Heart rhythm · 2026
Identification of clinical risk factors for arrhythmia recurrence in patients with atrial fibrillation undergoing catheter ablation: A systematic review and meta-analysis.
СтатьяСистематический обзорМетаанализНазвание и аннотация: Перевод пока не подготовлен
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Chan Kimmy W P, Yu Doris S F, Ho Joshua W K, Wong Cathy W Y, Li Polly W C
Аннотация
BACKGROUND: Arrhythmia recurrence after atrial fibrillation (AF) catheter ablation remains a substantial clinical challenge, but risk factors of arrhythmia recurrence are not well defined.
OBJECTIVE: This study aimed to elucidate baseline clinical risk factors for postablation recurrence and variations by AF phenotype and study heterogeneity.
METHODS: We systematically searched 8 databases for prospective cohort studies assessing associations between clinical risk factors and postablation arrhythmia recurrence up to 31 December 2025. Study quality was evaluated using the Newcastle-Ottawa scale. Multivariable-adjusted hazard ratios (aHRs) were pooled through random-effects meta-analyses with subgroup, meta-regression, and sensitivity analyses.
RESULTS: Among 152 studies involving 49,919 patients, 16 clinical risk factors were identified. In primary meta-analysis pooling aHRs, the strongest associations were observed for smoking (aHR 2.15 [1.49-3.10)]), periodontitis (aHR 2.04 [1.48-2.83]), metabolic syndrome (aHR 1.71 [1.12-2.62]), sleep apnea (aHR 1.65 [1.31-2.09]), and persistent AF (aHR 1.64 [1.53-1.76]), followed by chronic kidney disease, alcohol consumption, overweight/obesity, diabetes mellitus, female sex, hypertension, AF history, left atrial enlargement, and impaired left ventricular ejection fraction. Untreated sleep apnea (aHR 2.41 [1.51-3.86]) and uncontrolled hypertension (aHR 1.67 [1.12-2.40]) conferred heightened risks. Sensitivity analyses pooling adjusted odds ratios (aORs) additionally identified depression (aOR 2.86 [1.51-5.41]) and anxiety (aOR 2.54 [1.59-4.04]). Subgroup analyses revealed no difference across AF phenotypes. Meta-regression identified ablation modality as a significant moderator for AF history and geographic region for female sex, heart failure, and diabetes.
CONCLUSION: Expanded preablation risk profiles with consistent effect across AF phenotypes substantiate personalized risk stratification for ablation candidacy and preprocedural optimization.
OBJECTIVE: This study aimed to elucidate baseline clinical risk factors for postablation recurrence and variations by AF phenotype and study heterogeneity.
METHODS: We systematically searched 8 databases for prospective cohort studies assessing associations between clinical risk factors and postablation arrhythmia recurrence up to 31 December 2025. Study quality was evaluated using the Newcastle-Ottawa scale. Multivariable-adjusted hazard ratios (aHRs) were pooled through random-effects meta-analyses with subgroup, meta-regression, and sensitivity analyses.
RESULTS: Among 152 studies involving 49,919 patients, 16 clinical risk factors were identified. In primary meta-analysis pooling aHRs, the strongest associations were observed for smoking (aHR 2.15 [1.49-3.10)]), periodontitis (aHR 2.04 [1.48-2.83]), metabolic syndrome (aHR 1.71 [1.12-2.62]), sleep apnea (aHR 1.65 [1.31-2.09]), and persistent AF (aHR 1.64 [1.53-1.76]), followed by chronic kidney disease, alcohol consumption, overweight/obesity, diabetes mellitus, female sex, hypertension, AF history, left atrial enlargement, and impaired left ventricular ejection fraction. Untreated sleep apnea (aHR 2.41 [1.51-3.86]) and uncontrolled hypertension (aHR 1.67 [1.12-2.40]) conferred heightened risks. Sensitivity analyses pooling adjusted odds ratios (aORs) additionally identified depression (aOR 2.86 [1.51-5.41]) and anxiety (aOR 2.54 [1.59-4.04]). Subgroup analyses revealed no difference across AF phenotypes. Meta-regression identified ablation modality as a significant moderator for AF history and geographic region for female sex, heart failure, and diabetes.
CONCLUSION: Expanded preablation risk profiles with consistent effect across AF phenotypes substantiate personalized risk stratification for ablation candidacy and preprocedural optimization.