Outcomes of patients with atrial fibrillation with and without diabetes: A propensity score matching of the COOL-AF registry

Dysglycemia and arrhythmias

Disorders in glucose metabolism can be divided into three separate but interrelated domains, namely hyperglycemia, hypoglycemia, and glycemic variability. Intensive glycemic control in patients with diabetes might increase the risk of hypoglycemic incidents and glucose fluctuations. These three dysglycemic states occur not only amongst patients with diabetes, but are frequently present in other clinical settings, such as during critically ill. A growing body of evidence has focused on the relationships between these dysglycemic domains with cardiac arrhythmias, including supraventricular arrhythmias (primarily atrial fibrillation), ventricular arrhythmias (malignant ventricular arrhythmias and QT interval prolongation), and bradyarrhythmias (bradycardia and heart block). Different mechanisms by which these dysglycemic states might provoke cardiac arr-hythmias have been identified in experimental studies. A customized glycemic control strategy to minimize the risk of hyperglycemia, hypoglycemia and glucose variability is of the utmost importance in order to mitigate the risk of cardiac arrhythmias.

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

BACKGROUND

The objectives of this study were to compare the GARFIELD Refitted model and CHA₂ DS₂ -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 CHA₂ DS₂ -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, CHA₂ DS₂ -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 CHA₂ DS₂ -VASc model.