Bipolar ablation for deep intra-myocardial circuits: human ex vivo development and in vivo experience
Bibliographic record
Abstract
AIMS: Current conventional ablation strategies for ventricular tachycardia (VT) aim to interrupt reentrant circuits by creating ablation lesions. However, the critical components of reentrant VT circuits may be located at deep intramural sites. We hypothesized that bipolar ablations would create deeper lesions than unipolar ablation in human hearts. METHODS AND RESULTS: Ablation was performed on nine explanted human hearts at the time of transplantation. Following explant, the hearts were perfused by using a Langendorff perfusion setup. For bipolar ablation, the endocardial catheter was connected to the generator as the active electrode and the epicardial catheter as the return electrode. Unipolar ablation was performed at 50 W with irrigation of 25 mL/min, with temperature limit of 50°C. Bipolar ablation was performed with the same settings. Subsequently, in a patient with an incessant septal VT, catheters were positioned on the septum from both the ventricles and radiofrequency was delivered with 40 W. In the explanted hearts, there were a total of nine unipolar ablations and four bipolar ablations. The lesion depth was greater with bipolar ablation, 14.8 vs. 6.1 mm (P < 0.01), but the width was not different (9.8 vs. 7.8 mm). All bipolar lesions achieved transmurality in contrast to the unipolar ablations. In the patient with a septal focus, bipolar ablation resulted in termination of VT with no inducible VTs. CONCLUSION: By using a bipolar ablation technique, we have demonstrated the creation of significantly deeper lesions without increasing the lesion width, compared with standard ablation. Further clinical trials are warranted to detail the risks of this technique.
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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) | 0.002 | 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".