Histopathology of Cryoballoon Ablation‐Induced Phrenic Nerve Injury
Bibliographic record
Abstract
INTRODUCTION: Hemi-diaphragmatic paralysis is the most common complication associated with cryoballoon ablation for atrial fibrillation, yet the histopathology of phrenic nerve injury has not been well described. METHODS AND RESULTS: A preclinical randomized study was conducted to characterize the histopathology of phrenic nerve injury induced by cryoballoon ablation and assess the potential for electromyographic (EMG) monitoring to limit phrenic nerve damage. Thirty-two dogs underwent cryoballoon ablation of the right superior pulmonary vein with the objective of inducing phrenic nerve injury. Animals were randomized 1:1 to standard monitoring (i.e., interruption of ablation upon reduction in diaphragmatic motion) versus EMG guidance (i.e., cessation of ablation upon a 30% reduction in the diaphragmatic compound motor action potential [CMAP] amplitude). The acute procedural endpoint was achieved in all dogs. Phrenic nerve injury was characterized by Wallerian degeneration, with subperineural injury to large myelinated axons and evidence of axonal regeneration. The degree of phrenic nerve injury paralleled the reduction in CMAP amplitude (P = 0.007). Animals randomized to EMG guidance had a lower incidence of acute hemi-diaphragmatic paralysis (50% vs 100%; P = 0.001), persistent paralysis at 30 days (21% vs 75%; multivariate odds ratio 0.12, 95% confidence interval [0.02, 0.69], P = 0.017), and a lesser severity of histologic injury (P = 0.001). Mature pulmonary vein ablation lesion characteristics, including circumferentiality and transmurality, were similar in both groups. CONCLUSION: Phrenic nerve injury induced by cryoballoon ablation is axonal in nature and characterized by Wallerian degeneration, with potential for recovery. An EMG-guided approach is superior to standard monitoring in limiting phrenic nerve damage.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".