The predictive performance of SAPS 2 and SAPS 3 in an intermediate care unit for internal medicine at a German university transplant center; A retrospective analysis.

Michael Jahn,Antonios Katsounas,Ali Canbay,Jan Rekowski,Andreas Kribben,Guido Gerken,Chiara Lazzeri

doi:10.1371/journal.pone.0222164

Abstract

ObjectiveTo analyze and compare the performance of the Simplified-Acute-Physiology-Score (SAPS) 2 and SAPS 3 among intermediate care patients with internal disorders.Materials and methodsWe conducted a retrospective single-center analysis in patients (n = 305) admitted to an intermediate-care-unit (ImCU) for internal medicine at the University Hospital Essen, Germany. We employed and compared the SAPS 2 vs. the SAPS 3 scoring system for the assessment of disease severity and prediction of mortality rates among patients admitted to the ImCU within an 18-month period. Both scores, which utilize parameters recorded at admission to the intensive-care-unit (ICU), represent the most widely applied scoring systems in European intensive care medicine. The area-under-the-receiver-operating-characteristic-curve (AUROC) was used to evaluate the SAPS 2 and SAPS 3 discrimination performance. Ultimately, standardized-mortality-ratios (SMRs) were calculated alongside their respective 95%-confidence-intervals (95% CI) in order to determine the observed-to-expected death ratio and calibration belt plots were generated to evaluate the SAPS 2 and SAPS 3 calibration performance.ResultsBoth scores provided acceptable discrimination performance, i.e., the AUROC was 0.71 (95% CI, 0.65–0.77) for SAPS 2 and 0.77 (95% CI, 0.72–0.82) for SAPS 3. Against the observed in-hospital mortality of 30.2%, SAPS 2 showed a weak performance with a predicted mortality of 17.4% and a SMR of 1.74 (95% CI, 1.38–2.09), especially in association with liver diseases and/or sepsis. SAPS 3 performed accurately, resulting in a predicted mortality of 29.9% and a SMR of 1.01 (95% CI, 0.8–1.21). Based on Calibration belt plots, SAPS 2 showed a poor calibration-performance especially in patients with low mortality risk (P<0.001), while SAPS 3 exhibited a highly accurate calibration performance (P = 0.906) across all risk levels.ConclusionsIn our study, the SAPS 3 exhibited high accuracy in prediction of mortality in ImCU patients with internal disorders. In contrast, the SAPS 2 underestimated mortality particularly in patients with liver diseases and sepsis.

Highlights

The use of in-hospital mortality prediction scores at admission to an intensive care unit (ICU) has become a viable evaluation method for treatment outcomes in critically ill patients [1]
Against the observed in-hospital mortality of 30.2%, Simplified Acute Physiology Score (SAPS) 2 showed a weak performance with a predicted mortality of 17.4% and a standardized mortality ratios (SMRs) of 1.74, especially in association
We observed a high rate of patients with chronic kidney diseases (CKD) based on the KDIGO-criteria [31] (n = 131; 43.0%, of those, n = 39 with end-stage CKD) and patients with systemic immunosuppression after solid organ transplantation (n = 55, 18.0%; of those, n = 22 post liver transplantation, n = 28 post kidney transplantation, and n = 5 post combined pancreas-kidney transplantation, Table 3)

Summary

Introduction

The use of in-hospital mortality prediction scores at admission to an intensive care unit (ICU) has become a viable evaluation method for treatment outcomes in critically ill patients [1]. In contrast to crude mortality data, such scores provide a risk-adjusted mortality assessment by considering various grades of disease severity and other prerequisites or predisposing conditions. Given an acceptable calibration performance, SMRs are useful tools, which can be used to evaluate interventions and/or quality of clinical management within an ICU or across a group of ICUs with comparable configurations over time. SMRs can act as benchmarking parameters for performance assessment and improvement in an ICU with evolving cost-containment policies and medical practices or structures, as (for example) a decreasing SMR may indicate the presence of some particular change that is beneficially affecting mortality [9]

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