Abstract

BackgroundIllness predictive scoring systems are significant and meaningful adjuncts of patient management in the Intensive Care Unit (ICU). They assist in predicting patient outcomes, improve clinical decision making and provide insight into the effectiveness of care and management of patients while optimizing the use of hospital resources. We evaluated mortality predictive performance of Simplified Acute Physiology Score (SAPS 3) and Mortality Probability Models (MPM0-III) and compared their performance in predicting outcome as well as identifying disease pattern and factors associated with increased mortality.MethodsThis was a retrospective cohort study of adult patients admitted to the ICU of the Aga Khan Hospital, Dar- es- Salaam, Tanzania between August 2018 and April 2020. Demographics, clinical characteristics, outcomes, source of admission, primary admission category, length of stay and the support provided with the worst physiological data within the first hour of ICU admission were extracted. SAPS 3 and MPM0-III scores were calculated using an online web-based calculator. The performance of each model was assessed by discrimination and calibration. Discrimination between survivors and non–survivors was assessed by the area under the receiver operator characteristic curve (ROC) and calibration was estimated using the Hosmer-Lemeshow goodness-of-fit test.ResultsA total of 331 patients were enrolled in the study with a median age of 58 years (IQR 43-71), most of whom were male (n = 208, 62.8%), of African origin (n = 178, 53.8%) and admitted from the emergency department (n = 306, 92.4%). In- hospital mortality of critically ill patients was 16.1%. Discrimination was very good for all models, the area under the receiver-operating characteristic (ROC) curve for SAPS 3 and MPM0-III was 0.89 (95% CI [0.844–0.935]) and 0.90 (95% CI [0.864–0.944]) respectively. Calibration as calculated by Hosmer-Lemeshow goodness-of-fit test showed good calibration for SAPS 3 and MPM0-III with Chi- square values of 4.61 and 5.08 respectively and P–Value > 0.05.ConclusionBoth SAPS 3 and MPM0-III performed well in predicting mortality and outcome in our cohort of patients admitted to the intensive care unit of a private tertiary hospital. The in-hospital mortality of critically ill patients was lower compared to studies done in other intensive care units in tertiary referral hospitals within Tanzania.

Highlights

  • Illness predictive scoring systems are significant and meaningful adjuncts of patient management in the Intensive Care Unit (ICU)

  • Most of the patients were admitted to the ICU from the emergency department (n = 306, 92.5%), who were at home prior (n = 318, 96.1%) with majority of them suffering from neurological disease (n = 63, 19%), sepsis (n = 60, 18.1%), respiratory (n = 36, 10.9%) and cardiovascular (n = 36, 10.9%) related conditions

  • The MPM0III was well calibrated amongst the critical ill patients admitted to the ICU of the Aga Khan University Hospital, Nairobi (Lukoko et al, 2020) but showed poor calibration amongst all adult patients admitted to Rwanda’s two public ICUs (Riviello et al, 2016). These findings highlight the similar treatment protocols and interventions between two sister hospitals located in different geographical regions. In this retrospective study we aimed to identify patient demographics, disease patterns, clinical outcomes as well as factors associated with higher risk of mortality in patients admitted to the ICU of the Aga Khan Hospital, Dar –es Salaam

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Summary

Introduction

Illness predictive scoring systems are significant and meaningful adjuncts of patient management in the Intensive Care Unit (ICU). They assist in predicting patient outcomes, improve clinical decision making and provide insight into the effectiveness of care and management of patients while optimizing the use of hospital resources. Discrimination was very good for all models, the area under the receiver-operating characteristic (ROC) curve for SAPS 3 and MPM0-III was 0.89 (95% CI [0.844–0.935]) and 0.90 (95% CI [0.864– 0.944]) respectively. Both SAPS 3 and MPM0-III performed well in predicting mortality and outcome in our cohort of patients admitted to the intensive care unit of a private tertiary. The burden of critical care and ICU mortality is greatest in countries with low global national income (Vincent et al, 2014). The availability and improvement of quality of care of critical illness in LMICs is necessary to reduce this burden and even more significant in the coming years as the population ages and prevalence of comorbidities increases (Adhikari et al, 2010)

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