断出 14 例(5.36%)肌少症患者,与肌少症最相关的变量是 MAC(P<0.01)。肌少症患者的 1 年死亡率为 35.71%,与无肌少症患者的 15.38%相比差异无统计学意义(P=0.07)。
在需要进行放射性检查之前,肝硬化患者可以接受简单的筛查工具,以识别出那些患有肌少症风险较高的患者,从而进行具有成本效益的评估。