住院患者压力性损伤愈合影响因素分析及列线图预测模型的构建  

Influencing factors of the healing of pressure injury in inpatients and the construction of nomogram prediction model

作　　者：查曼丽 黄春霞[1] 袁宝芳[1] 沈红五[1] ZHA Manli;HUANG Chunxia;YUAN Baofang;SHEN Hongwu(Nursing Department,the Affiliated Hospital of Nantong University,Nantong 226001)

机构地区：[1]南通大学附属医院护理部,南通226001

出　　处：《南通大学学报（医学版）》2023年第1期25-29,共5页Journal of Nantong University(Medical sciences)

基　　金：南通市科技计划项目(JC2020044)。

摘　　要：目的:构建预测住院患者压力性损伤(pressure injury,PI)愈合的列线图预测模型,并对列线图预测模型进行评价,探索其在PI愈合预测中的适用性。方法:多中心回顾性收集3家三级甲等医院2017年1—12月PI上报登记表及PI住院患者的病历资料,根据PI患者出院时创面愈合情况将其分为愈合组与未愈组。通过单因素分析和多因素Logistic回归分析筛选影响PI愈合的独立危险因素,并在此基础上绘制可视化列线图预测模型。采用Hosmer-Lemeshow拟合优度检验对模型进行校准度评价并绘制校正曲线。采用ROC曲线以及曲线下面积(area under the receiver operating characteristic curve,AUC^(ROC))对模型进行区分度评价。用灵敏度和特异度确定预测PI愈合的列线图预测模型的预测截断值。结果:多因素Logistic回归分析显示:年龄>75岁,白蛋白水平、Braden评分、PI分期、PI面积和住院时间是影响PI愈合的独立因素。Hosmer-Lemeshow拟合优度检验χ^(2)=4.199,P=0.839>0.20,AUC^(ROC)=0.769。由灵敏度和特异度确定的截断值为0.3,与之对应的列线图总得分为17分。结论:PI愈合列线图预测模型校准度较高,区分度中等偏上。该模型适用于住院患者PI愈合预测,当PI患者愈合概率<0.3(总得分<17分)时则被识别为PI难愈的高危人群。护理人员可利用此模型快速识别PI难愈高危人群。Objective:To construct the nomogram prediction model for predicting the healing of pressure injury(PI),and evaluating the nomogram prediction to explore its applicability in predicting the healing of PI.Methods:PI report registration form and medical records of PI inpatients in three grade A hospitals from January to December 2017 were retrospectively collected in a multi-center,and PI patients were divided into healing group and unhealed group according to wound healing at discharge.The independent risk factors affecting PI healing were screened by univariate analysis and multivariate Logistic regression analysis,and a visualized prediction model was developed based on the results.Hosmer-Lemeshow goodness-of-fit test was used to evaluate the calibration of the model and the calibration curve was drawn.The ROC curve and area under the receiver operating characteristic curve(AUC^(ROC))were used to evaluate the discrimination of the model.Sensitivity and specificity were used to determine the truncation value of the nomogram prediction model for the healing of PI.Results:Multiple Logistic regression analysis showed that age>75 years old,hospitalization days,albumin value,Braden score,stage of PI,and area of PI were independent factors affecting the healing of PI.The result of Hosmer-Lemeshow goodness-of-fit test wasχ^(2)=4.199,P=0.839>0.20.In this study,AUC^(ROC)=0.769.The truncation probability value determined by sensitivity and specificity was 0.3.Correspondingly,the total score of nomogram was 17.Conclusion:The nomogram prediction model for the healing of PI has good calibration ability and a medium discrimination ability.The model is suitable for predicting the healing of PI.If the healing probability of inpatients with PI is less than 0.3(total scores<17 points),it is recognized as inpatients with a high-risk for unhealing.Nursing staff can use this prediction model to quickly identify inpatients with a high-risk for unhealing.

关 键 词：压力性损伤 愈合 影响因素 预测模型 列线图 

分 类 号：R473.75[医药卫生—护理学]