Four early warning scores predict mortality in emergency surgical patients at University Teaching Hospital, Lusaka: a prospective observational study

Abstract

Purpose: The value of early warning scoring systems has been established in high-income countries. There is little evidence for their use in low-resource settings. We aimed to compare existing early warning scores to predict 30-day mortality. Methods: University Teaching Hospital is a tertiary center in Lusaka, Zambia. Adult surgical patients, excluding obstetrics, admitted for > 24 hr were included in this prospective observational study. On days 1 to 3 of admission, we collected data on patient demographics, heart rate, blood pressure, oxygen saturation, oxygen administration, temperature, consciousness level, and mobility. Two-, three-, and 30-day mortality were recorded with their associated variables analyzed using area under receiver operating curves (AUROC) for the National Early Warning Score (NEWS); the Modified Early Warning Score (MEWS); a modified Hypotension, Oxygen Saturation, Temperature, ECG, Loss of Independence (mHOTEL) score; and the Tachypnea, Oxygen saturation, Temperature, Alertness, Loss of Independence (TOTAL) score. Results: Data were available for 254 patients from March 2017 to July 2017. Eighteen (7.5%) patients died at 30 days. The four early warning scores were found to be predictive of 30-day mortality: MEWS (AUROC, 0.76; 95% confidence interval [CI], 0.63 to 0.88; P < 0.001), NEWS (AUROC 0.805; 95% CI, 0.688 to 0.92; P < 0.001), mHOTEL (AUROC 0.759; 95% CI, 0.63 to 0.89, P < 0.001), and TOTAL (AUROC 0.782; 95% CI, 0.66 to 0.90; P < 0.001). Conclusions: We validated four scoring systems in predicting mortality in a Zambian surgical population. Further work is required to assess if implementation of these scoring systems can improve outcomes.