P1056Contact force as a predictor of complete lesion formation in patients with ischemic scar-related ventricular tachycardia
Bibliographic record
Abstract
Background: Contact force (CF) is a useful ablation parameter. Correlation between CF and complete lesion (CL) formation, as defined by inability to pace each site after ablation in scar-related ventricular tachycardia (SRVT) hasn’t been demonstrated. Objective: We explored whether CF can predict complete lesion (CL) formation in-vivo. Methods: Consecutive patients (n=19, all men, age 66.5±9 years) with ischemic cardiomyopathy who had SRVT ablation were included in the study. All ablations were done using irrigated contact force-sensing catheters (Biosense Webster). CL formation was defined as local non-capture post ablation using unipolar pacing at 10 mA @ 2 ms. Ablation points were included in the analysis when pacing was performed post ablation and pre-ablation CF was available. We also collected power, temperature, impedance, bipolar and unipolar electrogram (EGM) signal amplitudes. Zones were divided according to bipolar voltage into Scar zone (<0.5 mV), border zone (0.5-1.5 mV) and normal (>1.5 mV). Results: Among 299 collected ablation points (16±10 points/patient), CL occurred at 146 points (48%). The only parameters that were associated with CL were lower mean impedance (115±13 vs. 117±11 ohms, p=0.049) and lower Unipolar/Bipolar EGM ratio (6.7±4.7 vs. 8.5±7.5, p=0.017). Mean CF was not different (19.4±9 vs. 19.4±11 grams, p=0.99). However, within scar zone, CF < 10 g was less likely to be associated with CL formation (9.8% vs. 21.9%, p=0.029). Conclusions: CF did not predict CL formation except within regions of scar, where CF<10g was negatively associated with CL formation. Lower Unipolar/Bipolar EGM ratio was significantly associated with CL formation.
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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".