基于列线图构建住院老年患者肌少症临床预测模型

The Clinical Prediction Model of Sarcopenia in Hospitalized Elderly Patients Was Constructed Based on the Nomogram

摘要: 背景：随着老龄化的进一步加深，肌少症在老年人群的发病逐年增高。目的：构建住院老年患者肌少症的临床预测模型，对早期肌少症患者识别提供依据。方法：便利抽样法选取2020年7月~2021年9月在新疆医科大学第一附属医院住院的老年患者372例，将其按7:3比例随机分为建模队列(n = 260)和验证队列(n = 112)，基于logistic回归结果构建住院老年患者肌少症的列线图，对模型进行校准，同时验证模型效益。结果：本研究肌少症检出率18.82%，男性23.84%、女性14.50%。单因素分析得到13个差异变量，多因素逐步logistics回归，最终得到5个差异变量：性别、BMI、步速、握力、腹围。构建住院老年肌少症患者的临床预测模型并绘制成列线图。构建训练组和验证组列线图的ROC曲线AUC大小分别为0.879 (95% CI: 0.824~0.933)和0.870 (95% CI: 0.785~0.955)，通过Hosmer-Lemeshow检验，训练组拟合优度大于验证组拟合优度，两组P值均>0.05，表明该列线图模型同样具有良好的校准度。结论：通过模型预测，运用标尺刻度，男性合并步速下降、握力下降、腹围增加、BMI减小，肌少症发生的风险远远高于其他患者几倍至十几倍，经过系列验证提示该模型的训练组和验证组均具有净收益范围，一致性和预测效能较好。

Abstract: Background: With the further deepening of aging, the incidence of sarcopenia in the elderly population increases year by year. Objective: To construct a clinical prediction model of sarcopenia in hospitalized elderly patients, and provide a basis for the identification of early sarcopenia patients. Methods: A total of 372 elderly patients hospitalized in the First Affiliated Hospital of Xinjiang Medical University from July 2020 to September 2021 were selected by convenience sampling method, and randomly divided into modeling cohort (n = 260) and validation cohort (n = 112) according to a ratio of 7:3. Based on logistic regression results, a column diagram of the elderly patients with sarcopenia was constructed. At the same time, the model is calibrated and the benefit of the model is verified. Results: In this study, the detection rate of sarcopenia was 18.82%, 23.84% in males and 14.50% in females. Univariate analysis obtained 13 differential variables, and multi-factor logistics regression obtained 5 differential variables: gender, BMI, walking speed, grip strength and abdominal circumference. The clinical prediction model of hospitalized elderly patients with sarcopenia was constructed and drawn as a column graph. The ROC curve AUC sizes of the training group and the verification group were 0.879 (95% CI: 0.824~0.933) and 0.870 (95% CI: 0.7855~0.955), respectively. Hosmer-Lemeshow test showed that the goodness of fit of the training group was greater than that of the verification group. The P values of both groups were >0.05, indicating that the column-line model also had good calibration degree. Conclusion: According to the model prediction, using the scale, the risk of sarcosis in male patients with reduced walking speed, decreased grip strength, increased abdominal circumference and decreased BMI was much higher than that of other patients by several times to ten times. The series of verification indicated that the training group and the verification group of this model had a net benefit range, and the consistency and prediction efficiency were good.