维持性血液透析患者衰弱风险预测模型的系统评价

doi:10.3761/j.issn.1672-9234.2026.01.015

摘要/Abstract

摘要：

目的系统梳理并综合评估现有维持性血液透析患者衰弱风险预测模型的构建特征、预测效能与方法学质量，为该领域模型的优化与临床转化提供全面的证据总结与参考。方法系统检索PubMed、Embase、Web of Science、Cocharne Library、中国知网、万方数据库、维普数据库和中国生物医学文献数据库，收集建库至2025年9月发表的维持性血液透析患者衰弱风险预测模型的相关研究。文献筛选和数据提取由2名研究人员独立完成，并采用预测模型偏倚风险评估工具对所有纳入研究的偏倚风险及临床适用性进行评估。结果共纳入15项研究，涉及19个预测模型。Meta分析显示，模型整体区分度良好（合并曲线下面积=0.882，95%CI：0.839~0.924），但研究间存在高度异质性（I²=92.57%），且敏感性分析证实此结果稳健。质量评价结果显示，13项研究存在高偏倚风险。预测因子可归纳为患者基线资料、疾病负担、实验室指标和功能状态4个类别，其中年龄、合并症指数、血清白蛋白、抑郁症状和体力活动水平是高频的核心风险因素。结论现有维持性血液透析患者衰弱风险预测模型研究呈现出“表现性能良好，但研究严谨性不足”的矛盾特征，然而，识别出的核心风险因素集可为当前临床提供实用的高风险个体警示信号。未来还需开展高质量的风险预测模型研究，并通过临床实际部署验证其临床适用性和有效性。

关键词: 血液透析, 衰弱, 预测模型, 系统评价, 循证护理学

Abstract:

Objective This study systematically synthesizes and comprehensively evaluates the construction characteristics，predictive performance and methodological quality of existing models for predicting the risk of frailty in maintenance hemodialysis（MHD） patients，with the aim of providing a comprehensive evidence summary and reference for the optimization and clinical transformation of models in this field. Methods Systematically searched PubMed，Embase，Web of Science，Cocharne Library，CNKI，Wanfang Database，VIP Database and China Biomedical Literature Database to collect relevant studies published from the establishment of each database up to September 2025 on the prediction model of frailty risk for maintenance hemodialysis patients. Literature screening and data extraction were independently completed by two researchers，and the risk of bias and clinical applicability of all included studies were strictly assessed using the Predictive Model Bias Risk Assessment Tool （PROBAST）. Results A total of 15 studies involving 19 prediction models were included. Meta-analysis showed that the model had good overall discrimination overall（pooled AUC=0.882，95%CI：0.839-0.924），but there was a high degree of heterogeneity between studies（I²=92.57%），and sensitivity analysis confirmed that this result was robust. PROBAST assessment showed that 13 studies were at high risk of bias. Predictors were categorized into four groups：patient baseline data，disease burden，laboratory indicators and functional status. Among them，age，comorbidity index，serum albumin，depressive symptoms and physical activity level were the most frequently reported core risk factors. Conclusion Existing research on the risk prediction model for MHD patients shows the contradictory characteristic of “favorable apparent performance， but insufficient methodological rigor”. However， the core set of risk factors identified in this study can provide practical warning signals for high-risk individuals in current clinical practice. In the future， high-quality research on risk prediction models needs to be conducted， and their clinical applicability and effectiveness should be verified through actual clinical implementation.

Key words: Hemodialysis, Frailty, Prediction Model, Systematic Review, Evidence-Based Nursing

杨素珍, 魏锦轩, 王颖, 李颖, 仲伟娜, 张欣雨, 崔永军, 程海荣. 维持性血液透析患者衰弱风险预测模型的系统评价[J]. 中华护理教育, 2026, 23(1): 101-109.

YANG Suzhen, WEI Jinxuan, WANG Ying, LI Ying, ZHONG Weina, ZHANG Xinyu, CUI Yongjun, CHENG Hairong. Systematic review of prediction models for debilitating risk in maintenance hemodialysis patients[J]. Chinese Journal of Nursing Education, 2026, 23(1): 101-109.

图/表 4

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