Key result
Modified APPLE score improves prediction of post-ablation AF recurrence to an AUC of ~0.89.
Why the study?
It is necessary to predict atrial fibrillation recurrence through models in clinical practice for patients with hypertension undergoing radiofrequency ablation.
Does the Modified APPLE score improve the prediction of atrial fibrillation recurrence in patients with hypertension undergoing radiofrequency ablation compared to the traditional APPLE score?
Cohort (n=380)
No
Does the Modified APPLE score improve the prediction of atrial fibrillation recurrence in patients with hypertension undergoing radiofrequency ablation compared to the traditional APPLE score?
Absolute Event Rate: 0.889% vs 0.856%
p-value: p=0.006
Integrating inflammatory and cardiac structural indicators into the APPLE score significantly improves the prediction of AF recurrence post-ablation in hypertensive patients.
May enhance AF recurrence stratification post-ablation in hypertension; extends APPLE score but leaves open clinical adoption pending validation.
Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, with hypertension representing a significant risk factor. It is necessary to predict the recurrence of AF through models in clinical practice for patients with hypertension and AF. Methods: A retrospective analysis was conducted on 380 patients who underwent their first ablation procedure. Results: The traditional APPLE score was enhanced by incorporating additional indicators: the Systemic Immune-Inflammation Index (SII), left ventricular mass index (LVMI), body mass index (BMI), age, and estimated glomerular filtration rate (eGFR). The Modified APPLE Score model, achieved superior predictive performance with an AUC of 0.889, significantly outperforming the traditional APPLE score (AUC = 0.856), P = 0.006. Analysis revealed U-shaped relationships between recurrence risk and both SII and age. LVMI, BMI, and systolic blood pressure were positively correlated with recurrence risk, while eGFR was negatively correlated. Both SII and age showed U-shaped relationships with AF recurrence risk (SII critical values: 400 × 10 5 /L and 750 × 10 9 /L; age critical values: 50 and 70 years), while LVMI, BMI, and systolic blood pressure were positively correlated with recurrence risk, eGFR was negatively correlated. Among inflammatory markers, SII demonstrated the highest predictive value. Conclusions: The Modified APPLE score model, which integrates inflammatory and cardiac structural indicators, significantly enhances the prediction accuracy of AF recurrence. Its core mechanism lies in simultaneously capturing the synergistic effects of systemic inflammatory activation and ventricular remodeling. This model provides a practical tool for identifying high-risk patients and developing individualized intervention strategies, offering potential for advancing precision secondary prevention in patients with hypertension and AF.
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Wang et al. (2026) conducted a cohort in Atrial fibrillation and hypertension (n=380). Modified APPLE score vs. Traditional APPLE score was evaluated on Predictive performance for AF recurrence (AUC) (p=0.006). The Modified APPLE Score model achieved an AUC of 0.889 for predicting atrial fibrillation recurrence, significantly outperforming the traditional APPLE score.
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