Aims Treatment guidelines for patients with atrial fibrillation (AF) suggest that patients should be managed with an antiarrhythmic drug (AAD) before undergoing catheter ablation (CA). This study evaluated whether pulmonary vein isolation employing cryoballoon CA is superior to AAD therapy for the prevention of atrial arrhythmia (AA) recurrence in rhythm control naive patients with paroxysmal AF (PAF). Methods and results A total of 218 treatment naive patients with symptomatic PAF were randomized (1 : 1) to cryoballoon CA (Arctic Front Advance, Medtronic) or AAD (Class I or III) and followed for 12 months. The primary endpoint was ≥1 episode of recurrent AA (AF, atrial flutter, or atrial tachycardia) >30 s after a prespecified 90-day blanking period. Secondary endpoints included the rate of serious adverse events (SAEs) and recurrence of symptomatic palpitations (evaluated via patient diaries). Freedom from AA was achieved in 82.2% of subjects in the cryoballoon arm and 67.6% of subjects in the AAD arm (HR = 0.48, P = 0.01). There were no group differences in the time-to-first (HR = 0.76, P = 0.28) or overall incidence [incidence rate ratio (IRR)=0.79, P = 0.28] of SAEs. The incidence rate of symptomatic palpitations was lower in the cryoballoon (7.61 days/year) compared with the AAD arm (18.96 days/year; IRR = 0.40, P < 0.001). Conclusions Cryoballoon CA was superior to AAD therapy, significantly reducing AA recurrence in treatment naive patients with PAF. Additionally, cryoballoon CA was associated with lower symptom recurrence and a similar rate of SAEs compared with AAD therapy.

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Our study suggests that CS leads, after medium-term implantation, can be effectively and safely removed using MD with polypropylene sheaths, in the case of unsuccessful LT. No pre-operative elements predictive of LT failure could be identified. Areas of adherence were rarely located in the CS or its tributaries.

Background: The HeartLogic algorithm combines multiple implantable cardioverter-defibrillator sensors to identify patients at risk of heart failure (HF) events. We sought to evaluate the risk stratification ability of this algorithm in clinical practice. We also analyzed the alert management strategies adopted in the study group and their association with the occurrence of HF events. Methods: The HeartLogic feature was activated in 366 implantable cardioverter-defibrillator and cardiac resynchronization therapy implantable cardioverter-defibrillator patients at 22 centers. The median follow-up was 11 months [25th–75th percentile: 6–16]. The HeartLogic algorithm calculates a daily HF index and identifies periods IN alert state on the basis of a configurable threshold. Results: The HeartLogic index crossed the threshold value 273 times (0.76 alerts/patient-year) in 150 patients. The time IN alert state was 11% of the total observation period. Patients experienced 36 HF hospitalizations, and 8 patients died of HF during the observation period. Thirty-five events were associated with the IN alert state (0.92 events/patient-year versus 0.03 events/patient-year in the OUT of alert state). The hazard ratio in the IN/OUT of alert state comparison was (hazard ratio, 24.53 [95% CI, 8.55–70.38], P <0.001), after adjustment for baseline clinical confounders. Alerts followed by clinical actions were associated with less HF events (hazard ratio, 0.37 [95% CI, 0.14–0.99], P =0.047). No differences in event rates were observed between in-office and remote alert management. Conclusions: This multiparametric algorithm identifies patients during periods of significantly increased risk of HF events. The rate of HF events seemed lower when clinical actions were undertaken in response to alerts. Extra in-office visits did not seem to be required to effectively manage HeartLogic alerts. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT02275637.