Validating the predictive ability of the 2MACE score for major adverse cardiovascular events in patients with atrial fibrillation: results from phase II/III of the GLORIA-AF registry.

Publication/Presentation Date

1-1-2024

Abstract

The 2MACE score was specifically developed as a risk-stratification tool in atrial fibrillation (AF) to predict cardiovascular outcomes. We evaluated the predictive ability of the 2MACE score in the GLORIA-AF registry. All eligible patients from phase II/III of the prospective global GLORIA-AF registry were included. Major adverse cardiac events (MACEs) were defined as the composite outcome of stroke, myocardial infarction and cardiovascular death. Cox proportional hazards were used to examine the relationship between the 2MACE score and study outcomes. Predictive capability of the 2MACE score was investigated using receiver-operating characteristic curves. A total of 25,696 patients were included (mean age 71 years, female 44.9%). Over 3 years, 1583 MACEs were recorded. Patients who had MACE were older, with more cardiovascular risk factors and were less likely to be managed using a rhythm-control strategy. The median 2MACE score in the MACE and non-MACE groups were 2 (IQR 1-3) and 1 (IQR 0-2), respectively (p < 0.001). The 2MACE score was positively associated with an increase in the risk of MACE, with a score of ≥ 2 providing the best combination of sensitivity (69.6%) and specificity (51.6%), HR 2.47 (95% CI, 2.21-2.77). The 2MACE score had modest predictive performance for MACE in patients with AF (AUC 0.655 (95% CI, 0.641-0.669)). Our analysis in this prospective global registry demonstrates that the 2MACE score can adequately predict the risk of MACE (defined as myocardial infarction, CV death and stroke) in patients with AF. Clinical trial registration: http://www.clinicaltrials.gov . Unique identifiers: NCT01468701, NCT01671007 and NCT01937377.

Volume

57

Issue

1

First Page

39

Last Page

49

ISSN

1573-742X

Disciplines

Medicine and Health Sciences

PubMedID

37566295

Department(s)

Department of Medicine

Document Type

Article

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