The Validation of a Nomogram for Predicting Recurrence in Patients with Non-Valvular Atrial Fibrillation...

Area of Science:

• Cardiology
• Medical Diagnostics

Background:

• Non-valvular atrial fibrillation (NVAF) poses a significant risk for stroke and other complications.
• Radiofrequency catheter ablation (RFCA) is a common treatment for NVAF, but recurrence remains a challenge.
• Accurate prediction of recurrence is crucial for patient management and treatment optimization.

Purpose of the Study:

• To develop and validate a nomogram for predicting the risk of AF recurrence post-RFCA in NVAF patients.
• To compare the performance of the developed nomogram against established scores (APPLE, ATLAS, Antwerp).

Main Methods:

• A cohort of 242 NVAF patients undergoing RFCA was randomly divided into training (n=169) and validation (n=73) groups.
• A nomogram was constructed using variables including LAVI, RAVI, SII, NYHA classification, and CHA 2DS 2-VASc score.
• Performance was assessed using Area Under the Curve (AUC), integrated discrimination improvement, and net reclassification index, compared via DeLong test in R software.

Main Results:

• The nomogram demonstrated superior predictive performance with AUCs of 0.837 (training) and 0.895 (validation), significantly outperforming APPLE, ATLAS, and Antwerp scores (P < 0.05).
• The nomogram exhibited enhanced discriminatory power, better positive and negative predictive values, and reduced misjudgment rates.
• It offered a more balanced sensitivity-specificity profile and greater predictive stability compared to single-dimensional scores.

Conclusions:

• The developed nomogram is a superior tool for predicting AF recurrence after RFCA in NVAF patients compared to existing scores.
• The nomogram provides more robust clinical decision support and improved risk stratification.
• Further validation in larger, multi-center, prospective studies is warranted to confirm generalizability.