A Novel Pacing Maneuver to Localize Focal Atrial Tachycardia
Bibliographic record
Abstract
BACKGROUND: Although focal atrial tachycardias cannot be entrained, we hypothesized that atrial overdrive pacing (AOP) can be an effective adjunct to localize the focus of these tachycardias at the site where the post-pacing interval (PPI) is closest to the tachycardia cycle length (TCL). METHODS: Overdrive pacing was performed in nine patients during atrial tachycardia, and in a comparison group of 15 patients during sinus rhythm. Pacing at a rate slightly faster than atrial tachycardia in group 1 and sinus rhythm in group 2 was performed from five standardized sites in the right atrium and coronary sinus. The difference between the PPI and tachycardia or sinus cycle length (SCL) was recorded at each site. The tachycardia focus was then located and ablated in group 1, and the atrial site with earliest activation was mapped in group 2. RESULTS: In both groups the PPI-TCL at the five pacing sites reflected the distance from the AT focus or sinus node. In group 1, PPI-TCL at the successful ablation site was 11 +/- 8 msec. In group 2, PPI-SCL at the site of earliest atrial activation was 131 +/- 37 msec (P < 0.001 for comparison). In groups 1 and 2, calculated values at the five pacing sites were proportional to the distance from the AT focus or sinus node, respectively. CONCLUSIONS: The PPI-TCL after-AOP of focal atrial tachycardia has a direct relationship to proximity of the pacing site to the focus, and may be clinically useful in finding a successful ablation site.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".