What is the clinical evidence from this study?

Study design: Cohort. Population: Non-valvular atrial fibrillation (n=3405). Intervention: COOL-AF predictive models vs. GARFIELD Refitted and CHA2DS2-VASc/HAS-BLED models. Primary outcome: Predictive ability (C-statistic) for all-cause mortality (C-statistic 0.727, 95% CI 0.712-0.742).

October 5, 2022Open Access

Improving risk prediction for death, stroke and bleeding in Asian patients with atrial fibrillation

Key Result

The COOL-AF predictive model for all-cause mortality yielded a C-statistic of 0.727, proving superior to GARFIELD Refitted and CHA2DS2-VASc models in Asian patients with atrial fibrillation.

Study Design

Type

Cohort (n=3,405)

Multicenter

Yes

Structured PICO

Do the COOL-AF predictive models improve risk prediction for all-cause mortality, SSE, and major bleeding compared to GARFIELD Refitted, CHA2DS2-VASc, and HAS-BLED models in Asian patients with atrial fibrillation?

Population

3,405 Asian adults with non-valvular atrial fibrillation, mean age 67.8 years, 41.8% male, from 27 hospitals in Thailand. Key exclusions: rheumatic heart disease, mechanical heart valve, transient AF, life expectancy <3 years, hematologic disorders increasing bleeding risk, ischemic stroke within 3 months, and pregnancy.

Intervention

COOL-AF predictive models for all-cause mortality, ischemic stroke/systemic embolism (SSE), and major bleeding

Comparator

GARFIELD Refitted models, CHA2DS2-VASc model (for mortality and SSE), and HAS-BLED model (for major bleeding)

Outcome

All-cause mortality, ischemic stroke/systemic embolism (SSE), and major bleedinghard clinical

The COOL-AF predictive models demonstrated good predictive ability for mortality, stroke, and bleeding in Asian patients with atrial fibrillation, outperforming standard scores like CHA2DS2-VASc for all-cause mortality.

Main Result

Effect estimate: C-statistic 0.727 (95% CI 0.712-0.742)

Limitations

Missing data for left ventricular ejection fraction required imputation
Lack of external validation cohort
Inability to test GARFIELD models in OAC-only population for sensitivity analysis

Abstract

Abstract Background The objectives of this study were to compare the GARFIELD Refitted model and CHA 2 DS 2 ‐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 CHA 2 DS 2 ‐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, CHA 2 DS 2 ‐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 CHA 2 DS 2 ‐VASc model.

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