Risk factors for late recurrence in patients with nonvalvular atrial fibrillation after radiofrequency catheter ablation

Factors influencing early recurrence of atrial fibrillation among elderly patients following radiofrequency catheter ablation and the impact of different antiarrhythmic regimens

Background

Patients with atrial fibrillation (AF) who undergo radiofrequency catheter ablation (RFCA) necessitate the administration of antiarrhythmic drugs to prevent early recurrence. The clinical outcomes among these patients may be influenced by varying antiarrhythmic regimens.

Objectives

To identify the risk factors associated with early recurrence and compare the clinical outcomes among different antiarrhythmic regimens in elderly patients with AF following radiofrequency catheter ablation (RFCA) during a 3-month period.

Methods

A retrospective observational study encompassed 420 elderly patients with AF following RFCA. Baseline data were collected during the initial postoperative visit and clinical outcomes were carefully monitored over a 3-month follow-up period. Logistic regression and Cox-proportional hazard regression analyses were performed to investigate the relationship between various antiarrhythmic regimens and the clinical outcomes.

Results

Multivariate logistic regression analysis revealed that age (p = 0.001), left atrial diameter (p < 0.001), left ventricular diameter (p = 0.015), reactive hyperemia index (RHI) (p < 0.001), antiarrhythmic drug (p < 0.001) and hs-cTnI (p = 0.017) were independent risk factors of early recurrence. Furthermore, in cox survival regression analysis model, survival rate of early recurrence in the amiodarone group was higher than in the propafenone group (HR 2.30, 95%CI 1.17-4.53, p = 0.016) and in the sotalol group (HR 3.60, 95%CI 2.17-5.95, p < 0.001). Compared to the amiodarone group, the incidence of liver dysfunction was lower in the dronedarone group (p = 0.046) and the propafenone group (p = 0.021). The incidence of bradyarrhythmia (p = 0.003), QT interval prolongation (p = 0.035) and atrioventricular transmission block (p = 0.021) were higher in the sotalol group than in the amiodarone group.

Conclusion

RHI was identified as an independent risk factor for early recurrence among elderly AF patients after RFCA. Compared to amiodarone, propafenone and sotalol exhibited an elevated risk of early recurrence. Although there was no significant difference in early recurrence between amiodarone and dronedarone, dronedarone emerged as the preferred option due to its lower frequency of adverse drug reactions than amiodarone.

Nomogram to predict recurrence risk factors in patients with non-valvular paroxysmal atrial fibrillation after catheter radiofrequency ablation

BACKGROUND

Radiofrequency catheter ablation (RFCA) is an effective method for controlling the heart rate of paroxysmal atrial fibrillation (PAF). However, recurrence is trouble under the RFCA. To gain a deeper understanding of the risk factors for recurrence in patients, we created a nomogram model to provide clinicians with treatment recommendations.

METHODS

A total of two hundred thirty-three patients with PAF treated with RFCA at Guizhou Medical University Hospital between January 2021 and December 2022 were consecutively included in this study, and after 1 year of follow-up coverage, 166 patients met the nadir inclusion criteria. Patients with AF were divided into an AF recurrence group and a non-recurrence group. The nomogram was constructed using univariate and multivariate logistic regression analyses. By calculating the area under the curve, we analyzed the predictive ability of the risk scores (AUC). In addition, the performance of the nomogram in terms of calibration, discrimination, and clinical utility was evaluated.

RESULTS

At the 12-month follow-up, 48 patients (28.92%) experienced a recurrence of AF after RFCA, while 118 patients (71.08%) maintained a sinus rhythm. In addition to age, sex, and TRV, LAD, and TTPG were independent predictors of recurrence of RFCA. The c-index of the nomogram predicted AF recurrence with an accuracy of .723, showing good decision curves and a calibrated nomogram, as determined by internal validation using a bootstrap sample size of 1000.

CONCLUSION

We created a nomogram based on multifactorial logistic regression analysis to estimate the probability of recurrence in patients with atrial fibrillation 1 year after catheter ablation. This plot can be utilized by clinicians to predict the likelihood of recurrence.

Development and Validation of a Novel Prognostic Model Predicting the Atrial Fibrillation Recurrence Risk for Persistent Atrial Fibrillation Patients Treated with Nifekalant During the First Radiofrequency Catheter Ablation

BACKGROUND

This study aimed to establish and assess a prediction model for patients with persistent atrial fibrillation (AF) treated with nifekalant during the first radiofrequency catheter ablation (RFCA).

METHODS

In this study, 244 patients with persistent AF from January 17, 2017 to December 14, 2017, formed the derivation cohort, and 205 patients with persistent AF from December 15, 2017 to October 28, 2018, constituted the validation cohort. The least absolute shrinkage and selection operator regression was used for variable screening and the multivariable Cox survival model for nomogram development. The accuracy and discriminative capability of this predictive model were assessed according to discrimination (area under the curve [AUC]) and calibration. Clinical practical value was evaluated using decision curve analysis.

RESULTS

Body mass index, AF duration, sex, left atrial diameter, and the different responses after nifekalant administration were identified as AF recurrence-associated factors, all of which were selected for the nomogram. In the development and validation cohorts, the AUC for predicting 1-year AF-free survival was 0.863 (95% confidence interval (CI) 0.801-0.926) and 0.855 (95% CI 0.782-0.929), respectively. The calibration curves showed satisfactory agreement between the actual AF-free survival and the nomogram prediction in the derivation and validation cohorts. In both groups, the prognostic score enabled stratifying the patients into different AF recurrence risk groups.

CONCLUSIONS

This predictive nomogram can serve as a quantitative tool for estimating the 1-year AF recurrence risk for patients with persistent AF treated with nifekalant during the first RFCA.

Development and Validation of a Risk Nomogram Model for Predicting Recurrence in Patients with Atrial Fibrillation After Radiofrequency Catheter Ablation

Purpose

This study aimed to develop and validate a risk nomogram model for predicting the risk of atrial fibrillation recurrence after radiofrequency catheter ablation.

Patients and Methods

A retrospective observational study was conducted using data from 485 patients with atrial fibrillation who underwent the first radiofrequency ablation in our hospital from January 2018 to June 2021. All patients were randomized into training cohort (70%; n=340) and validation cohort (30%; n=145). Univariate and multivariate logistic regression analyses were used to identify independent risk factors. The predictive nomogram model was established by using R software. The nomogram was developed and evaluated based on differentiation, calibration, and clinical efficacy by concordance statistic (C-statistic), calibration plots, and decision curve analysis (DCA), respectively.

Results

The nomogram was established by four variables including left atrial diameter (OR 1.057, 95% CI 1.010–1.107, P=0.018), left ventricular ejection fraction (OR 0.943, 95% CI 0.905–0.982, P=0.005), type of atrial fibrillation (OR 2.164, 95% CI: 1.262–3.714), and systemic inflammation score (OR 1.905, 95% CI 1.408–2.577). The C-statistic of the nomogram was 0.741 (95% CI: 0.689–0.794) in the training cohort and 0.750 (95% CI: 0.670–0.831) in the validation cohort. The calibration plots showed good agreement between the predictions and observations in the training and validation cohorts. Decision curve analysis and clinical impact curves indicated the clinical utility of the predictive nomogram.

Conclusion

The nomogram model has good discrimination and accuracy, which can screen high-risk groups intuitively and individually, and has a certain predictive value for atrial fibrillation recurrence in patients after radiofrequency ablation.