Acute Procedural Results of Pulsed Field Cryoablation for Persistent Atrial Fibrillation: Multicenter First‐in‐Human PARALELL Trial
Bibliographic record
Abstract
INTRODUCTION: Pulsed Field Cryoablation (PFCA) is a dual-energy cardiac ablation modality consisting of short-duration ultra-low temperature cryoablation (ULTC) followed immediately by pulsed field ablation (PFA) delivered from the same catheter. It is hypothesized that PFCA may improve contact stability during PFA, while maintaining lesion depth and effectiveness of ULTC. METHODS: PARALELL is a first-in-human multicenter study evaluating safety and effectiveness of a novel PFCA catheter and system in patients with persistent atrial fibrillation (PsAF) using the combination of pulmonary vein (PVI) and posterior wall (PWI) isolation. RESULTS: Sixty-six patients were ablated at six sites. One groin hematoma and one intubation-related hospitalization were the only serious procedure- or device-related adverse events recorded in the study. Per protocol, acute effectiveness was evaluated in 46 patients, including 31 patients with post-hoc analysis of cryogenic energy per lesion. After an average of 21.1 ± 9.3 lesions per patient the rates of PVI and PWI were 95.7% (176/184) and 97.7% (42/43), respectively. The average cryogenic energy per patient was highly predictive of acute isolation success with ROC AUC = 0.944% and 100% rates of both PVI and PWI in 24 patients in the optimal energy cohort. Grade I microbubbles and faint muscle contractions were detected in 1.1% and 0.5% of ablations, respectively. CONCLUSION: This initial multi-center experience suggests that PFCA can be efficiently performed for PVI and PWI using a single versatile catheter system, with high acute success and good early safety profile. The evaluation of the chronic 12-month effectiveness of PFCA is ongoing.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".