Extension of the GRACE score for non-ST-elevation acute coronary syndrome: a development and validation study in ten
Florian A Wenzl1, Klaus F Kofoed2, Moa Simonsson3
1National Health Service England, London, UK; Center for Molecular Cardiology, University of Zürich, Zürich, Switzerland; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; Department of Clinical Sciences, Karolinska Institute, Stockholm, Sweden.
Insights
The updated GRACE 3.0 score improves risk assessment for non-ST-elevation acute coronary syndrome (NSTE-ACS) patients. It accurately predicts mortality and identifies individuals who benefit from early invasive management.
Area of Science:
- Cardiology
- Medical Informatics
- Machine Learning in Healthcare
Background:
- The Global Registry of Acute Coronary Events (GRACE) scoring system is crucial for managing non-ST-elevation acute coronary syndrome (NSTE-ACS).
- Existing models require broader validation, particularly for sex-specific predictions and long-term outcomes.
- Personalized prediction of early invasive management benefits is needed.
Purpose of the Study:
- To validate the GRACE 3.0 scoring system for in-hospital and 1-year mortality in NSTE-ACS patients.
- To develop and validate a model predicting the individualized treatment effect of early invasive management.
- To assess the clinical utility and discriminative ability of updated GRACE models.
Main Methods:
- Utilized data from 609,063 NSTE-ACS patients across ten countries (2005-2024).
- Developed machine learning models for in-hospital and 1-year mortality, externally validated across multiple countries.
- Created and validated a separate model for the individualized effect of early vs. delayed invasive coronary angiography and revascularization.
Main Results:
- The GRACE 3.0 in-hospital and 1-year mortality models demonstrated excellent discrimination (AUCs 0.90 and 0.84, respectively) and calibration upon external validation.
- The individualized treatment effect model successfully identified patients benefiting from early invasive management, showing a significant risk reduction (HR 0.60).
- The updated models showed improved discrimination and risk reclassification compared to GRACE 2.0.
Conclusions:
- The GRACE 3.0 scoring system is a validated, practical tool for personalized risk assessment in NSTE-ACS.
- Predicting individual long-term benefits from early invasive strategies can refine future clinical trial designs.
- Current treatment strategies may incompletely capture all NSTE-ACS patients who benefit from early intervention.
Background:
The Global Registry of Acute Coronary Events (GRACE) scoring system guides the management of patients with non-ST-elevation acute coronary syndrome (NSTE-ACS) according to current guidelines. However, broad validation of the sex-specific GRACE 3.0 in-hospital mortality model, and corresponding models for predicting long-term mortality and the personalised effect of early invasive management, are still needed.
Methods:
We used data of 609 063 patients with NSTE-ACS from ten countries between Jan 1, 2005, and June 24, 2024. A machine learning model for 1-year mortality was developed in 400 054 patients from England, Wales, and Northern Ireland. Both the in-hospital mortality model and the new 1-year mortality model were externally validated in patients from Sweden, Switzerland, Germany, Denmark, Spain, the Netherlands, and Czechia. A separate machine learning model to predict the individualised effect of early versus delayed invasive coronary angiography and revascularisation on a composite primary outcome of all-cause death, non-fatal recurrent myocardial infarction, hospital admission for refractory myocardial ischaemia, or hospital admission for heart failure at a median follow-up of 4·3 years was developed and externally validated in participants from geographically different sets of hospitals in the Danish VERDICT trial.
Findings:
The in-hospital mortality model (area under the receiver operating characteristic curve [AUC] 0·90, 95% CI 0·89-0·91) and the 1-year mortality model (time-dependent AUC 0·84, 95% CI 0·82-0·86) showed excellent discriminative abilities on external validation across all countries. Both models were well calibrated and decision curve analyses suggested favourable clinical utility. Compared with score version 2.0, both models provided improved discrimination and risk reclassification. The individualised treatment effect model effectively identified patients who would benefit from early invasive management on external validation. Patients with high predicted benefit had reduced risk of the composite outcome when randomly assigned to early invasive management (hazard ratio 0·60, 95% CI 0·41-0·88), whereas patients with no-to-moderate predicted benefit did not (1·06, 0·80-1·40; pinteraction=0·014). The individualised treatment effect model suggested that the group of patients with NSTE-ACS who benefit from early intervention might be incompletely captured by current treatment strategies.
Interpretation:
The updated GRACE 3.0 scoring system provides a validated, practical tool to support personalised risk assessment in patients with NSTE-ACS. Prediction of an individual's long-term cardiovascular benefit from early invasive management could refine future trial design.
Funding:
Swiss Heart Foundation, University of Zurich Foundation, Kurt and Senta Herrmann Foundation, Theodor and Ida Herzog-Egli Foundation, and Foundation for Cardiovascular Research-Zurich Heart House.
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