P292Does the regional incidence and cycle length of AF mechanisms differ between de novo and redo ablation patients?
Bibliographic record
Abstract
Funding Acknowledgements: Acutus Medical Background: AF pts can require >1 ablation to achieve successful outcome. The inability to map AF mechanisms (AFMs) may contribute to the lack of success. A new, non-contact, 3-D imaging/mapping system that uses ultrasound (U/S) to acquire chamber anatomy and dipole density (DD) instead of voltage to globally map AF, enabled characterization of AFMs in de novo and redo ablation pts. Purpose: Quantify and compare regional incidence and avg. fibrillatory CL of AFMs in de novo and redo AF ablation pts. Methods: Pts were mapped prior to ablation using a 6-splined catheter with 48 U/S crystals and 48 electrodes. U/S LA anatomies were constructed and 4 sec of AF mapped. DD inverse solution subtracts distant sources and displays localized map of activation, highlighting arrhythmic drivers and maintainers. Conduction is displayed as a retrospective moving color-map. Red is present location of leading-edge, while trailing color-bands represent past locations in time. Identified AFMs were classified as focal, rotational and irregular. Results: A total of 13 de novo and 10 redo pts were enrolled at 5 sites. De novo/Redo; 85%/75% Male, Age 58.2/62.9, AF duration 3.6 ± 5.6 /9.1 ± 4.9 yrs, LAD 42.3 ± 6.5/46.8 ± 6.5 mm, ablation conversion 15%/60%. AF duration and ablation conversion were significant (p = 0.01). Incidence of regional AFMs was not statistically different between the groups. All of the AFMs (100%) in the redo group were non-pulmonary vein (PV) related. Non-PV AFM incidence was similarly high in de novo (96.7%) (Figure 1). Regional and irregular AFM CLs in the redo group were significantly longer than the de novo group. Conclusions: The incidence of regional AFMS is similar in de novo and redo pts with a similar proportion being non-PV related. AFM CL was longer in redo patients likely due to effect of prior ablation. Abstract P292 Figure.
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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".