| 摘要: |
| 【摘要】目的 分析住院老年风湿病患者衰弱的影响因素并构建其列线图模型。方法 采用横断面研究方法，收集本中心246例≥60岁的风湿病患者为研究对象，收集一般资料，基于衰弱指数的评估方法分组，利用行Lasso回归对一般人口学资料、疾病相关资料、营养状况和实验室指标等变量进行筛选，再利用Logistic回归分析老年风湿病患者衰弱的危险因素并构建列线图模型。结果 老年风湿病衰弱患病率为26.83%，LASSO-Logistic回归的分析结果显示：MNA-SF评分、合并CTD-ILD、独居，通过绘制ROC曲线，发现预测模型AUC为0.76（95%CI：0.68-0.85），内部验证AUC为0.80（95%CI：0.64-0.97），校正曲线显示该列线图模型对预测观测值与实际测量值有很好的一致性。DCA曲线表明，在几乎全阈值范围内，该模型可以最大临床获益。结论 本研究建立的老年风湿病衰弱预测列线图模型具有具有较强的临床实用性。 |
| 关键词: 老年，风湿病，衰弱，预测模型 |
| DOI： |
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| 基金项目:国家重点研发计划(2022YFC3602000）；浙江省中医药科研基金计划（2022ZQ053）；浙江省医学会临床医学科研专项资金项目（2023ZYC-A184） |
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| Frailty Risk Factors and Nomogram Model Construction for Hospitalized Elderly Patients with Rheumatic Diseases |
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Wu Xiuping1, Lin Jin2, Ke Yini2, Yu Jianhong1
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1.Affiliated Hospital of Shaoxing University;2.The First Affiliated Hospital Zhejiang University School of Medicine
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| Abstract: |
| 【Abstract】 Objective To analyze the frailty risk factors in hospitalized elderly patients with rheumatic diseases and construct a nomogram model for prediction. Methods A cross-sectional study was conducted, enrolling 246 rheumatic disease patients aged 60 years and older from a single center. General data were collected, and patients were grouped based on the Frailty Index assessment method. LASSO regression was used to screen variables from demographic information, disease-related data, nutritional status, and laboratory indicators. Logistic regression was then used to identify frailty risk factors and build a nomogram model. Results The prevalence of frailty in elderly patients with rheumatic diseases was 26.83%. LASSO-logistic regression analysis identified the following significant predictors: MNA-SF, comorbid CTD-ILD, and living alone. The ROC curve for the predictive model showed an AUC of 0.76 (95% CI: 0.68-0.85), with an internal validation AUC of 0.80 (95% CI: 0.64-0.97). The calibration curve demonstrated good consistency between predicted and observed values. The DCA indicated that the model could achieve maximum clinical benefit across nearly the entire threshold range. Conclusion The nomogram model established in this study provides strong clinical utility for predicting frailty in elderly patients with rheumatic diseases. |
| Key words: Elderly, Rheumatic Diseases, Frailty, Predictive Model |