May 5, 2025European Journal of Internal Medicine9 citationsOpen Access
Chronic kidney disease classification according to different formulas and impact on adverse outcomes in patients with atrial fibrillation: A report from a prospective observational European registry
Key Result
The CG and CG-BSA formulas showed the best discriminative ability for predicting adverse outcomes in AF patients (AUC 0.661 [95% CI 0.644-0.678] and 0.660 [95% CI 0.644-0.677], respectively).
Study Design
Type
Observational (n=8,506)
Multicenter
Yes
Structured PICO
Which renal function estimation formula best predicts adverse outcomes in patients with atrial fibrillation?
P
Population
8,506 patients with atrial fibrillation enrolled in a prospective observational European registry
I
Intervention
Renal function estimation using eight formulas: BIS-1, CG, CG-BSA, CKD-EPI, EKFC, FAS, LMR and MDRD
C
Comparator
Comparison among the different renal function estimation formulas
O
Outcome
Composite of all-cause death, any coronary revascularization and any thromboembolismcomposite
The Cockcroft-Gault (CG) and CG-BSA formulas demonstrated superior discriminative ability for predicting adverse outcomes in patients with atrial fibrillation compared to other renal function estimation equations.
Main Result
Effect estimate: AUC 0.661 (CG) and 0.660 (CG-BSA) (95% CI 0.644-0.678 (CG) and 0.644-0.677 (CG-BSA))
Abstract
BACKGROUND: Chronic kidney disease (CKD) and atrial fibrillation (AF) often coexist, making accurate renal function estimation crucial, typically through equations calculating estimated glomerular filtration rate (eGFR) or creatinine clearance (CrCl). OBJECTIVE: To compare the concordance and predictive performance of different renal function estimation equations in a European cohort of AF patients. METHODS: We analyzed data from AF patients enrolled in a prospective observational European registry. Renal function was estimated using eight formulas: BIS-1, CG, CG-BSA, CKD-EPI, EKFC, FAS, LMR and MDRD. Concordance between formulas was assessed using weighted Cohen's Kappa, while Cox regression and receiver operating characteristic (ROC) curves evaluated their association with outcomes (composite of all-cause death, any coronary revascularization and any thromboembolism). RESULTS: We included 8,506 patients. CKD-EPI demonstrated good to excellent concordance with other formulas, with the lowest concordance with CG (K = 0.607; 95% CI, 0.595-0.618) and the highest with MDRD (K = 0.880; 95% CI, 0.873-0.887). The risk of adverse outcomes increased sharply when renal function dropped below 60 ml/min across all formulas. CG-BSA and CG formulas showed the best discriminative ability for predicting composite outcomes (AUC 0.660, 95% CI 0.644-0.677, and 0.661, 95% CI 0.644-0.678, respectively). Based on integrated discrimination improvement (IDI) analysis, compared to the CKD-EPI equation, the CG and CG-BSA formulas showed significant improvements in sensitivity of 0.9% and 1.1%, respectively CONCLUSION: Equations for estimating renal function vary in concordance, with potential implications for drug prescription and predicting adverse events. CG and CG-BSA formulas showed superior performance in identifying patients at risk for adverse outcomes.
Cite This Study
Boriani et al. (Mon,) conducted a observational in Atrial fibrillation (n=8,506). Renal function estimation equations (BIS-1, CG, CG-BSA, CKD-EPI, EKFC, FAS, LMR, MDRD) vs. Comparison among formulas was evaluated on Composite of all-cause death, any coronary revascularization and any thromboembolism (AUC 0.661 (CG) and 0.660 (CG-BSA), 95% CI 0.644-0.678 (CG) and 0.644-0.677 (CG-BSA)). The CG and CG-BSA formulas showed the best discriminative ability for predicting adverse outcomes in AF patients (AUC 0.661 [95% CI 0.644-0.678] and 0.660 [95% CI 0.644-0.677], respectively).