川北医学院学报2026，Vol.41Issue(1)：94-99,6.DOI:10.3969/j.issn.1005-3697.2026.01.019
基于LASSO-Logistic回归构建整合乳酸/白蛋白比值的老年脓毒症合并肺部感染重症监护室患者院内死亡风险预测模型的开发与验证
Development and validation of an in-hospital mortality risk prediction model integrating lactate-to-albumin ratio for elderly intensive care unit patients with sepsis and pulmonary infection based on LASSO-Logistic regression
摘要
Abstract
Objective:To explore the key risk factors influencing in-hospital mortality in elderly patients with sepsis and pulmonary infection,and to develop and validate a risk prediction model for in-hospital mortality based on the Least Absolute Shrinkage and Selection Operator(LASSO)-Logistic regression algorithm,integrating the lactate-to-albumin ratio(LAR)and other indicators,aiming to provide a quantitative tool for early identification of high-risk patients and optimization of intervention strategies.Methods:A retrospective analysis was conducted on 102 elderly patients(age≥65 years)with sepsis and pulmonary infection admitted to the Intensive Care Unit(ICU).Based on in-hospital outcomes(within 28 days),patients were divided into a survival group(n=65)and a death group(n=37).Clinical data of all patients were collected.The LASSO regression was used to screen predictive variables.The selected variables were incorporated into multivariate Logistic regression analysis to establish a risk prediction model.The Bootstrap method was employed for internal validation.The area under the receiver operating characteristic curve(AUC),and the Hosmer-Lemeshow goodness-of-fit test were used to evaluate the model's discrimination and calibration.Results:Univariate and LASSO-Logistic regression analyses revealed that Acute Physiology and Chronic Health Evaluation Ⅱ(APACHE Ⅱ)(OR=1.202,95％CI:1.078～1.326),Sequential Organ Failure Assessment(SOFA)score(OR=1.366,95％CI:1.142～1.590),LAR(OR=1.581,95％CI:1.242～1.920),and mechanical ventilation(OR=5.523,95％CI:1.892～9.155)were independent risk factors for in-hospital mortality(P<0.05).The AUC of the LASSO-Logistic regression prediction model was 0.855(95％CI:0.771～0.913).The Hosmer-Lemeshow test indicated a good model fit(P>0.05).Decision curve analysis(DCA)showed that the prediction model had good clinical applicability when the probability threshold ranged from 0.3 to 0.7.Conclusion:The prediction model based on APACHE Ⅱ score,SOFA score,LAR,and mechanical ventilation,constructed via LASSO-Logistic regression,demonstrates good predictive performance for in-hospital mortality risk in elderly ICU patients with sepsis and pulmonary infection.It aids in the early identification of high-risk patients and facilitates timely intervention.关键词
脓毒症/肺部感染/老年人/重症监护病房/死亡率/预测模型/乳酸/白蛋白比值Key words
Sepsis/Pulmonary infection/Aged patients/Intensive care units/Mortality/Prediction models/Lactate-to-albumin ratio分类
医药卫生引用本文复制引用
常静静,周娜,王小倩,王楠..基于LASSO-Logistic回归构建整合乳酸/白蛋白比值的老年脓毒症合并肺部感染重症监护室患者院内死亡风险预测模型的开发与验证[J].川北医学院学报,2026,41(1):94-99,6.基金项目
合肥工业大学工业安全与应急技术安徽省重点实验室自主创新专项项目(PA2024GDSK0097) （PA2024GDSK0097）
