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Peer-Reviewed Article September 29, 2026

Prognostic Value of the ACTION ICU Score Compared to GRACE and TIMI Scores in Non-ST-Segment Elevation Acute Coronary Syndromes

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Published in: Tunisian Journal of Emergency Medicine
Publisher: TN Academic Press • Tunisia • 3061-9165
DOI: https://doi.org/10.66759/dy5r4q27

Abstract

Non-ST-segment elevation acute coronary syndromes (NSTE-ACS) represent the primary manifestation of acute coronary syndromes, accounting for 60% to 70% of hospital admissions. Effective management in the emergency department (ED) relies on accurate risk stratification to guide triage. While established scores like GRACE and TIMI are widely used for long-term prognosis, they lack specific validation for predicting immediate in-hospital complications in the acute ED phase. This study compared the prognostic value of the ACTION ICU, GRACE, and TIMI scores for short-term complications and 6-month major adverse cardiovascular events (MACE). Methods We conducted a retrospective observational analysis of a prospective registry at the Ben Arous Regional Hospital, Tunisia, over a nine-year period (2014–2022). Inclusion of patients admitted for NSTE-ACS in the ED. Diagnostic performance was evaluated using Receiver Operating Characteristic (ROC) curves to identify optimal cut-off values for acute in-hospital complications (acute pulmonary edema, arrhythmias, death) and 6-month MACE. Results The cohort had a mean age of 60 ± 12 years with 59.3% males. In-hospital complications occurred in 6.3% of patients. For predicting these acute events, the ACTION ICU score significantly outperformed other models with an Area Under the Curve (AUC) of 0.88 (95% CI: 0.836–0.941), compared to 0.77 for GRACE and 0.59 for TIMI. An ACTION ICU cut-off value of >5.5 provided 80% sensitivity, 77.39% specificity, and a negative predictive value of 98.29%. Conversely, the GRACE score was the most accurate for 6-month MACE (AUC 0.707). Conclusion The ACTION ICU score is a superior tool for immediate ED triage, providing high accuracy in predicting short-term complications. Its systematic implementation could optimize intensive care unit resource allocation in constrained healthcare settings without compromising patient safety.

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