Publication details

Extension of the GRACE score for non-ST-elevation acute coronary syndrome: a development and validation study in ten countries

Authors	WENZL Florian A KOFOED Klaus F SIMONSSON Moa AMBLER Gareth SANGEN Niels M R van der LAMPA Erik BRUNO Francesco BELDER Mark A de HLÁSENSKÝ Jiří MUELLER-HENNESSEN Matthias SMOLLE Maria A WANG Peizhi HENRIQUES José P S KIKKERT Wouter J KELBAK Henning BOUČEK Luboš RAPOSEIRAS-ROUBÍN Sergio ABU-ASSI Emad AZZAHHAFI Jaouad VELDERS Matthijs A STELLOS Konstantinos ENGSTROM Thomas YIN Dean R P P Chan Pin WESTON Clive ADLAM David RICKLI Hans GIANNITSIS Evangelos RADOVANOVIC Dragana PAŘENICA Jiří ANTONIADES Charalambos A FOX Keith A A D'ASCENZO Fabrizio BERG Jurriën M Ten KOBER Lars V JAMES Stefan DEANFIELD John LÜSCHER Thomas F
Year of publication	2025
Type	Article in Periodical
Magazine / Source	Lancet Digital Health
MU Faculty or unit	Faculty of Medicine
Citation
web	https://www.thelancet.com/journals/landig/article/PIIS2589-7500(25)00089-5/fulltext
Doi	https://doi.org/10.1016/j.landig.2025.100907
Description	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.