中国护士群体足部重度疼痛风险预测的列线图模型构建

Nomographic Model for Predicting Severe Foot Pain in Nurses from Tertiary Hospitals in China

目的调查护士足部重度疼痛的发生率及常见部位,明确其危险因素,并构建个体足部重度疼痛风险预测列线图。方法采用分层整体抽样方法,于2019年8–12月期间选取在我国351家三级医院的10691名护士,调查足部重度疼痛的发生现状。将可能影响其发生的变量进行单因素分析,明确护士足部重度疼痛发生的影响因素,进一步采用logistic逐步回归分析,筛查足部重度疼痛发生的独立危险因素。将多因素回归分析结果中有统计学意义的因素纳入Nomograph预测模型的构建。通过一致性指数(C-index)和1000个bootstrap样本校准来测量Nomograph预测性能。结果10691名护士中发生足部疼痛3419名,发生率为31.98%,其中重度疼痛(VAS 7~10分)发生率为2.27%(243名)。重度疼痛部位多见于双侧脚掌与足跟。研究最终纳入年龄、学历、工作鞋材质、工作鞋舒适程度、足部外伤史、是否合并其他并发症这6个因素,构建了Nomograph预测模型。C-index值为0.706,标准曲线与校准预测曲线贴合良好。结论该研究构建的模型具有良好的预测效果,指标简单易得,可为护士预防重度足部疼痛提供借鉴。

Objective To investigate the prevalence and common sites of severe foot pain among nurses,to define the risk factors of severe foot pain in nurses in tertiary hospital in China,and to construct a nomograph model for predicting individuals'risks for severe foot pain.Methods Between August 2019 and December 2019,a stratified global sampling method was used to select 10691 nurses from 351 tertiary hospitals in China to investigate the incidence of severe foot pain among them.The variables that may affect the occurrence of severe foot pain were analyzed by single factor analysis to identify the influencing factors of severe foot pain in nurses.Furthermore,the independent risk factors of severe foot pain were analyzed by stepwise logistic regression analysis.The statistically significant factors identified in the multivariate regression analysis were incorporated into the nomograph prediction model.The predictive performance of the nomograph was measured by the consistency index(C-index)and calibrated with 1000 Bootstrap samples.Results A total of 3419 nurses out of the 10691 had foot pain,resulting in an incidence of 31.98%.The incidence of severe pain(VAS score 7-10)was 2.27%(243 of 10691).The locations of severe pain were more commonly found in the soles and heels of both feet.Six factors,including age,education,the material of the work shoes,comfortableness of the work shoes,number of complications,and foot injure history,were incorporated in the nomograph predicting model.The C-index value was 0.706 and the standard curve fitted well with the calibrated prediction curve.Conclusion The risk prediction model constructed in this study showed sound performance in predicting the risk of severe foot pain in nurses,and all the indicators involved are simple and the relevant data are easily obtained.The model can provide reference for preventing severe foot pain in nurses.