Ablation Lesion Size Correlates with Pacing Threshold:
Bibliographic record
Abstract
The virtual electrode model predicts that pacing stimulus strength should reflect proximity of the pacing electrode to excitable myocardium, allowing pacing threshold to assess radiofrequency (RF) ablation lesions and unexcitable scar. The purpose of this study is to correlate RF lesion size with pacing threshold and electrogram (EG) amplitude change at the ablation site. In four swine (32-58 kg, 20 ventricular RF lesions were created using a 4-mm tip electrode catheters under fluoroscopic and electroanatomic guidance. Unipolar pacing threshold and bipolar and unipolar EG amplitude were measured before and after ablation and compared with lesion size measured in the fixed, serially sectioned tissue. Lesion diameter ranged from 6.4 to 19 mm and volume ranged from 29 to 1920 mm3. Ablation increased the pacing threshold by 320%, from 0.9 +/- 0.3 to 3.6 +/- 2.6 mA, P < 0.001. The change in pacing threshold correlated with lesion volume R = 0.88, P < 0.001). Linear regression predicts that lesion volume (mm3) = 160 X rise in pacing threshold + 13. Ablation reduced peak to peak bipolar EG amplitude by 56%, from 2.5 +/- 2.0 mV to 1.1 +/- 0.6 mV (P = 0.005). Unipolar EG amplitude diminished by only 22% from 4.0 +/- 1.6 to 3.2 +/- 0.9 mV postablation (P = 0.005). The correlations of lesion volume with change in either bipolar R = 0.14, P = 0.6) or unipolar R = 0.18, P = 0.6) EG amplitude were poor. Pacing threshold correlates with RF ablation lesion size, consistent with the virtual electrode model. In normal myocardium, change in pacing threshold is likely to be a better marker of lesion size than electrogram amplitude.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".