Construction of in-hospital death prediction model for patients with congestive heart failure complicated with cardiogenic shock and clinical efficacy analysis

Sun Tienan; Li Zhizhong

doi:10.3760/j.issn.1673-4777.2024.11.004

Abstract：Objective To develop a model based on the Medical Information Mart for Intensive Care(MIMIC)database to predict in-hospital mortality in patients with congestive heart failure and cardiogenic shock(CS),and evaluate its clinical efficacy.Methods This retrospective study included 2 090 patients diagnosed as congestive heart failure complicated with CS from 2008 to 2019 from the MIMIC-Ⅳ database.All patients were divided into non-death group(1 434 cases)and death group(656 cases)according to whether there was in-hospital death.Data on clinical characteristics,vital signs,laboratory results,and system scores were collected.Lasso regression was used to select relevant variables,and multivariate logistic regression analysis was employed to identify independent predictors and construct a nomogram model for predicting in-hospital mortality.Internal validation was performed using the Bootstrap method.The model was evaluated using the receiver operating charac-teristic(ROC)curve and decision curve analysis(DCA).Results Multivariate Logistic regression analysis showed that peripheral oxygen saturation[odds radio(OR)=0.968,95％confidence interval(CI):0.949-0.987,P=0.001]and serum albumin(OR=0.764,95％CI:0.626-0.932,P=0.008)were independent protection factors for patients in-hospital death,and age(OR=1.043,95％CI:1.034-1.051,P＜0.001),female(OR=1.304,95％CI:1.052-1.615,P=0.015),body temperature＜36 ℃(OR=1.720,95％CI:1.284-2.304,P＜0.001),chronic obstructive pulmonary disease(OR=1.404,95％CI:1.131-1.744,P=0.002),hemodi-alysis(OR=2.210,95％CI:1.710-2.856,P＜0.001),serum lactate levels(OR=1.149,95％CI:1.100-1.200,P＜0.001)and sequential organs failure assessment(SOFA)score(OR=1.113,95％CI:1.080-1.146,P＜0.001)were independent risk factors.Based on multivariate Logistic regression analysis,a nomogram risk model of nosocomial death in patients with congestive heart failure complicated with CS was constructed.The nomogram model demonstrated an area under the ROC curve of 0.766,with a sensitivity of 72.6％and specificity of 66.9％.Internal validation showed good agreement between the predicted and actual values on the calibration curve.Decision curve analysis indicated that the model provided significant clinical net benefit.Conclusions Based on the MIMIC-Ⅳ database,this study developed a nomogram model incorporating age,gender,chronic obstructive pulmonary disease,peripheral oxygen saturation,body temperature＜36 ℃,hemodialysis,serum albumin,serum lactate,and SOFA score to predict in-hospital mortality in patients with CS complicated by congestive heart failure cardiogenic shock.The model demonstrated high discriminative ability,calibration,predictive performance,and clinical net benefit,enabling early identification of high-risk patients and optimization of treatment decisions.