Key result
SCIENCE score predicts CICU mortality with ~0.78 AUC, substituting M-CARS when anion gap is unavailable.
Why the study?
The established Mayo Cardiac Admission Risk Score requires specialized laboratory tests, so this study evaluated the simpler Sardjito Cardiovascular Intensive Care score as an alternative for predicting CICU mortality.
Does the SCIENCE score predict CICU and in-hospital mortality as well as M-CARS in cardiovascular intensive care patients?
Cohort (n=1,503)
No
Does the SCIENCE score predict CICU and in-hospital mortality as well as M-CARS in cardiovascular intensive care patients?
The SCIENCE score provides acceptable predictive performance for CICU and in-hospital mortality and may serve as a practical alternative to M-CARS in settings with limited laboratory capabilities.
Answers are grounded in this paper and cite their sources.
May offer practical alternative to M-CARS when anion gap unavailable; leaves open need for prospective validation.
Background: The cardiovascular intensive care unit (CICU) has evolved into a multidisciplinary unit managing critically ill patients with high mortality rates. In 2022, the Sardjito Cardiovascular Intensive Care (SCIENCE) score introduced seven simple parameters assessed within the first 24 h to predict CICU mortality. The Mayo Cardiac Admission Risk Score (M-CARS) is a well-established tool for predicting CICU mortality but requires specialized laboratory tests. This study compared the predictive performance of the SCIENCE score and M-CARS and validated SCIENCE at its development site. Methods: This retrospective cohort study was conducted between February 2022 and September 2024 and included CICU patients at Sardjito Hospital. Outcomes assessed were CICU and in-hospital mortality. Predictive performance was evaluated by accuracy, discrimination, and calibration (Hosmer–Lemeshow test). Results: Over 50% of the initial participants were excluded due to missing M-CARS data (particularly the anion gap), leaving 1,503 eligible patients. M-CARS showed good predictive performance for CICU mortality (accuracy 70.9%, area under the curve (AUC) 0.804, P = 0.685) and in-hospital mortality (accuracy 72.2%, AUC 0.797, P = 0.303). The SCIENCE score also showed good predictive performance for CICU mortality (accuracy 63.7%, AUC 0.775, P = 0.059) and in-hospital mortality (accuracy 65.8%, AUC 0.767, P = 0.352). Acute stroke (hemorrhagic and non-hemorrhagic) was associated with higher CICU and in-hospital mortality (P < 0.05). Conclusion: Both the SCIENCE score and M-CARS provide acceptable predictive performance for CICU patients. However, as M-CARS has limited applicability in some settings, the SCIENCE score may serve as a more practical alternative.
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Adani et al. (2026) conducted a cohort in Cardiovascular intensive care unit (CICU) admission (n=1,503). SCIENCE score vs. M-CARS was evaluated on CICU mortality prediction (AUC) (AUC 0.775, 95% CI 0.751-0.800, p=<0.001). The SCIENCE score provided acceptable predictive performance for CICU mortality (AUC 0.775), serving as a practical alternative to M-CARS (AUC 0.804) when anion gap data is unavailable.
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