[Predictive value of six critical illness scores for 28-day death risk in comprehensive and specialized intensive care unit patients based on MIMIC-IV database]

Abstract

Objective: To explore the basic characteristics of various types of intensive care unit (ICU) patients and the predictive value of six common disease severity scores in critically ill patients on the first day on the 28-day death risk.

Methods: The general information, disease severity scores [acute physiology score III (APS III), Oxford acute disease severity (OASIS) score, Logistic organ dysfunction score (LODS), simplified acute physiology score II (SAPS II), systemic inflammatory response syndrome (SIRS) score and sequential organ failure assessment (SOFA) score], prognosis and other indicators of critically ill patients admitted from 2008 to 2019 were extracted from Medical Information Mart for Intensive Care-IV 2.0 (MIMIC-IV 2.0). The receiver operator characteristic curve (ROC curve) of six critical illness scores for 28-day death risk of patients in various ICU, and the area under the ROC curve (AUC) was calculated, the optimal Youden index was used to determine the cut-off value, and the AUC of various ICU was verified by Delong method.

Results: A total of 53 150 critically ill patients were enrolled, with medical ICU (MICU) accounted for the most (19.25%, n = 10 233), followed by cardiac vascular ICU (CVICU) with 17.78%(n = 9 450), and neurological ICU (NICU) accounted for the least (6.25%, n = 3 320). The patients in coronary care unit (CCU) were the oldest [years old: 71.79 (60.27, 82.33)]. The length of ICU stay in NICU was the longest [days: 2.84 (1.51, 5.49)] and accounted for the highest proportion of total length of hospital stay [63.51% (34.61%, 97.07%)]. The patients in comprehensive ICU had the shortest length of ICU stay [days: 1.75 (0.99, 3.05)]. The patients in CVICU had the lowest proportion of length of ICU stay to total length of hospital stay [27.69% (18.68%, 45.18%)]. The six scores within the first day of ICU admission in NICU patients were lower than those in the other ICU, while APS III, LODS, OASIS, and SOFA scores in MICU patients were higher than those in the other ICU. SAP II and SIRS scores were both the highest in CVICU, respectively. In terms of prognosis, MICU patients had the highest 28-day mortality (14.14%, 1 447/10 233), while CVICU patients had the lowest (2.88%, 272/9 450). ROC curve analysis of the predictive value of each score on the 28-day death risk of various ICU patients showed that, the predictive value of APS III, LODS, and SAPS II in comprehensive ICU were higher [AUC and 95% confidence interval (95%CI) were 0.84 (0.83-0.85), 0.82 (0.81-0.84), and 0.83 (0.82-0.84), respectively]. The predictive value of OASIS, LODS, and SAPS II in surgical ICU (SICU) were higher [AUC and 95%CI were 0.80 (0.79-0.82), 0.79 (0.78-0.81), and 0.79 (0.77-0.80), respectively]. The predictive value of APS III and SAPS II in MICU were higher [AUC and 95%CI were 0.84 (0.82-0.85) and 0.82 (0.81-0.83), respectively]. The predictive value of APS III and SAPS II in CCU were higher [AUC and 95%CI were 0.86 (0.85-0.88) and 0.85 (0.83-0.86), respectively]. The predictive value of LODS and SAPS II in trauma ICU (TICU) were higher [AUC and 95%CI were 0.83 (0.82-0.83) and 0.83 (0.82-0.84), respectively]. The predictive value of OASIS and SAPS II in NICU were higher [AUC and 95%CI were 0.83 (0.80-0.85) and 0.81 (0.78-0.83), respectively]. The predictive value of APS III, LODS, and SAPS II in CVICU were higher [AUC and 95%CI were 0.84 (0.83-0.85), 0.81 (0.80-0.82), and 0.78 (0.77-0.78), respectively].

Conclusions: For the patients in comprehensive ICU, MICU, CCU, and CVICU, APS III or SAPS II can be applied for predicting 28-day death risk. For the patients in SICU and NICU, OASIS or SAPS II can be applied to predict 28-day death risk. For the patients in TICU, SAPS II or LODS can be applied for predicting 28-day death risk. For CVICU patients, APS III or LODS can be applied to predict 28-day death risk.