Dataset Information

Impact of pericoronary adipose tissue attenuation on recurrence after radiofrequency catheter ablation for atrial fibrillation.

ABSTRACT:

Background

Inflammation plays a vital role in the occurrence and progression of atrial fibrillation (AF). The association between pericoronary adipose tissue attenuation (PCATA) and AF recurrence following ablation has not been fully clarified.

Hypothesis

We aimed to evaluate the association between PCATA and AF recurrence after radiofrequency catheter ablation (RFCA).

Methods

Patients who underwent the first RFCA for AF and performed coronary computed tomography angiography before ablation between 2018 and 2021 were enrolled. The predictive values of PCATA for AF recurrence after ablation were investigated. The area under curve (AUC), relative integrated discrimination improvement (IDI), and categorical free net reclassification improvement (NRI) were used to assess the discrimination ability of different models for AF recurrence.

Results

During 1-year follow-up, 34.1% patients experienced AF recurrence. The multivariable analysis model revealed that PCATA of the right coronary artery (RCA) was an independent risk factor for AF recurrence. Patients with a high level of RCA-PCATA had a high risk of recurrence, after adjusting for other risk factors by restricted cubic splines. The performance in predicting AF recurrence was significantly improved by adding the marker of RCA-PCATA to the clinical model (AUC: 0.724 vs. 0.686, p = .024), with a relative IDI of 0.043 (p = .006) and continuous NRI of 0.521 (p < .001).

Conclusions

PCATA of RCA was independently associated with AF recurrence after ablation. PCATA may be helpful for risk classification for AF ablation patients.

SUBMITTER: Wang Z

PROVIDER: S-EPMC10577529 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Publications

Impact of pericoronary adipose tissue attenuation on recurrence after radiofrequency catheter ablation for atrial fibrillation.

Wang Zhe Z Wang Yi-Jia YJ Chen Jia-Wei JW Ren Li-Chen LC Guo He-He HH Chen Xiao-Jie XJ Dong Jian-Zeng JZ Chen Ying-Wei YW Sun Yi-Hong YH

Clinical cardiology 20230712 10

<h4>Background</h4>Inflammation plays a vital role in the occurrence and progression of atrial fibrillation (AF). The association between pericoronary adipose tissue attenuation (PCATA) and AF recurrence following ablation has not been fully clarified.<h4>Hypothesis</h4>We aimed to evaluate the association between PCATA and AF recurrence after radiofrequency catheter ablation (RFCA).<h4>Methods</h4>Patients who underwent the first RFCA for AF and performed coronary computed tomography angiograph ...[more]

PMID: 37436796

Similar Datasets

Project description:BackgroundRadiofrequency catheter ablation (RFCA) represents an important treatment option for atrial fibrillation (AF); however, the recurrence rate following surgery is relatively high. This study aimed to predict the recurrence of AF after RFCA using interpretable machine learning models that combined the triglyceride-glucose (TyG) index and the quantification of left atrial epicardial and pericoronary adipose tissue.MethodsThis retrospective study included 325 patients with AF who underwent their first successful RFCA, among whom 79 had confirmed recurrence. The preoperative clinical data of patients were collected, the TyG index was calculated, and computed tomography (CT) image features were quantitatively measured. Multivariate Cox regression analysis was used to identify the independent risk factors for RFCA recurrence, and adjustments being made for various confounding factors. Post-hoc subgroup analysis was conducted to evaluate the predictive value of the TyG index for recurrence in different patient subgroups. Prediction models based on six machine learning algorithms were constructed. The optimal model's features were evaluated using Shapley additive explanations (SHAP).ResultsAfter adjustment were made for various confounding factors such as comorbidities of AF, Cox regression showed that the volume of left atrial epicardial adipose tissue (LA-EAT), LA-EAT attenuation, left circumflex coronary artery fat attenuation index (LCX-FAI), and the TyG index were independent risk factors for recurrence after RFCA (P<0.001). The support vector machine (SVM) model based on these combined indicators had the best predictive performance, with an area under the curve of 0.793 [95% confidence interval (CI): 0.782-0.805] in the validation set, while its accuracy and positive predictive value were 0.804 and 0.710, respectively. The predictive efficiency of the TyG index appeared to be independent of type 2 diabetes mellitus (T2DM) status (Pinteraction=0.660).ConclusionsThe SVM model that integrated the TyG index and quantitative CT imaging variables demonstrated good predictive ability for post-RFCA recurrence in patients with AF. Furthermore, the TyG index appeared capable of predicting recurrence independently of T2DM status.

Dataset Information

Impact of pericoronary adipose tissue attenuation on recurrence after radiofrequency catheter ablation for atrial fibrillation.

Background

Hypothesis

Methods

Results

Conclusions

Publications

Impact of pericoronary adipose tissue attenuation on recurrence after radiofrequency catheter ablation for atrial fibrillation.

Similar Datasets

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