Acute Physiologic and Chronic Health Evaluation II and Simplified Acute Physiology Score 3 Scores as Predictors of Mortality in Cardiac Surgery.

Authors

Tatiani Bellettini-Santos, Rafael Folador Frederico, Silas Nascimento Ronchi, Jackelyne Lopes Silva, Heloísa Faltz Pimentel, Michelle Lima Garcez

Published in

Brazilian journal of cardiovascular surgery. Volume 41. Issue 3. Pages e20250098. Sep 21, 2026. Epub Sep 21, 2026.

Abstract

Acute Physiologic and Chronic Health Evaluation (APACHE) II is an effective tool to predict outcomes in cardiac surgery recovery. The present study aimed to evaluate the efficacy and compare the performance of the APACHE II and Simplified Acute Physiology Score (SAPS 3) scoring tools as predictive indices of mortality in cardiac surgery patients.
This was a retrospective observational study, evaluating patients over 18 years of age who underwent cardiac surgeries between 2020 and 2023. A receiver operating characteristic curve analysis was conducted to evaluate the sensitivity and specificity of the APACHE II and SAPS 3 tools in detecting intensive care unit (ICU) mortality in critically ill patients. Binary logistic regression was performed to assess the odds of mortality between groups (primary outcome) using data on comorbidities.
APACHE II was efficient in predicting mortality in cardiac surgery (sensitivity = 81%; specificity = 75%) as was SAPS 3 (sensitivity = 75%; specificity = 64%). Binary logistic regression revealed that mortality was significantly associated with comorbidities (chronic obstructive pulmonary disease and non-dialysis-dependent chronic kidney disease) and the type of surgery, with a higher risk in emergency procedures compared to elective ones.
In conclusion, APACHE II and SAPS 3 proved to be efficient tools for predicting mortality in cardiac surgery patients admitted to the ICU. This study contributes to understanding these tools in a regional context and specifically in cardiac surgeries, as well as assessing other predictors that may be important for idenjpgying risk groups and predicting mortality after cardiac surgeries.

PMID:
42776133
Bibliographic data and abstract were imported from PubMed on 23 Sep 2026.

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