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Published on: June 10, 2025
GRACE score predicts heart failure admission following acute coronary syndrome
David A McAllister1, Nynke Halbesma2, Kathryn Carruthers3
1Centre for Population Health Sciences, University of Edinburgh, UK david.mcallister@ed.ac.uk.
Insights
The Global Registry of Acute Coronary Events (GRACE) score effectively predicts heart failure admissions in patients with acute coronary syndrome (ACS). This score can identify high-risk individuals for targeted monitoring and treatment to prevent congestive heart failure (CHF).
Area of Science:
- Cardiology
- Clinical Risk Prediction
- Public Health
Background:
- Congestive heart failure (CHF) is a significant complication of acute coronary syndrome (ACS).
- Existing risk scores for ACS have not reliably predicted the subsequent risk of developing CHF.
- There is a need for validated tools to identify ACS patients at high risk for CHF.
Purpose of the Study:
- To evaluate the predictive capability of the at-discharge Global Registry of Acute Coronary Events (GRACE) score for subsequent heart failure admissions in patients with ACS.
- To determine if the GRACE score can identify patients who will develop CHF after an acute coronary event.
Main Methods:
- A retrospective analysis of 1,956 patients admitted with ACS between June 1999 and September 2009.
- Utilized five-year mortality and hospitalization data from a single center within the GRACE registry.
- Defined CHF using the WHO International Classification of Diseases 10 code I50 and employed Cox models to estimate hazard ratios for CHF admission based on GRACE score quintiles, adjusting for relevant covariates.
Main Results:
- Over a median follow-up of 3.8 years, 12% of patients were admitted with CHF.
- Patients in the highest GRACE score quintile experienced significantly more CHF admissions (116 vs. 17) and a shorter time to first admission compared to the lowest quintile.
- Each standard deviation increase in GRACE score was associated with a more than two-fold higher risk of CHF admission (adjusted HR 2.49).
- The GRACE score demonstrated a C-statistic of 0.74 for predicting 1-year CHF admission.
Conclusions:
- The at-discharge GRACE score is a significant predictor of heart failure admissions following acute coronary syndrome.
- The GRACE score can be utilized to identify ACS patients at high risk for developing CHF.
- Targeted clinical monitoring and therapeutic interventions can be implemented for high-risk ACS patients identified by the GRACE score.
Background:
Congestive heart failure (CHF) is a common and preventable complication of acute coronary syndrome (ACS). Nevertheless, ACS risk scores have not been shown to predict CHF risk. We investigated whether the at-discharge Global Registry of Acute Coronary Events (GRACE) score predicts heart failure admission following ACS.
Methods And Results:
Five-year mortality and hospitalization data were obtained for patients admitted with ACS from June 1999 to September 2009 to a single centre of the GRACE registry. CHF was defined as any admission assigned WHO International Classification of Diseases 10 diagnostic code I50. The hazard ratio (HR) for CHF according to GRACE score was estimated in Cox models adjusting for age, gender and the presence of CHF on index admission. Among 1,956 patients, CHF was recorded on index admission in 141 patients (7%), and 243 (12%) were admitted with CHF over 3.8 median years of follow-up. Compared to the lowest quintile, patients in the highest GRACE score quintile had more CHF admissions (116 vs 17) and a shorter time to first admission (1.2 vs 2.0 years, HR 9.87, 95% CI 5.93-16.43). Per standard deviation increment in GRACE score, the instantaneous risk was more than two-fold higher (HR 2.28; 95% CI 2.02-2.57), including after adjustment for CHF on index admission, age and gender (HR 2.49; 95% CI 2.06-3.02). The C-statistic for CHF admission at 1-year was 0.74 (95% CI 0.70-0.79).
Conclusions:
The GRACE score predicts CHF admission, and may therefore be used to target ACS patients at high risk of CHF with clinical monitoring and therapies.
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