Failed anti-tachycardia pacing can be used to differentiate atrial arrhythmias from ventricular tachycardia in implantable cardioverter-defibrillators
Bibliographic record
Abstract
BACKGROUND: Atrial fibrillation/tachycardia (AF/AT) may result in inappropriate therapies in implantable cardioverter-defibrillators (ICDs). The post-pacing interval (PPI) and tachycardia cycle length difference (PPI - TCL) has been previously demonstrated to indicate the proximity of the pacing site to a tachycardia origin. AIMS: We postulated that the PPI and PPI - TCL would be greater in AT/AF vs. ventricular tachycardia (VT) after episodes of failed anti-tachycardia pacing (ATP). METHODS AND RESULTS: This was a single-centre, retrospective study evaluating consecutive patients implanted with dual (DR)/biventricular (BIV) ICDs. Stored electrograms were used to determine whether the ATP captured the arrhythmia and the arrhythmia did not present with primary or secondary termination. Measurements were done using manual calipers. A total of 155 patients were included. There were 79 BIV and 76 DR devices. In total, 39 episodes were identified in 20 patients over a 23-month follow-up period. A total of 76 sequences of ATP (burst/ramp) were delivered, 28 (37%) of them inappropriate. Fifty-one events (18 AT/AF and 33 VT) were compared. The mean PPI was 693 ± 96 vs. 512 ± 88 ms (P < 0.01) and the mean PPI - TCL was 330 ± 97 vs. 179 ± 103 ms (P < 0.01) for AT/AF and VT, respectively. Cut-offs of 615 ms for the PPI [area under curve (AUC) 0.93; 95% confidence interval (CI): 0.84-1.00; P < 0.01] and 260 ms for PPI - TCL (AUC 0.86; 95% CI: 0.74-0.98; P < 0.01) were identified. CONCLUSION: The PPI and PPI - TCL after failed ATP differs significantly between AF/AT and VT and are therefore useful indices to discriminate between supraventricular tachycardia and VT in ICDs.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".