Characteristics of Slow Pathway Conduction After Successful AVNRT Ablation
Bibliographic record
Abstract
BACKGROUND: AV node slow pathway conduction can persist following successful ablation for AV node reentrant tachycardia (AVNRT). We hypothesized that careful examination of AV nodal conduction curves before and after effective AVNRT ablation in patients with persistent slow pathway conduction could shed light on this apparent paradox. METHODS AND RESULTS: Thirty patients (age 40.9 +/- 14.3; 8 male) were included. AV node function curves were created based on pre- and postablation atrial extrastimulus testing. Analysis of slow pathway function curves demonstrated significant decrease in AH for any given coupling interval after ablation (mean difference -68.1 [-94.5, -41.7] P < 0.001), graphically indicated by downward displacement of the curve. In addition, mean slow pathway effective refractory period (ERP) increased from 247.9 +/- 36.1 msec to 288.6 +/- 56.0 msec (P < 0.001); mean maximum AH interval decreased from 361.3 +/- 114.2 msec to 306.9 +/- 65.2 msec (P = 0.013); mean difference in minimum and maximum AH interval during slow pathway conduction decreased (from 94.5 +/- 75.8 msec to 59.6 +/- 46.2 msec (P = 0.016). Finally, mean difference between the fast and slow pathway effective refractory periods, the span of coupling intervals over which slow pathway conduction occurred, decreased (from 113.9 +/- 61.4 msec to 63.2 +/- 41.5 msec, P = 0.001). CONCLUSIONS: Ablation, which successfully eliminates inducible and spontaneous AVNRT in the presence of persistent slow pathway conduction, is associated with significantly altered slow pathway conduction characteristics, indicating the presence of a damaged or different slow pathway after ablation, incapable of sustaining tachycardia.
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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) | 0.001 | 0.001 |
| 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".