The SAPS 3 score as a predictor of hospital mortality in a South African tertiary intensive care unit: A prospective cohort study.

Abstract

Background No African countries were included in the development of the Simplified Acute Physiology Score 3 (SAPS 3). This study aimed to assess the performance of the SAPS 3 as a predictor of hospital mortality in patients admitted to a multidisciplinary tertiary intensive care unit (ICU) in South Africa. Methods A prospective cohort study was undertaken in a tertiary single-centre closed multidisciplinary ICU with 16 beds over 12 months in 2017. First time admissions 12 years and over were included. Exclusions were patients who died within six hours of admission, incomplete data sets and unknown outcome after ICU discharge. Demographic data, clinical admission data and co-morbidities were recorded. The SAPS 3 score was calculated within the first hour of ICU admission. The highest Sequential Organ Failure Assessment score, vasopressor use, mechanical ventilation requirements and details of acute kidney injury, if present, were recorded. Discrimination of the model was evaluated using an area under the receiver operating characteristic curve (AUROC) and calibration by the Hosmer-Lemeshow (HL) Goodness of Fit Test (Ĉ and Ĥ statistic). The observed versus the SAPS 3 model predicted mortality ratios were compared and the standardized mortality ratio (SMR) was calculated. Results A total of 829 admissions with a mean SAPS 3 (SD) of 48.1 (16) were included. Of patients with a known human immunodeficiency virus (HIV) status, 32,4% were positive. The ICU and hospital mortality rates were 13.3% and 21.4% respectively. The SAPS 3 model had a AUROC of 0.796 and HLĈ and Ĥ statistics were 12.1 and 11.8 (p-values 0.15 and 0.16).

Critically ill COVID-19 patients in northeast Brazil: mortality predictors during the first and second waves including SAPS 3

“…The SAPS 3 is a well-validated scoring system widely used around the world for the prediction of hospital mortality. 21 , 22 However, a recent study investigated the performance of the SAPS 3 score in 30.571 patients admitted to private ICUs in Brazil. The authors investigated if adjustments in the SAPS 3 score modifies its performance and suggested that SAPS 3 should be used with caution for mortality prognosis in critically ill patients with COVID-19.…”

Long-stay medical-surgical intensive care unit patients in South Africa: Quality of life and mortality 1 year after discharge

“…[9,28,29] The ICU and hospital mortality of 31.1% and 42.9%, respectively, in our long-stay cohort are also high taking into account that the overall 2017 ICU and hospital mortality in the same unit and hospital for all ICU admissions were 13.3% and 21.4%, respectively. [17] It is worth noting that 21.2% of the deaths occurred while in hospital post ICU discharge, and a further 18.2% occurred within 6 months after hospital discharge. This finding points towards the fact that long-stay patients warrant some form of monitoring after discharge from the ICU for setbacks, both in the hospital and on an outpatient basis.…”

“…In SA, ICU admissions tend to be younger, HIV-positive rates are high, and there is a RESEARCH preponderance of surgical emergency and trauma admissions. [17][18][19] These variations and the large proportion of the ICU budget that is spent on long-stay ICU survivors necessitate that we ascertain survival and the HRQOL in the SA setting.…”

Mortality risk prediction models: Methods of assessing discrimination and calibration and what they mean

“…In the current SAJCC issue, Pazi et al, [12] using a cohort of 829 patients admitted to an adult ICU in a tertiary hospital in South Africa (SA), have developed a SAPS III-based mortality prediction model calibrated to their specific ICU population using data available from a previous SAPS III validation study. [13] Data were collected for one year starting in January 2017. They reported a mortality rate of 21.35%.…”