Battery longevity of a helix-fixation dual-chamber leadless pacemaker: results from the AVEIR DR i2i Study
Bibliographic record
Abstract
AIMS: A dual-chamber leadless pacemaker (LP) system that employs distinct atrial and ventricular LP devices (ALP, VLP) has been introduced to clinical practice. Proprietary, low-energy, implant-to-implant (i2i) communication at each beat enables the devices to maintain synchronous atrioventricular sensing and pacing. We evaluated device longevities and contributing factors, such as i2i communication. METHODS AND RESULTS: Patients meeting dual-chamber pacing indications received the dual-chamber LP system as part of a prospective, multi-centre, international clinical trial (Aveir DR i2i Study, NCT05252702). Programming and diagnostics were interrogated from all de novo, non-revised, dual-chamber programmed devices at 12 months post-implant. This analysis included 302 patients (65% male; age 70 ± 13 years; weight 80 ± 19 kg; intrinsic heart rate 55 ± 7 bpm; 58% sinus node dysfunction, 27% atrioventricular block). At 12 months, devices were programmed to dual-chamber pacing (DDD(R) or DDI(R)) at a median 60 bpm rate, median 1.25 V pulse amplitude in ALP and 1.5 V in VLP, median 0.4 ms pulse width, and median i2i signal setting level 5 out of 7. Median ALP and VLP remaining battery longevities at 12 months were 4.3 and 9.1 years, with median total ALP and VLP longevities of 5.3 and 9.9 years. Base rate, pulse amplitude, pacing percentage, event rate, impedance, and i2i setting level all exhibited significant correlations with ALP and VLP longevities (P < 0.001). Programming i2i setting levels below 7 produced the greatest longevity savings. CONCLUSION: The first dual-chamber LP demonstrated adequate projected battery longevity after 12 months of use. Patient-specific device programming considerations, unique to leadless devices, may extend longevity.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".