<![CDATA[Background: TIMI and GRACE scores are widely used for prognostic risk stratification in acute coronary syndrome (ACS), yet comparative evidence across ACS subtypes, settings, follow-up periods, and outcomes remains heterogeneous. This scoping review mapped evidence comparing TIMI and GRACE scores for predicting mortality and MACE in patients with ACS or suspected ACS. Methods: This scooping review followed the PRISMA-ScR guidelines, the PCC framework, and the Arksey and O’Malley approach. Searches were conducted in ProQuest, Scopus, and CINAHL using Boolean search terms related to TIMI, GRACE, ACS, mortality, and MACE. Eligible studies were empirical quantitative studies comparing TIMI and GRACE for predicting mortality and MACE in adults with ACS. Records were screened, full texts were assessed, data were recorded using a standardized form, and findings were synthesized narratively based on outcomes and clinical settings. Results: A total of 187 records were identified, 45 duplicates were removed, 142 records were screened, 44 full-text reports were assessed, and 12 studies were included. Studies were published between 2022 and 2025 and included at least 12,039 participants from China, Lithuania, India, Turkey, Spain, Pakistan, and Iran. For mortality, GRACE more consistently demonstrated stronger discrimination than TIMI, particularly in NSTEMI, broader AMI cohorts, and STEMI patients undergoing reperfusion or PCI. For MACE, findings were more heterogeneous; GRACE generally performed better in confirmed NSTE-ACS and STEMI PCI cohorts, whereas TIMI showed comparable or sometimes higher discrimination than GRACE in undifferentiated emergency chest pain populations. Conclusion: The comparative performance of TIMI and GRACE depends on ACS phenotype, clinical context, and outcome definition. GRACE appears more robust for mortality prediction, while TIMI retains practical value as a simple bedside tool, especially in rapid triage contexts. Future studies should standardize MACE definitions, reporting metrics, and subgroup analyses across ACS populations.]]>
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