Development and pilot testing of the AMPS model for predicting ICU mortality in low and middle income countries

Mortality prediction models developed in high-income country intensive care units (ICUs) may perform poorly in low–middle-income country (LMIC) ICUs due to differences in case mix and provision of life-supporting interventions. This study aims to develop a novel prognostic score and investigate its precision, discrimination, and calibration properties in predicting ICU mortality. Predictor variables were identified by reviewing relevant published studies from LMICs. The most frequently cited variables were selected to develop A Mortality Predictor Score (AMPS). Subsequently, the tool was assessed for accuracy, discrimination, and calibration using the Brier score, area under receiver operating characteristic curve (AUROC), reliability diagram and Decision curve analysis by using data gathered from the ICU of Black Lion Hospital between September 2019 and September 2020. Its prognostic ability was compared with the mortality prediction model II (MPM II) and ICU priority level. P p-value less than or equal to 0.05 was considered significant. The commonly identified model variables were Altered Mental status, Mechanical ventilation, More than two organ systems diagnosis, Pressure (systolic) less than 90, Potentially irreversible condition, Suspected infection, and Severe hypoalbuminemia (serum albumin