目的:对糖尿病周围神经病变(DPN)风险预测模型的质量进行系统评价,为现有模型的改进和新模型的建立提供参考依据.方法:检索PubMed、the Cochrane Library、EMbase、Web of Science、中国生物医学文献数据库、中国知网、维普数据库、万方数据库发表的有关构建DPN风险预测模型的研究,检索时限为建库至2024年4月1日.采用PROBAST工具对纳入的预测模型研究进行质量评估,并利用RevMan 5.4软件对关键预测因子进行Meta分析.结果:本研究共纳入12篇文献,涉及23 380例病人,共构建了 19个DPN风险预测模型.其中11篇文献进行了模型校准,9篇文献进行了模型验证.预测模型研究的偏倚风险评估工具(PROBAST)评价结果表明,12篇文献均为高偏倚风险.预测因子主要包括基本因素、疾病因素及实验室检查指标3类.Meta分析结果显示,糖化血红蛋白[OR=1.54,95％CI(1.38,1.72),Z=7.55,P＜0.001]、年龄[OR=1.10,95％CI(1.00,1.20),Z=2.06,P=0.040]、糖尿病病程[OR=1.22,95％CI(1.14,1.30),Z=5.95,P＜0.001]是DPN的预测因子.结论:现有证据显示,DPN的预测模型仍处于探索阶段,未来应根据临床实际情况选择或开发一种偏倚风险低、适用性强的预测模型,并在实际应用中持续监测其预测效果.同时,医护人员应高度关注病人的糖化血红蛋白水平、年龄及病程,以期早期发现DPN,并采取有针对性的预防和治疗措施.
Risk prediction models for diabetic peripheral neuropathy:a systematic review and Meta-analysis
Objective:To systematically evaluate the quality of risk prediction models for diabetic peripheral neuropathy(DPN)and provide a reference for improving existing models and establishing new models.Methods:Literature related to the construction of risk prediction models for DPN were retrieved from PubMed,the Cochrane Library,EMbase,Web of Science,CBM,CNKI,VIP,and WanFang Database from the establishment of the database to April 1,2024.The quality of the included prediction model studies was assessed using the PROBAST tool,and the key predictors were Meta-analyzed using RevMan 5.4 software.Results:A total of 12 articles were included in this study involving 23 380 patients,and 19 DPN risk prediction models were constructed.Among them,11 articles were calibrated and 9 articles were validated.The PROBAST evaluation results showed that all 12 articles were at high risk of bias.The predictive factors mainly included basic factors,disease factors,and laboratory test indicators.Meta-analysis results showed that glycosylated hemoglobin(OR=1.54,95％CI 1.38-1.72,Z=7.55,P＜0.001),age(OR=1.10,95％CI 1.00-1.20,Z=2.06,P=0.040),and diabetic course(OR=1.22,95％CI 1.14-1.30,Z=5.95,P＜0.001)were predictive factors for DPN.Conclusions:current evidence shows that the prediction model of DPN is still in the exploratory stage.In the future,a prediction model with low bias risk and strong applicability should be selected or developed according to the actual clinical situation,and its prediction effect should be continuously monitored in practical applications.At the same time,medical staff should pay high attention to the patient's glycated hemoglobin level,age,and course of disease,in order to detect DPN earlier and take targeted prevention and treatment measures.
万方数据
维普
