老年病人行全膝关节置换术出院后30天内非计划再入院预测模型的建立

doi:10.3969/j.issn.1003-9198.2023.08.005

摘要/Abstract

摘要： 目的探讨影响行全膝关节置换术的老年病人非计划再入院的危险因素并构建列线图预测模型。方法回顾性收集苏北人民医院2020年1月至2022年4月因原发性膝关节骨性关节炎行全膝关节置换术(TKA)的老年病人919例,根据病人出院30 d内是否再入院分为再入院组(47例)与对照组(872例)。采用多元Logistic回归筛选出再入院的危险因素,并以列线图的形式构建临床预测模型。采用ROC曲线评估预测模型的效能。结果 919例老年病人中非计划再入院47例(5.11%)。多元Logistic回归分析显示年龄、BMI、文化程度、支付类型、年龄校正的查尔森合并症指数(ACCI)、手术时间、术中出血量以及出院去向为TKA老年病人出院30 d内非计划再入院的独立危险因素。以列线图形式构建临床预测模型的ROC曲线下面积为0.834(95%CI:0.776~0.892),特异度为78.7%,灵敏度为78.0%。结论本研究构建的列线图具有良好的预测效能,为临床医生预估病人再入院的风险提供一定的参考依据。

关键词: 骨关节炎, 全膝关节置换, 老年人, 非计划再入院, 危险因素, 列线图, 预测模型

Abstract: Objective To explore the risk factors affecting early unplanned readmissions in the elderly patients undergoing total knee arthroplasty(TKA), and to construct a clinical prediction model in the form of nomogram. Methods A retrospective study was conducted to collect 919 elderly patients who underwent TKA for primary knee osteoarthritis at Northern Jiangsu People's Hospital from January 2020 to April 2022. All patients were divided into readmission group and control group according to whether they were readmitted within 30 days after discharge. Multivariate Logistic regression analysis was performed to screen the risk factors of readmission. And the risk factors were used to construct a clinical prediction model in the form of nomogram, and receiver operator characteristic(ROC) curve was plotted to evaluate the performance of the nomogram. Results The incidence rate of unplanned readmission within 30 days after discharge was 5.11%(47/919) in the elderly patients with TKA. Binary Logistic regression analysis showed age, body mass index(BMI), literacy, payment type, age-adjusted Charlson comorbidity index(AACI), operation time, intraoperative bleeding, and discharge destination were the independent risk factors for unplanned readmission within 30 days after discharge in the elderly patients with TKA, and a clinical prediction model was established in the form of a nomogram. The area under the ROC curve of the nomogram was 0.834(95%CI: 0.776-0.892), with a specificity of 78.7%, and a sensitivity of 78.0%. Conclusions The nomogram established in this study has good predictive efficacy for the readmission risk in the elderly patients with TKA.

Key words: osteoarthritis, total knee arthroplasty, aged, unplanned readmission, risk factors, nomogram, prediction model

中图分类号:

R 687.4

陈翔宇, 李凯, 王旭, 尹军相, 许奎鑫, 李剑星, 颜连启. 老年病人行全膝关节置换术出院后30天内非计划再入院预测模型的建立[J]. 实用老年医学, 2023, 37(8): 772-776.

CHEN Xiang-yu, LI Kai, WANG Xu, YIN Jun-xiang, XU Kui-xin, LI Jian-xing, YAN Lian-qi. Establishment of prediction model of unplanned readmission within 30 days after discharge in elderly patients receiving total knee arthroplasty[J]. Practical Geriatrics, 2023, 37(8): 772-776.

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