Multiple organ scoring systems for predicting in-hospital mortality of sepsis patients in the intensive care unit
Xuan Zhou1, Zhenen Zhang1, Huimin Wang1
1Department of Intensive Care Unit, Jianhu County Branch of Northern Jiangsu People's Hospital, Yancheng, Jiangsu, 224700, China.
Objective:
This study aims to comprehensively evaluate the Charlson Comorbidity Index (CCI), Logistic Organ Dysfunction System (LODS) score, Acute Physiology Score III (APS III), Simplified Acute Physiology Score II (SAPS II), and Sequential Organ Failure Assessment (SOFA) in order to provide a more scientifically rigorous and effective tool for predicting mortality risk among sepsis patients in the Intensive Care Unit (ICU).
Methods:
The demographic information and sepsis-related data were extracted from the MIMIC-IV database for patients admitted to the ICU with a diagnosis of sepsis. The predictive performance of CCI, LODS, APS III, SAPS II, and SOFA scoring systems in terms of ICU mortality was evaluated by comparing receiver operating characteristic (ROC) curves. Multivariate regression identified predictors, later validated with a nomogram. Finally, the dataset was divided into a training set and a validation set at a ratio of 7:3 to assess the clinical utility of the prediction model through ROC curves.
Results:
The study enrolled a total of 17,226 patients with a median age of 67.65 (55.79, 78.82) years; among them, males accounted for 57.69%. Within this cohort, a total of 1,115 (6.47%) individuals succumbed during their admission to the ICU. The ROC curve demonstrated that both APS III and LODS score exhibited robust predictive value for ICU mortality. Multivariate regression analysis revealed that CCI, APS III score, LODS score, respiratory rate, body temperature, and race served as potential predictors. Combining these variables into a nomogram showed strong clinical utility, with AUCs of 0.803 (training set) and 0.797 (validation set).
Conclusions:
Organ failure scores hold significant clinical relevance in predicting mortality among sepsis patients in the ICU. Augmenting predictive accuracy can be achieved by integrating the CCI, APS III score, LODS score, mean respiratory rate, and body temperature during the initial 24 h following ICU admission.
