Paced P‐wave morphology templates to guide atrial tachycardia localization: A derivation and validation study
Bibliographic record
Abstract
BACKGROUND: Surface ECG is a useful tool to guide mapping of focal atrial tachycardia (AT). OBJECTIVES: We aimed to construct 12-lead ECG templates for P-wave morphology (PWM) during endocardial pacing from different sites in both atria in patients with no apparent structural heart disease (derivation cohort), with the goal of creating a localization algorithm, which could subsequently be validated in a cohort of patients undergoing catheter ablation of focal AT (validation cohort). METHODS: We prospectively enrolled consecutive patients who underwent electrophysiology study, had no structural heart disease and no atrial enlargement. Atrial pacing, at twice diastolic threshold, was carried out at different anatomical sites in both atria. Paced PWM and duration were assessed. An algorithm was generated from the constructed templates of each pacing site. The algorithm was applied on a retrospective series of successfully ablated AT patients. Overall and site-specific accuracy were determined. RESULTS: Derivation cohort included 65 patients (25 men, age 37 ± 13 years). Atrial pacing was performed in 1025 sites in 61 patients (95%) in RA and in 15 patients (23%) in LA. The validation cohort included 71 patients (28 men, age 52 ± 19 years). AT were right atrial in 66.2%. The algorithm successfully predicted AT origin in 91.5% of patients (100% in LA and 87.2% in RA). It was off by one adjacent segment in the remaining 8.5%. CONCLUSIONS: A simple ECG algorithm based on paced PWM templates was highly accurate in localizing site of origin of focal AT in patients with structurally normal hearts.
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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 | 0.004 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".