Key result
The new COM-AF risk score was an independent predictor of atrial fibrillation after cardiac surgery (OR 1.91 per point increase) and demonstrated greater predictive ability (AUC 0.78) than existing scores.
Why the study?
Atrial fibrillation frequently complicates cardiac surgery and increases morbidity and mortality; this study aimed to develop and validate a combined risk score using the highest predictive value variables from POAF, CHA2DS2-VASc, and HATCH.
Does the COM-AF risk score improve the prediction of new-onset atrial fibrillation after cardiac surgery compared to POAF, CHA2DS2-VASc, and HATCH scores in patients undergoing cardiac surgery?
Cohort (n=3,113)
No
Does the COM-AF risk score improve the prediction of new-onset atrial fibrillation after cardiac surgery compared to POAF, CHA2DS2-VASc, and HATCH scores in patients undergoing cardiac surgery?
Odds Ratio: 1.91 (95% CI 1.63–2.23)
p-value: p=<0.001
The newly developed COM-AF score demonstrates superior predictive ability for postoperative atrial fibrillation following cardiac surgery compared to existing risk scores.
May enhance postoperative AF risk stratification; hypothesis-generating and requires prospective validation before clinical adoption.
Background and Aims: Atrial fibrillation frequently occurs in the postoperative period of cardiac surgery, associated with an increase in morbidity and mortality. The scores POAF, CHA2DS2-VASc and HATCH demonstrated a validated ability to predict atrial fibrillation after cardiac surgery (AFCS). The objective is to develop and validate a risk score to predict AFCS from the combination of the variables with highest predictive value of POAF, CHA2DS2-VASc and HATCH models. Methods: We conducted a single-center cohort study, performing a retrospective analysis of prospectively collected data. The study included consecutive patients undergoing cardiac surgery in 2010-2016. The primary outcome was the development of new-onset AFCS. The variables of the POAF, CHA2DS2-VASc and HATCH scores were evaluated in a multivariate regression model to determine the predictive impact. Those variables that were independently associated with AFCS were included in the final model. Results: A total of 3113 patients underwent cardiac surgery, of which 21% presented AFCS. The variables included in the new score COM-AF were: age (≥75: 2 points, 65-74: 1 point), heart failure (2 points), female sex (1 point), hypertension (1 point), diabetes (1 point), previous stroke (2 points). For the prediction of AFCS, COM-AF presented an AUC of 0.78 (95% CI 0.76-0.80), the rest of the scores presented lower discrimination ability (P < 0.001): CHA2DS2-VASc AUC 0.76 (95% CI 0.74-0.78), POAF 0.71 (95% CI 0.69-0.73) and HATCH 0.70 (95% CI: 0, 67-0.72). Multivariable analysis demonstrated that COM-AF score was an independent predictor of AFCS: OR 1,91 (IC 95% 1,63-2,23). Conclusion: From the combination of variables with higher predictive value included in the POAF, CHA2DS2-VASc, and HATCH scores, a new risk model system called COM-AF was created to predict AFCS, presenting a greater predictive ability than the original ones. Being necessary future prospective validations.
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Burgos et al. (2021) conducted a cohort in Patients undergoing cardiac surgery (n=3,113). COM-AF score vs. CHA2DS2-VASc, POAF, and HATCH scores was evaluated on Development of new-onset atrial fibrillation after cardiac surgery (AFCS) (OR 1.91, 95% CI 1.63-2.23, p=<0.001). The new COM-AF risk score was an independent predictor of atrial fibrillation after cardiac surgery (OR 1.91 per point increase) and demonstrated greater predictive ability (AUC 0.78) than existing scores.
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