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Abstract 12659: Associations Between Patient Demographic Characteristics and Odds of Repeat Ablation for Atrial Fibrillation

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Introduction: Atrial fibrillation (AF) affects over 3 million adults in the United States and has an estimated direct healthcare cost of $6 billion. Between 2000 and 2013, there was an eightfold increase in the number of ablations for AF performed. However, success rates vary from 35%-80%. Because AF recurrence is common, patients may require repeat ablations, but less is known about which patients are at high risk for repeat ablations. The objective of this study was to investigate the prevalence of repeat ablations by patient demographic characteristics. Methods: From electronic health records, we identified all patients with an admitting diagnosis of paroxysmal AF using International Classification of Diseases billing codes who were treated at NewYork-Presbyterian Hospital from 2010 through 2019. We then identified patients who underwent ablation at the institution using Current Procedural Terminology codes and extracted ablation dates, age at first ablation, gender, race, and ethnicity. We summarized patient characteristics using standard descriptive statistics and evaluated associations between demographics and repeat ablations using logistic regression modeling. Results: Of the 1,799 patients studied, 31.0% were female, 54.0% were white, 4.0% were Hispanic or Latino, and 17.9% had at least one repeat ablation. At the first ablation, 19.7% of patients were under age 55, 26.4% aged 55 to 64, 33.4% aged 65 to 74, 16.3% aged 75-84, and 4.2% aged 85 and older. Subjects aged <55 were significantly more likely to undergo repeat ablation compared to ( > 85 (OR 2.03 [95% CI 1.01-4.54]). The odds of repeat ablation did not significantly differ by gender, race, or ethnicity. Conclusion: Younger age is associated with increased odds of repeat ablations. Age and other potential predictors of repeat ablations should be further studied in larger, more diverse samples controlling for relevant covariates.
Title: Abstract 12659: Associations Between Patient Demographic Characteristics and Odds of Repeat Ablation for Atrial Fibrillation
Description:
Introduction: Atrial fibrillation (AF) affects over 3 million adults in the United States and has an estimated direct healthcare cost of $6 billion.
Between 2000 and 2013, there was an eightfold increase in the number of ablations for AF performed.
However, success rates vary from 35%-80%.
Because AF recurrence is common, patients may require repeat ablations, but less is known about which patients are at high risk for repeat ablations.
The objective of this study was to investigate the prevalence of repeat ablations by patient demographic characteristics.
Methods: From electronic health records, we identified all patients with an admitting diagnosis of paroxysmal AF using International Classification of Diseases billing codes who were treated at NewYork-Presbyterian Hospital from 2010 through 2019.
We then identified patients who underwent ablation at the institution using Current Procedural Terminology codes and extracted ablation dates, age at first ablation, gender, race, and ethnicity.
We summarized patient characteristics using standard descriptive statistics and evaluated associations between demographics and repeat ablations using logistic regression modeling.
Results: Of the 1,799 patients studied, 31.
0% were female, 54.
0% were white, 4.
0% were Hispanic or Latino, and 17.
9% had at least one repeat ablation.
At the first ablation, 19.
7% of patients were under age 55, 26.
4% aged 55 to 64, 33.
4% aged 65 to 74, 16.
3% aged 75-84, and 4.
2% aged 85 and older.
Subjects aged <55 were significantly more likely to undergo repeat ablation compared to ( > 85 (OR 2.
03 [95% CI 1.
01-4.
54]).
The odds of repeat ablation did not significantly differ by gender, race, or ethnicity.
Conclusion: Younger age is associated with increased odds of repeat ablations.
Age and other potential predictors of repeat ablations should be further studied in larger, more diverse samples controlling for relevant covariates.

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