Abstract
ObjectiveThis study aims to evaluate the accuracy of the Acute Physiology and Chronic Health Evaluation (APACHE) II score on different days in predicting the mortality of critically ill patients to identify the best time point for the APACHE II score.MethodsThe demographic and clinical data are retrieved from the Medical Information Mart for Intensive Care (MIMIC)-IV dataset. APACHE II scores on days 1, 2, 3, 5, 7, 14, and 28 of hospitalization are calculated, and their performance is evaluated using the area under the receiver operating characteristic (AUROC) analysis. The cut-off for defining the high risk of mortality is determined using Youden's index. The APACHE II score on day 3 is the best time point to predict hospital mortality of ICU patients. The Hosmer-Lemeshow goodness-of-fit test is then applied to evaluate the calibration of the day 3 APACHE II score.ResultsWe recruited 6,374 eligible subjects from the MIMIC-IV database. Day 3 is the optimal time point for obtaining the APACHE II score to predict the hospital mortality of patients. The best cut-off for day 3 APACHE II score is 17. When APACHE II score ≥17, the sensitivity for the non-survivors and survivors is 92.8 and 82.2%, respectively, and the positive predictive value (PPV) is 23.1%. When APACHE II socre <17, the specificity for non-survivors and survivors is 90.1 and 80.2%, respectively, and the negative predictive value (NPV) is 87.8%. When day-3 APACHE II is used to predict the hospital mortality, the AUROC is 0.743 (P <0.001). In the ≥17 group, the sensitivity of non-survivors and survivors is 92.2 and 81.3%, respectively, and the PPV is 30.3%. In the <17 group, the specificity of non-survivors and survivors is 100.0 and 80.2%, respectively, and the NPV is 81.6%. The Hosmer-Lemeshow test indicated day-3 APACHE II has a high predicting the hospital mortality (X2 = 6.198, P = 0.625, consistency = 79.4%). However, the day-1 APACHE II has a poor calibration in predicting the hospital mortality rate (X 2 = 294.898, P <0.001).ConclusionDay-3 APACHE II score is an optimal biomarker to predict the outcomes of ICU patients; 17 is the best cut-off for defining patients at high risk of mortality.
Highlights
Predicting the mortality of patients in ICU plays an important role in patient care and resource allocation
We found that the third-day APACHE II score is the optimal biomarker to predict the outcomes of ICU patients, and 17 is the best cut-off for defining patients at higher risk of mortality
This study found that the first-day APACHE II score has a poor calibration on hospital mortality of the included cohort of patients
Summary
Predicting the mortality of patients in ICU plays an important role in patient care and resource allocation. Several scoring systems have been developed to evaluate the severity of illness and predict the outcomes [3,4,5], especially the mortality [6, 7] of critically ill patients, such as Acute Physiology Chronic Health Evaluation II (APACHE II), Organ Dysfunction and Infection System, Sequential Organ Failure Assessment (SOFA) and Simplified Acute Physiology Score (SAPS). Among these severity-of-disease classification systems, the APACHE II score is the most commonly used method, which generates a point score ranging from 0 to 71 based upon initial values of 12 acute physiologic variables, age, and previous health status. These factors raise concerns that APACHE II score within 24 h may not be able to accurately predict the outcomes and mortality of critically ill patients
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
