Dataset Information

Impact of body mass index on procedural complications, procedure duration, and radiation dose in patients with atrial fibrillation undergoing radiofrequency ablation: A systematic review and meta-analysis.

ABSTRACT: BACKGROUND:The association of body mass index (BMI) and procedure-related factors in patients with atrial fibrillation (AF) after radiofrequency ablation (RFA) is still unclear. HYPOTHESIS:BMI is associated with increased the radiation dose, procedure duration, and procedural complications. METHODS:Prospective studies assessing BMI and procedure duration, radiation dose, and procedural complications in patients with AF after RFA were identified through electronic searches of PubMed, Embase, and the Cochrane Library database. RESULTS:Ten studies with 14?735 participants undergoing RFA were included. Procedure duration was significantly longer in patients with overweight or obesity than in patients with normal BMI, with a mean difference (MD) of 0.95. Patients with overweight and obesity were exposed to a larger radiation dose, with standard MD of 1.71 and 1.98, respectively. There was no significant association between overweight or obesity and the risk of procedural complications (RR of 0.91 for overweight, 1.01 for obesity, 0.89 for stage I obesity, 1.00 for stage II obesity, and 0.94 for stage III obesity). Further analysis showed there was no significant difference regarding stroke or transient ischemic attack (overweight, RR: 0.92; obesity, RR: 1.02); cardiac tamponade (overweight, RR: 0.92; obesity, RR: 1.02); groin hematoma (overweight, RR: 0.62; obesity, RR: 0.40); or pulmonary vein stenosis (overweight, RR: 0.49; obesity, RR: 0.40) among BMI groups. CONCLUSION:Based on available evidence, we first showed that patients with overweight/obesity undergoing RFA experienced a significantly increased procedure duration and received a larger radiation dose than patients with normal BMI; however, there was no significant difference in procedural complications between patients with overweight/obesity and patients with normal BMI.

SUBMITTER: Liu M

PROVIDER: S-EPMC7534012 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Impact of body mass index on procedural complications, procedure duration, and radiation dose in patients with atrial fibrillation undergoing radiofrequency ablation: A systematic review and meta-analysis.

Liu Menglu M Mei Kaibo K Liu Xiao X Zhao Yujie Y

Clinical cardiology 20200603 10

<h4>Background</h4>The association of body mass index (BMI) and procedure-related factors in patients with atrial fibrillation (AF) after radiofrequency ablation (RFA) is still unclear.<h4>Hypothesis</h4>BMI is associated with increased the radiation dose, procedure duration, and procedural complications.<h4>Methods</h4>Prospective studies assessing BMI and procedure duration, radiation dose, and procedural complications in patients with AF after RFA were identified through electronic searches o ...[more]

PMID: 32492246

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Project description:BackgroundRadiofrequency ablation (RFA) for atrial fibrillation (AF) is associated with a risk of complications. This study aimed to develop and validate risk models for predicting complications after radiofrequency ablation of atrial fibrillation patients.MethodsThis retrospective cohort study included 3365 procedures on 3187 patients with atrial fibrillation at a single medical center from 2018 to 2021. The outcome was the occurrence of postoperative procedural complications during hospitalization. Logistic regression, decision tree, random forest, gradient boosting machine, and extreme gradient boosting were used to develop risk models for any postoperative complications, cardiac effusion/tamponade, and hemorrhage, respectively. Patients' demographic characteristics, medical history, signs, symptoms at presentation, electrocardiographic features, procedural characteristics, laboratory values, and postoperative complications were collected from the medical record. The prediction results were evaluated by performance metrics (i.e., the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, F score, and Brier score) with repeated fivefold cross-validation.ResultsOf the 3365 RFA procedures, there were 62 procedural complications with a rate of 1.84% in the entire cohort. The most common complications were cardiac effusion/tamponade (28 cases, 0.83%), and hemorrhage (21 cases, 0.80%). There was no procedure-related mortality. The machine learning algorithms of random forest (RF) outperformed other models for any complication (AUC 0.721 vs 0.627 to 0.707), and hemorrhage (AUC 0.839 vs 0.649 to 0.794). The extreme gradient boosting (XGBoost) model outperformed other models for cardiac effusion/tamponade (AUC 0.696 vs 0.606 to 0.662).ConclusionsThe developed risk models using machine learning algorithms showed good performance in predicting complications after RFA of AF patients. These models help identify patients at high risk of complications and guiding clinical decision-making.

Project description:Background: Little is known about the prognostic value of nutritional status among patients undergoing atrial fibrillation (AF) catheter ablation (AFCA). We compared the risk of procedure-related complications and long-term rhythm outcomes of AFCA according to nutritional status. Methods: We included 3,239 patients undergoing de novo AFCA in 2009-2020. Nutritional status was assessed using the controlling nutritional status (CONUT) score. The association between malnutrition and the risk of AFCA complications or long-term rhythm outcomes was evaluated. We validated the effects of malnutrition using an external cohort of 360 patients undergoing AFCA in 2013-2016. Results: In the study population (26.8% women, median age: 58 years), 1,005 (31.0%) had malnutrition (CONUT scores ≥ 2); 991 (30.6%) had mild (CONUT 2-4) and 14 (0.4%) had moderate-to-severe (CONUT ≥ 5) malnutrition. The overall complication rates after AFCA were 3.3% for normal nutrition, 4.2% for mild malnutrition, and 21.4% for moderate-to-severe malnutrition. Moderate-to-severe malnutrition [odds ratio (OR) 6.456, 95% confidence interval (CI) 1.637-25.463, compared with normal nutrition], older age (OR 1.020 per 1-year increase, 95% CI 1.001-1.039), female sex (OR 1.915, 95% CI 1.302-2.817), and higher systolic blood pressure (OR 1.013 per 1-mmHg increase, 95% CI 1.000-1.026) were independent predictors for the occurrence of complications. In the validation cohort, malnutrition (CONUT ≥ 2) was associated with a 2.87-fold higher risk of AFCA complications (95% CI 1.174-7.033). The association between malnutrition and a higher risk of AFCA complications was consistently observed regardless of body mass index and sex. Malnutrition did not affect rhythm outcomes during the median follow-up of 40 months (clinical recurrence: 37.0% in normal nutrition vs. 36.5% in malnutrition). Conclusion: Malnutrition, which is common in patients undergoing AFCA, was associated with a substantially higher risk for complications after AFCA.

Project description:Radiofrequency ablation (RFA) using the CARTO 3D mapping system is a common approach for pulmonary vein isolation to treat atrial fibrillation (AF). Linkage between CARTO procedural data and patients' electronical health records (EHR) provides an opportunity to identify the ablation-related parameters that would predict AF recurrence. The objective of this study is to assess the incremental accuracy of RFA procedural data to predict post-ablation AF recurrence using machine learning model. Procedural data generated during RFA procedure were downloaded from CARTONET and linked to deidentified Mercy Health EHR data. Data were divided into train (70%) and test (30%) data for model development and validation. Automate machine learning (AutoML) was used to predict 1 year AF recurrence, defined as a composite of repeat ablation, electrical cardioversion, and AF hospitalization. At first, AutoML model only included Patients' demographic and clinical characteristics. Second, an AutoML model with procedural variables and demographical/clinical variables was developed. Area under receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI) were used to compare model performances using test data. Among 306 patients, 67 (21.9%) patients experienced 1-year AF recurrence. AUROC increased from 0.66 to 0.78 after adding procedural data in the AutoML model based on test data. For patients with AF recurrence, NRI was 32% for model with procedural data. Nine of 10 important predictive features were CARTO procedural data. From CARTO procedural data, patients with lower contact force in right inferior site, long ablation duration, and low number of left inferior and right roof lesions had a higher risk of AF recurrence. Patients with persistent AF were more likely to have AF recurrence. The machine learning model with procedural data better predicted 1-year AF recurrence than the model without procedural data. The model could be used for identification of patients with high risk of AF recurrence post ablation.

Dataset Information

Impact of body mass index on procedural complications, procedure duration, and radiation dose in patients with atrial fibrillation undergoing radiofrequency ablation: A systematic review and meta-analysis.

Publications

Impact of body mass index on procedural complications, procedure duration, and radiation dose in patients with atrial fibrillation undergoing radiofrequency ablation: A systematic review and meta-analysis.

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