Improving risk prediction for death, stroke and bleeding in Asian patients with atrial fibrillation
Issued Date
2023-02-01
Resource Type
ISSN
00142972
eISSN
13652362
Scopus ID
2-s2.0-85139956218
Pubmed ID
36197442
Journal Title
European Journal of Clinical Investigation
Volume
53
Issue
2
Rights Holder(s)
SCOPUS
Bibliographic Citation
European Journal of Clinical Investigation Vol.53 No.2 (2023)
Suggested Citation
Krittayaphong R., Kanjanarutjawiwat W., Wisaratapong T., Lip G.Y.H. Improving risk prediction for death, stroke and bleeding in Asian patients with atrial fibrillation. European Journal of Clinical Investigation Vol.53 No.2 (2023). doi:10.1111/eci.13886 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/82827
Title
Improving risk prediction for death, stroke and bleeding in Asian patients with atrial fibrillation
Other Contributor(s)
Abstract
Background: The objectives of this study were to compare the GARFIELD Refitted model and CHA2DS2-VASc/HAS-BLED risk scores with the new model from the COOL-AF registry for all-cause death, ischaemic stroke/systemic embolism (SSE) and major bleeding in Asian patients with atrial fibrillation (AF). Methods: Patients with non-valvular AF in the nationwide COOL-AF registry were studied. Patients were enrolled from 27 hospitals in Thailand during 2014–2017. Main outcomes were all-cause mortality, SSE and major bleeding. Predictive models of the three outcomes were developed from the variables in the multivariable Cox-proportional Hazard model. Predictive values of the models were evaluated by C-statistics, calibration plots and decision curve analysis (DCA). The new COOL-AF models were compared with the GARFIELD Refitted models and CHA2DS2-VASc model for all-cause mortality, SSE/HAS-BLED model for major bleeding. Results: A total of 3405 patients were enrolled. The C-statistics for the COOL-AF models were 0.727 (0.712–0.742), 0.708 (0.693–0.724) and 0.706 (0.690–0.721) for all-cause mortality, SSE and major bleeding, respectively. Calibration plots showed good agreement between predicted probability the observed outcomes for the COOL-AF models with a calibration slope of 0.94–0.99. The predictive ability remains preserved after the internal validation with bootstraps and optimism (bias) correction. The COOL-AF predictive models tended to be superior to the GARFIELD Refitted, CHA2DS2-VASc and HAS-BLED models. Conclusion: The COOL-AF predictive models for all-cause mortality, SSE and major bleeding in Asian patients with AF had a good predictive ability. The COOL-AF model for all-cause mortality was superior to the GARFIELD Refitted and CHA2DS2-VASc model.