Temperature-based rate response in a leadless pacemaker system
Bibliographic record
Abstract
BACKGROUND: A new dual-chamber leadless pacemaker (DR-LP) system, composed of 2 implantable devices in the right ventricle and right atrium, uses a less common temperature-based rate-response sensor. There is a need to understand the effectiveness of the rate response during exercise in both the ventricular (VR-LP) and atrial (AR-LP) devices. OBJECTIVE: We sought to determine whether temperature-based rate-responsive pacing is proportional to metabolic workload during an exercise test in a leadless pacemaker system. METHODS: After 6 weeks of implantation, we administered a treadmill exercise protocol to eligible participants concurrently enrolled in the LEADLESS II-Phase 2 and Aveir DR i2i studies. Programmed settings were optimized after a prior 6-minute walk test. We evaluated the ventricular and atrial rate-response sensors in participants implanted with the VR-LP and DR-LP system, respectively. For each device, the normalized slopes of sensor-indicated rate vs metabolic workload were aggregated across all analyzable patients. If the mean slope's 95% confidence interval (CI) fell within the prespecified 0.65 and 1.35 acceptance range, the rate response was considered proportional to metabolic demand. RESULTS: Seventeen participants had a mean ventricular rate-response slope of 0.93 ± 0.29 (CI, 0.78-1.08), which fell within the acceptance criteria (P = .001). Twenty participants had a mean atrial rate-response slope of 0.91 ± 0.28 (CI, 0.78-1.05), also falling within the prespecified criteria (P < .001). CONCLUSION: The temperature-based sensor in a dual-chamber leadless pacemaker system was shown to be effective at modulating pacing rate in response to increased metabolic demand for right ventricular and atrial devices. GOV IDENTIFIER: NCT04559945 (LEADLESS II-Phase 2 study) and NCT05252702 (Aveir DR i2i study).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".