Department of Nutrition and Food Science, Faculty of Pharmacy, University of Granada, 18071 Granada, Spain.
Hospital of Neurotraumatology and Rehabilitation, 18013 Granada, Spain.
Nutrients. 2022 Oct 12;14(20):4255. doi: 10.3390/nu14204255.
Sarcopenia is an important risk factor for hip fracture in older people. Nevertheless, this condition is overlooked in clinical practice. This study aimed to explore the factors associated with sarcopenia among older patients hospitalized for hip fracture, to identify a predictive model of sarcopenia based on variables related to this condition, and to evaluate the performance of screening tools in order to choose the most suitable to be adopted in routine care of older people with hip fracture. A cross-sectional study was undertaken with 90 patients (mean age 83.4 ± 7.2 years), by assessing sociodemographic and clinical characteristics, anthropometric measures, such as body mass index (BMI) and calf circumference (CC), the functional status (Barthel Index), the nutritional status (MNA-SF), and the adherence to the Mediterranean Diet (MEDAS). Diagnosis of sarcopenia was established according to the criteria of the European Working Group on Sarcopenia in Older People (EWGSOP2). The analysis of variables associated with sarcopenia was performed using multivariate logistic regression models. Clusters of sarcopenia were explored with heatmaps and predictive risk models were estimated. Sarcopenia was confirmed in 30% of hip fracture patients. Variables with the strongest association with sarcopenia were BMI (OR = 0.79 [0.68−0.91], p < 0.05) and CC (OR = 0.64 [0.51−0.81], p < 0.01). CC showed a relatively high predictive capacity of sarcopenia (area under the curve: AUC = 0.82). Furthermore, CC could be a valuable tool to predict sarcopenia risk compared with the currently used screening tools, SARC-F and SARC-CalF (AUC, 0.819 vs. 0.734 and 0.576, respectively). More studies are needed to validate these findings in external study populations.
肌少症是老年人髋部骨折的一个重要危险因素。然而，这种情况在临床实践中被忽视了。本研究旨在探讨与因髋部骨折住院的老年患者肌少症相关的因素，确定基于与该疾病相关的变量的肌少症预测模型，并评估筛查工具的性能，以选择最适合在常规护理中采用的工具。对 90 名患者（平均年龄 83.4±7.2 岁）进行了横断面研究，评估了社会人口统计学和临床特征、人体测量学指标（如体重指数（BMI）和小腿围（CC））、功能状态（巴氏指数）、营养状况（MNA-SF）和地中海饮食的依从性（MEDAS）。根据欧洲老年人肌少症工作组（EWGSOP2）的标准诊断肌少症。使用多变量逻辑回归模型分析与肌少症相关的变量。使用热图探索肌少症聚类，并估计预测风险模型。30%的髋部骨折患者被确诊为肌少症。与肌少症关联最强的变量是 BMI（OR=0.79[0.68-0.91]，p<0.05）和 CC（OR=0.64[0.51-0.81]，p<0.01）。CC 显示出相对较高的肌少症预测能力（曲线下面积：AUC=0.82）。此外，与目前使用的筛查工具 SARC-F 和 SARC-CalF 相比，CC 可能是预测肌少症风险的有价值工具（AUC，0.819 与 0.734 和 0.576）。需要更多的研究来验证这些发现是否适用于外部研究人群。
