ReviewArchives of academic emergency medicine2023
HEART versus GRACE Score in Predicting the Outcomes of Patients with Acute Coronary Syndrome; a Systematic Review and Meta-Analysis.
Review in Archives of academic emergency medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 10 citations in OpenAlex.
- Comparing the Performance of Machine Learning Models and Conventional Risk Scores for Predicting Major Adverse Cardiovascular Cerebrovascular Events After Percutaneous Coronary Intervention in Patients With Acute Myocardial Infarction: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- ACEF score and its predictive performance in coronary artery disease patients undergoing PCI: a systematic review and meta-analysis of the C-statistic.AsiaIntervention · 2026Article
- Stress hyperglycemia ratio improves 28-day mortality prediction beyond GRACE score in critically ill patients with acute coronary syndrome: a retrospective cohort study from MIMIC-IV.BMC cardiovascular disorders · 2026Article
- Predicting long-term major adverse cardiac events after percutaneous coronary intervention in individuals with acute coronary syndrome and nonvalvular atrial fibrillation: a machine learning study.BMC cardiovascular disorders · 2026Article
- Impact of Atrial Fibrillation on Hospital Outcomes in NSTEMI Patients: A Retrospective Cohort Study.Journal of community hospital internal medicine perspectives · 2026Article
- Prognostic value of CALLY index in combination with the GRACE score among patients with acute myocardial infarction: a retrospective cohort study.Frontiers in cardiovascular medicine · 2026Article
- Article
- SVEAT score for early risk stratification of acute chest pain: a multicenter study.BMC emergency medicine · 2025Observational
- Improving chest pain risk assessment: validation of HEART, TIMI, GRACE, EDACS-ADP, and HET for MACE prediction in the emergency department.BMC emergency medicine · 2025Article
- The Power of Heuristics in Predicting Fracture Nonunion.Journal of clinical medicine · 2025Article
- Machine Learning Efficiency in Predicting Obstructive Coronary Artery Disease in Patients with Non-ST Elevation Acute Coronary Syndrome in the First Hours of Admission.Sovremennye tekhnologii v meditsine · 2025Article
- Anemia, Hyperglycemia, and Reduced Left Ventricular Ejection Fraction Improve the GRACE Score's Predictability for In-hospital Mortality in Acute Coronary Syndrome; Single-Centre Cross-Sectional Study.Open access emergency medicine : OAEM · 2025Article
- Age-related differences in coronary artery lesions and short-term prognosis in acute coronary syndrome patients.American journal of translational research · 2025Article
- Risk factors for mechanical complications in very elderly patients with acute myocardial infarction.Frontiers in medicine · 2025Article
- A Look at Archives of Academic Emergency Medicine Journal in 2023.Archives of academic emergency medicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Several scoring systems have been proposed to predict the outcomes of patients with ischemic heart disease. Global Registry of Acute Coronary Events (GRACE) and History, ECG, Age, Risk Factors, and Troponin (HEART) scores are two of the more widely used risk prediction tools in patients with acute coronary syndrome (ACS). The present systematic review and meta-analysis aimed to compare the value of GRACE and HEART scores in the outcome prediction of ACS patient. Method: The online databases of Medline, Embase, Web of Science, and Scopus were search until September 2022 for articles directly comparing GRACE and HEART scores value in prediction of outcome in patients with ACS. GRACE score cut-offs were categorized into two groups of less than and equal to 100 and more than 100, and HEART score cut-offs were categorized into three groups of less than 4, equal to 4, and more than 4. Investigated outcomes were major adverse cardiovascular events (MACE), acute myocardial infraction (AMI) and all-cause mortality. Results: 25 articles were included. The sensitivity and specificity of the GRACE score for prediction of MACE were 0.96 and 0.26 for cut-offs of ≤ 100, and 0.58 and 0.69 for cut-offs of >100, respectively. The sensitivity and specificity of the HEART score for prediction of MACE were 0.99 and 0.16 for cut-offs less than 4, 0.93 and 0.47 for equal to 4, and 0.77 and 0.78 for cut-offs greater than 4. GRACE score was shown to be predictive of AMI with sensitivity and specificity of 0.95 and 0.29, respectively. The analysis for the value of HEART score in the prediction of AMI a sensitivity and specificity of 0.94 and 0.48, respectively. The risk scores were not found to be suitable predictors of all-cause mortality. Conclusion: The results demonstrated the low specificity of GRACE and HEART scores in predicting the MACE, AMI and all-cause mortality, irrespective of the utilized cut-off. Considering the acceptable sensitivity of two scores in predicting the MACE and AMI, these scores were more suitable to be used as a rule-out tool for identification of ACS patients with low risk of developing adverse outcomes.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.