Chronic wireless communication between dual-chamber leadless pacemaker devices
Bibliographic record
Abstract
BACKGROUND: Aveir DR (Abbott, Abbott Park, IL) is a dual-chamber leadless pacemaker (LP) system with distinct atrial and ventricular LPs (ALP, VLP) that communicate wirelessly to deliver atrioventricular synchronous pacing. Success rates of these implant-to-implant (i2i) transmissions have not been systematically evaluated. OBJECTIVE: This study aims to evaluate chronic i2i success rates in a clinical setting. METHODS: Patients meeting standard dual-chamber pacing indications were enrolled and implanted with dual-chamber LP systems as part of a prospective international clinical trial (Aveir DR i2i Study). The percent of successful i2i transmissions from ALP-to-VLP (A-to-V) and VLP-to-ALP (V-to-A) were interrogated from LPs in de novo patients using the device programmer at implant, discharge, and at 1, 3, and 6 months postimplant (1M, 3M, 6M). RESULTS: A total of 399 patients completed device implant and i2i diagnostic interrogation (62% male; age 69 years; 65% sinus node dysfunction, 32% atrioventricular [AV] block). Median A-to-V and V-to-A i2i success rates exceeded 90% of beats at all time-points from implant to 6M. The minority of patients with A-to-V or V-to-A i2i success in <70% of beats at implant (A-to-V: 19% of patients, V-to-A: 31% of patients) showed roughly 40% improvement by 1M, with this minority dropping to roughly 5% of patients by 6M. Improvement in i2i communication success may be attributed to reprogramming of i2i setting levels, natural changes in dominant posture, and device stabilization. CONCLUSION: Wireless implant-to-implant communication in the new dual-chamber leadless pacemaker system demonstrated successful transmissions in >90% of beats throughout the 6-month evaluation period. Communication success improved significantly over time postimplant for specific subgroups. CLINICAL TRIAL REGISTRATION: Aveir DR i2i Study, ClinicalTrials.gov ID NCT05252702.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".