Does Adenosine Response Predict Clinical Recurrence of Atrial Fibrillation After Pulmonary Vein Isolation?
Bibliographic record
Abstract
BACKGROUND: Approximately 30% of patients undergoing pulmonary vein isolation (PVI) for atrial fibrillation (AF) have clinical recurrence of AF, and a great majority of these patients have recovery of vein conduction. Adenosine can be associated with acute recovery of conduction to the pulmonary veins immediately after isolation. However, it is not known whether this is prognostic for permanent recovery of conduction or recurrence of AF. METHODS: Patients with paroxysmal AF underwent PVI, with administration of adenosine after electrical isolation. Those with transient conduction recovery (TCR+) underwent no further ablation and were compared to those without (TCR-) for clinical AF recurrence and conduction recovery at second procedure. RESULTS: Seventy-two consecutive PVI patients were studied (mean age 56.7 ± 9.2, 61 male). Twenty-five (35%) patients had transient recovery of conduction with adenosine. After 1 year, 18 patients (25%) had symptomatic recurrence of AF. In this group of 18 patients, 6 were TCR+ at initial ablation (sensitivity 33%, NPV = 74%). In the remaining group of 54 patients free from AF recurrence, 35 patients (65%) were TCR- at initial ablation (specificity 65%, PPV = 24%). All 18 patients with recurrent AF underwent repeat procedure and had at least 1 pulmonary vein with recurrent conduction. The initial adenosine test correctly predicted 13 out of 36 (36%) veins, with positive predictive value 90% and negative predictive value 15%. CONCLUSIONS: Adenosine testing for TCR does not appear to predict recurrence of clinical AF. TCR- veins remain susceptible to conduction recovery, as determined at the follow-up procedure.
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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 | 0.001 | 0.004 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".