急诊科患者30 d死亡风险预测模型的构建与验证

Development and validation of a predictive model for the risk of 30-day death in emergency department patients

目的探讨急诊科患者30 d死亡危险因素,采用列线图构建预测模型并进行验证。方法采用回顾性队列研究方法,收集2021年1月1日至6月30日常德市第一人民医院急诊科收治的1091例患者的临床资料,其中1月1日至3月31日的741例患者为建模组,4月1日至6月30日的350例患者为验证组。收集患者的一般资料、入急诊科首次生命体征和实验室检查结果,计算改良早期预警评分(MEWS),并记录30 d转归。采用单因素和多因素Logistic回归分析筛选出30 d死亡的危险因素;根据多因素分析结果构建30 d死亡的列线图模型,采用受试者工作特征曲线(ROC曲线)评估所建模型的一致性,采用Hosmer-Lemeshow拟合优度检验评价预测模型的拟合程度。结果最终1091例患者均纳入分析,其中建模组741例,男性356例、女性385例,年龄(51.42±17.33)岁,30 d病死率为28.88%;验证组350例,男性188例、女性162例,年龄(52.88±16.11)岁,30 d病死率为24.00%。单因素分析结果显示,年龄、入急诊科时主要诊断、意识、呼吸频率(RR)、收缩压(SBP)、心率(HR)、脉搏血氧饱和度(SpO_(2))、MEWS评分、红细胞沉降率(ESR)、降钙素原(PCT)、体质量指数(BMI)可能是急诊科患者30 d死亡的危险因素;进一步纳入多因素分析结果显示,MEWS评分〔优势比(OR)=14.22,95%可信区间(95%CI)为1.46~138.12〕、ESR(OR=46.71,95%CI为20.48~106.53)、PCT(OR=4.97,95%CI为2.46~10.02)、BMI(24.0~27.9 kg/m^(2):OR=37.82,95%CI为14.69~97.36;≥28.0 kg/m^(2):OR=62.11,95%CI为25.77~149.72)是急诊科患者30 d死亡的独立危险因素(均P<0.05)。根据多因素分析筛选出的变量构建列线图模型,建模组模型的ROC曲线下面积(AUC)为0.974(95%CI为0.753~0.983),验证组模型的AUC为0.963(95%CI为0.740~0.975);Hosmer-Lemeshow检验显示,列线图模型的预测结果与实际情况差异无统计学意义(χ2=1.216,P=1.270)。结论MEWS评分联合BMI、ESR、PCT建立的预测模型可以科学、有效地预测急诊科患者30 d转归。

Objective To explore the risk factors for 30-day death in emergency department patients,and then construct a prediction model and validate it using nomogram.Methods A retrospective cohort study was conducted.The clinical data of 1091 patients admitted to the emergency department of the First People's Hospital of Changde from January 1 to June 30,2021 was collected,including 741 patients from January 1 to March 31 in the development group and 350 patients from April 1 to June 30 in the validation group.General information,first vital signs admitted to the emergency department,and laboratory results were collected,the modified early warning score(MEWS)was calculated,and 30-day outcomes were recorded.Univariate and multivariate Logistic regression analysis was used to screen out the risk factors of 30-day death.According to the results of multivariate analysis,the nomogram was used to construct a 30-day death prediction model.The receiver operator characteristic curve(ROC curve)was used to evaluate the consistency of the prediction model,the calibration of the prediction model was evaluated by the Hosmer-Lemeshow goodness of fit test.Results A total of 1091 patients were enrolled.There were 741 patients in the development group,including 356 males and 385 females,aged(51.42±17.33)years old,and the 30-day mortality was 28.88%.There were 350 patients in the validation group,including 188 males and 162 females,aged(52.88±16.11)years old,and the 30-day mortality was 24.00%.The results of the univariate analysis showed that age,primary diagnosis on admission,consciousness,respiratory rate(RR),systolic blood pressure(SBP),heart rate(HR),pulse oxygen saturation(SpO_(2)),MEWS score,erythrocyte sedimentation rate(ESR),procalcitonin(PCT)and body mass index(BMI)might be the risk factors for 30-day death in patients in the emergency department.The results of the multivariate analysis showed that the MEWS score[odds ratio(OR)=14.22,95%confidence interval(95%CI)was 1.46-138.12],ESR(OR=46.71,95%CI was 20.48-106.53),PCT(OR=4.97,95%CI was 2.46-10.02),BMI(24.0-27.9 kg/m^(2):OR=37.82,95%CI was 14.69-97.36;≥28.0 kg/m^(2):OR=62.11,95%CI was 25.77-149.72)were independent risk factors for 30-day death in the emergency department(all P<0.05).Using the four variables with the results of multivariate analysis to construct a nomogram prediction model,the area under the ROC curve(AUC)was 0.974(95%CI was 0.753-0.983)for the development group,and the AUC was 0.963(95%CI was 0.740-0.975)for the validation group.The Hosmer-Lemeshow test showed no statistically significant difference between the predicted outcome of the nomogram prediction model and the actual occurrence(χ2=1.216,P=1.270).Conclusion The prediction model developed by the MEWS score combined with BMI,ESR and PCT can scientifically and effectively predict the 30-day outcome of emergency department patients.