Epidemiology and Outcomes of Critical Illness and Novel Predictors of Mortality in an Ethiopian Medical Intensive Care Unit

Abstract

Low- and middle-income countries (LMICs) bear most of the global burden of critical illness. Managing this burden requires improved understanding of epidemiology and outcomes in LMIC intensive care units (ICUs), including LMIC-specific mortality prediction scores. This study was a retrospective observational study at Tikur Anbessa Specialized Hospital in Addis Ababa, Ethiopia, examining all consecutive medical ICU admissions from June 2014 to April 2015. The primary outcome was ICU mortality; secondary outcomes were prolonged ICU stay and prolonged mechanical ventilation. ICU mortality prediction models were created using multivariable logistic regression and compared with the Mortality Probability Model-II (MPM-II). Associations with secondary outcomes were examined with multivariable logistic regression. There were 198 admissions during the study period; mortality was 35%. Age, shock on admission, mechanical ventilation, human immunodeficiency virus, and Glasgow Coma Scale ≤8 were associated with ICU mortality. The receiver operating characteristic curve for this 5-factor model had an AUC of 0.8205 versus 0.7468 for MPM-II, favoring the simplified new model. Mechanical ventilation and lack of shock were associated with prolonged ICU stays. Mortality in an LMIC medical ICU was high. This study examines an LMIC medical ICU population, showing a simplified prediction model may predict mortality as well as complex models.