Abstract 11448: Feasibility and Septal Perforation Rates in Left Bundle Branch Area Pacing
Bibliographic record
Abstract
Introduction: Left Bundle Branch area Pacing (LBBaP) is gaining prevalence as a more physiologic alternative to conventional right ventricular pacing. Given limited literature on LBBaP, this retrospective study assessed feasibility and septal perforation rates following LBBaP. Methods: Procedure reports and electrophysiologic parameters were reviewed of patients that underwent LBBaP since 2019. Partial septal perforation was defined as any two of: a) reduction of impedance by 200 ohms b) increase in capture threshold by 50% and c) decrease in ventricular sensing by 50% during follow-up compared to approximately 1-week post pacemaker implant. Results: Since 2019, LBBaP was attempted in 168 patients and was successful in 102 (60.7 %), partial successful in 55 (32.7%) defined as QRS reduction of >20ms and duration <140ms, and unsuccessful in 11 (6.6%). QRS duration shortened or remained short after successful LBBaP compared to unsuccessful (113 vs 147 ms, p < 0.001). Left ventricular ejection fraction was similar following successful LBBaP (p = 0.92). Five patients (3%) had potential septal perforation based on above criteria. Lead revisions were not arranged for these patients as pacing requirements were not high and it was clinically appropriate to continue 3 monthly observations in clinic. Conclusions: We report success rates of LBBaP recently adopted in a large tertiary center. In a medium-term follow-up, we show that changes in electrophysiologic parameters likely consistent with partial septal perforation may occur spontaneously in some patients (3% in our cohort) over time. Clinical significance of these changes and confirmation with imaging requires further study.
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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 | 0.007 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".