Dynamic APACHE II Score to Predict Outcome Among Intensive Care Unit Patients

Abstract

Purpose: The Acute Physiology and Chronic Health Evaluation II (APACHE II) score is used to determine disease severity and predict outcomes in critically ill patients. However, there is no dynamic APACHE II score for predicting outcomes among ICU patients.The aim of this study is to explore the optimal timing to predict the outcomes of ICU patients by dynamically evaluating APACHE II score.Methods: Study data of demographics and comorbidities from the first 24 h after ICU admission were retrospectively extracted from MIMIC-III, a multiparameter intensive care database. The primary outcome was hospital mortality. 90-day mortality was a secondary outcome. APACHE II scores on days 1, 2, 3, 5, 7, 14 and 28 were compared using area under the receiver operating characteristic (AUROC) analysis. Hospital survival was visualised using Kaplan-Meier Curves.Results:A total of 6374 eligible subjects were extracted from the MIMIC-III. Mean APACHE II score on day 1 were 18.4±6.3, hospital and 90-day mortality was 19.1% and 25.8%, respectively.The optimal timing where predicted hospital mortality was on day 3 with an area under the cure of 0.666 (0.607-0.726)(P＜0.0001). The best tradeoff for preciction was found at 17 score, more than 17 score predicted mortality of non-survivors with a sensitivity of 92.8% and PPV of 23.1%. Hosmer-lemeshow goodness of fit test showed that APACHE II 3 has a good predictive calibration ability (X2 =6.198, P=0.625) and consistency of predicted death and actual death was 79.4%. The calibration of APACHE II 1 was poor (X2=294.898, P<0.001).Conclusions: APACHE II on 3 dayis the optimal prognostic marker and 17 score provided the best dignostic accuracy to predict outcomes for ICU patients. These finding will help medical make clinical judgment.