With the aging population and the increasing incidence of basic illnesses such as hypertension and diabetes (DM), the incidence of atrial fibrillation (AF) has increased significantly. AF is the most common arrhythmia in clinical practice, which can cause heart failure (HF) and ischemic stroke (IS), increasing disability and mortality. Current studies point out that myocardial fibrosis (MF) is one of the most critical substrates for the occurrence and maintenance of AF. Although myocardial biopsy is the gold standard for evaluating MF, it is rarely used in clinical practice because it is an invasive procedure. In addition, serological indicators and imaging methods have also been used to evaluate MF. Nevertheless, the accuracy of serological markers in evaluating MF is controversial. This review focuses on the pathogenesis of MF, serological evaluation, imaging evaluation, and anti-fibrosis treatment to discuss the existing problems and provide new ideas for MF and AF evaluation and treatment.

ObjectiveThis study was aimed to investigate the risk of recurrence in patients with atrial fibrillation (AF) after radiofrequency ablation and predict risk of recurrence using C2HEST and HATCH scores.MethodsWe retrospectively included 322 patients with AF from Second Hospital of Lanzhou University, and 261 patients were included in the analysis finally. They had AF and were admitted for radiofrequency catheter ablation. We compared the ability of C2HEST and HATCH scores to predict recurrence after radiofrequency ablation of AF. The predictive ability of C2HEST and HATCH scores for AF recurrence was estimated by the area under the receiver operating characteristic curve (AUROC). The difference in receiver operating characteristic curve between the two models was compared using the DeLong test.ResultsOf the 261 patients included in the analysis, 83 (31.6%) patients suffered a late recurrence of AF after radiofrequency ablation. The risk of postoperative recurrence of AF increased with increasing C2HEST and HATCH scores. The AUROC of C2HEST and HATCH scores in predicting postoperative recurrence of AF was 0.773 (95%CI, 0.713–0.833) and 0.801 (95% CI, 0.740–0.861), respectively. There was no significant difference between the two models in their ability to evaluate patients for postoperative recurrence of AF (DeLong test p-value = 0.36). Among the risk factors in both models, hypertension and heart failure (HF) contributed the most to postoperative recurrence after AF, and higher blood pressure and lower cardiac ejection fraction (EF) were associated with a higher risk of recurrence.ConclusionBoth C2HEST and HATCH scores were significantly associated with the risk of late recurrence after radiofrequency ablation of AF. Besides hypertension and HF contributed the most to postoperative recurrence after AF.

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AimsSeveral models have been developed to predict the risk of atrial fibrillation (AF) recurrence after radiofrequency catheter ablation (RFCA). However, these models are of poor quality from the start. We, therefore, aimed to develop and validate a predictive model for post-operative recurrence of AF.Materials and methodsIn a study including 433 patients undergoing the first circumferential pulmonary vein isolation (CPVI) procedure, independent predictors of AF recurrence were retrospectively identified. Using the Cox regression of designated variables, a risk model was developed in a random sample of 70% of the patients (development cohort) and validated in the remaining (validation cohort) 30%. The accuracy and discriminative power of the predictive models were evaluated in both cohorts.ResultsDuring the established 12 months follow-up, 134 patients (31%) recurred. Six variables were identified in the model including age, coronary artery disease (CAD), heart failure (HF), hypertension, transient ischemic attack (TIA) or cerebrovascular accident (CVA), and left atrial diameter (LAD). The model showed good discriminative power in the development cohort, with an AUC of 0.77 (95% confidence interval [CI], 0.69–0.86). Furthermore, the model shows good agreement between actual and predicted probabilities in the calibration curve. The above results were confirmed in the validation cohort. Meanwhile, decision curve analysis (DCA) for this model also demonstrates the advantages of clinical application.ConclusionA simple risk model to predict AF recurrence after ablation was developed and validated, showing good discriminative power and calibration.