Predicting atrial fibrillation recurrence after ablation in patients with heart failure: Validity of the APPLE and CAAP-AF risk scoring systems.

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Black-Maier, Eric
Parish, Alice
Steinberg, Benjamin A
Green, Cynthia L
Loring, Zak
Barnett, Adam S
Al-Khatib, Sana M
Atwater, Brett D
Daubert, James P
Frazier-Mills, Camille

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Compared with medical therapy, catheter ablation of atrial fibrillation (AF) in patients with heart failure (HF) improves cardiovascular outcomes. Risk scores (CAAP-AF and APPLE) have been developed to predict the likelihood of AF recurrence after ablation, have not been validated specifically in patients with AF and HF.


We analyzed baseline characteristics, risk scores, and rates of AF recurrence 12 months postablation in a cohort of 230 consecutive patients with AF and HF undergoing PVI in the Duke Center for Atrial Fibrillation registry from 2009-2013.


During a follow-up period of 12 months, 76 of 230 (33%) patients with HF experienced recurrent AF after ablation. The median APPLE and CAAP-AF scores were 1.5 ([Q1, Q3]: [1.0, 2.0]) and 4.0 ([Q1, Q3]: [3.0, 5.0]), respectively and were not different from those patients with and without recurrent AF. Freedom from AF was not different according to APPLE and CAAP-AF scores. Discrimination for recurrent AF with the CAAP-AF score was modest with a C-statistic of 0.60 (95% CI 0.52-0.67). Discrimination with the APPLE score was similarly modest, with a C-statistic of 0.54 (95% CI: 0.47-0.62).


Validated predictive risk scores for recurrent AF after catheter ablation exhibit limited predictive ability in cohorts of AF and HF. Additional tools are needed to facilitate risk stratification and patient selection for AF ablation in patients with concomitant HF.





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Black-Maier, Eric, Alice Parish, Benjamin A Steinberg, Cynthia L Green, Zak Loring, Adam S Barnett, Sana M Al-Khatib, Brett D Atwater, et al. (2019). Predicting atrial fibrillation recurrence after ablation in patients with heart failure: Validity of the APPLE and CAAP-AF risk scoring systems. Pacing and clinical electrophysiology : PACE, 42(11). pp. 1440–1447. 10.1111/pace.13805 Retrieved from

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Alice Parish

Biostatistician III

Education: Master of Science in Public Health, Biostatistics-  Emory University Rollins School of Public Health.  

Overview: Alice collaborates with researchers and clinicians with the Division of Gastroenterology on many observational studies using data from EHR as well as large national databases such as HCUP, UNOS, and Medicare 5% LDS.  Additionally, Alice collaborates with the Division of Pulmonary on palliative care RCTs and various retrospective studies.  Alice works with the Pharmacy residents on their PGY1 studies.  In the past Alice has had the opportunity to work with investigators in Heart Center and Epicenter.  Alice has experience working with zero inflated count outcomes, among many other statistical methodologies.


Cynthia Lea Green

Associate Professor of Biostatistics & Bioinformatics

Survival Analysis
Longitudinal Data Analysis
Logistic Regression
Missing Data
Clinical Trial Methods
Maximum Likelihood Methods

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