Morphometric Ablation Lesion Characteristics Comparing 4, 6, and 8 mm Electrode‐Tip Cryocatheters
Bibliographic record
Abstract
UNLABELLED: Cryolesion Characteristics. INTRODUCTION: Despite widespread clinical use, ablation lesions produced by cryocatheters with 6 and 8 mm electrode-tips have not been fully characterized. We, therefore, sought to quantify and compare lesion dimensions and thrombus formation with 4, 6, and 8 mm electrode-tip cryocatheters. METHODS AND RESULTS: By means of a randomized factorial design, 72 ablation lesions were created in atrial and ventricular chambers of adult miniature swine at a mean temperature of 79.9 +/- 4.0 degrees C. By histological morphometric analysis, the overall lesion depth was 4.3 +/- 2.1 mm, surface area 61.3 (28.7, 116.0) mm(2), and volume 130.2 (62.7, 231.3) mm(3). Cryolesions produced by all electrode-tip sizes were well circumscribed, with intact endothelial cell layers, and absence of thrombus. Colder temperatures generated lesions of greater surface area (P = 0.0061) and volume (P = 0.0080), but not depth. Depths were similar between the three electrode-tips. However, surface areas produced by 8 mm catheters were 91.7 mm(2) larger on average (176.7% increase, P = 0.0003) than 4 mm and 72.3 mm(2) greater (101.3% increase, P = 0.0144) than 6 mm catheters. The 8 and 6 mm catheters yielded mean lesion volumes 252.6 mm(3) (248.3% increase, P = 0.0041) and 115.9 mm(3) (113.9% increase, P = 0.0670) larger than 4 mm catheters. Greater variability in surface area and volume were observed with 8 mm catheters. CONCLUSION: Longer electrode-tip cryocatheters produce larger lesions of similar depth, with intact endothelial layers and absence of thrombosis. Surface areas and volumes may be particularly sensitive to catheter tip-to-tissue contact angles with larger electrodes, as reflected by greater variability with 8 mm tips.
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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".