APACHE scoring as an indicator of mortality rate in ICU patients: a cohort study

Abstract

Introduction: Predictive scoring systems are tools that assess the magnitude of a patient’s illness and forecast disease prognosis, usually in the form of mortality, in the ICU. We aimed to determine the mortality rate among patients admitted to ICU using the Acute Physiology and Chronic Health Evaluation II (APACHE II) scoring system correlating with lengths of stay in the ICU. Methodology: A cohort study using team approach to care was conducted from July 2021 through July 2022 at KRL Hospital. Five hundred fifty-two patients aged 18–40 years, admitted for medical or surgical reasons (other than cardiac) who stayed in the ICU for more than 24 h were included. The APACHE II score was determined using 12 physiological variables at the end of the first 24 h of ICU admission. Data were analyzed using IBM Corp. released in 2015 (IBM SPSS Statistics for Windows, Version 23.0, Armonk, New York). Results: The average age of study participants was 36.34±2.77, ranging from 18 to 40 years. Three hundred fifteen participants were males and 237 were females. Patients were categorized into four separate groups as per their respective APACHE II scores. Patients with an APACHE II score of 31–40 were assigned to group 1. Patients with an APACHE II score of 21–30 were assigned to group 2. Patients with an APACHE II score of 11–20 were assigned to group 3. Lastly, patients with an APACHE II score of 3–10 were assigned to group 4. All patients in group 1 and group 2 died and none survived. Groups 1 and 2 contained a sum of 228 patients. A total of 123 patients were assigned to group 3, out of which 88 patients (71.54%) survived and 35 patients (28.45%) died. From these observations, it is evident that a higher APACHE II score is correlated with increased mortality. Conclusion: APACHE II scoring serves as an early warning indication of death and prompts clinicians to upgrade their treatment protocol. This makes it a useful tool for the clinical prediction of ICU mortality.