ArticlePloS one2016
Simplified Acute Physiology Score II as Predictor of Mortality in Intensive Care Units: A Decision Curve Analysis.
Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.
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Who cites it
25 citing papers in PubMed.
- Prediction Model for Intensive Care Unit Mortality in Patients with Spine Fracture: Can Machine Learning be Used to Improve Current Standards?Neurocritical care · 2026Article
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- MaTrICS: Micromobility Associated With Trauma and Its Clinical and Socioeconomic Impact.Cureus · 2026Article
- Development and validation of a nomogram for predicting acute kidney injury in elderly patients in intensive care unit.Renal failure · 2025Article
- Multiplex Targeted Proteomic Analysis of Cytokine Ratios for ICU Mortality in Severe COVID-19.Proteomes · 2025Article
- Prognostic Impact of COVID-19 Inflammation Score Response: A Sub-Group Analysis on Critically Ill Patients of the RuxCoFlam Trial.Life (Basel, Switzerland) · 2025Article
- Subtle changes on electrocardiogram in severe patients with COVID-19 may be predictors of treatment outcome.Frontiers in artificial intelligence · 2025Article
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- Association between white blood cell-to-haemoglobin ratio and 30 day mortality in heart failure in intensive care unit.ESC heart failure · 2024Article
- Chest X-ray at Emergency Admission and Potential Association with Barotrauma in Mechanically Ventilated Patients: Experience from the Italian Core of the First Pandemic Peak.Tomography (Ann Arbor, Mich.) · 2023Article
- Postoperative high-sensitivity troponin T predicts 1-year mortality and days alive and out of hospital after orthotopic heart transplantation.European journal of medical research · 2023Article
- Association and prediction of red blood cell distribution width to albumin ratio in all-cause mortality of acute kidney injury in critically ill patients.Frontiers in medicine · 2023Article
- Interleukin 33, soluble suppression of tumorigenicity 2, interleukin 27, and galectin 3 as predictors for outcome in patients admitted to intensive care units.Open medicine (Warsaw, Poland) · 2023Article
- The value of comorbidities and illness severity scores as prognostic tools for early outcome estimation in patients with aneurysmal subarachnoid hemorrhage.Neurosurgical review · 2022Article
- Outcome in patients with open abdomen treatment for peritonitis: a multidomain approach outperforms single domain predictions.Journal of clinical monitoring and computing · 2022Article
- Tertiary peritonitis: A disease that should not be ignored.World journal of clinical cases · 2021Review
- Early Prediction of Seven-Day Mortality in Intensive Care Unit Using a Machine Learning Model: Results from the SPIN-UTI Project.Journal of clinical medicine · 2021Article
- The Relationship Between Prognostic Nutritional Index and All-Cause Mortality in Critically Ill Patients: A Retrospective Study.International journal of general medicine · 2021Article
- Score performance of SAPS 2 and SAPS 3 in combination with biomarkers IL-6, PCT or CRP.PloS one · 2020Article
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Authors and funding
6 authors.
Funding
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Abstract
backgroundEnd-of-life decision-making in Intensive care Units (ICUs) is difficult. The main problems encountered are the lack of a reliable prediction score for death and the fact that the opinion of patients is rarely taken into consideration. The Decision Curve Analysis (DCA) is a recent method developed to evaluate the prediction models and which takes into account the wishes of patients (or surrogates) to expose themselves to the risk of obtaining a false result. Our objective was to evaluate the clinical usefulness, with DCA, of the Simplified Acute Physiology Score II (SAPS II) to predict ICU mortality.
methodsWe conducted a retrospective cohort study from January 2011 to September 2015, in a medical-surgical 23-bed ICU at University Hospital. Performances of the SAPS II, a modified SAPS II (without AGE), and age to predict ICU mortality, were measured by a Receiver Operating Characteristic (ROC) analysis and DCA.
resultsAmong the 4.370 patients admitted, 23.3% died in the ICU. Mean (standard deviation) age was 56.8 (16.7) years, and median (first-third quartile) SAPS II was 48 (34-65). Areas under ROC curves were 0.828 (0.813-0.843) for SAPS II, 0.814 (0.798-0.829) for modified SAPS II and of 0.627 (0.608-0.646) for age. DCA showed a net benefit whatever the probability threshold, especially under 0.5.
conclusionDCA shows the benefits of the SAPS II to predict ICU mortality, especially when the probability threshold is low. Complementary studies are needed to define the exact role that the SAPS II can play in end-of-life decision-making in ICUs.
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