Canadian Registry of Electronic Device Outcomes: remote monitoring outcomes in the Abbott battery performance alert—a multicentre cohort
Bibliographic record
Abstract
AIMS: Cardiac implantable electronic devices with device advisories have the potential of device malfunction. Remote monitoring (RM) of devices has been suggested to allow the identification of abnormal device performance and permit early intervention. We sought to describe the outcomes of patients with and without RM in devices subject to the Abbott Premature Battery Depletion (PBD) advisory with data from a Canadian registry. METHODS AND RESULTS: Patients with an Abbott device subject to the PBD advisory from nine implantable cardioverter defibrillator (ICD) implanting centres in Canada were included in the registry. The use of RM was identified from baseline and follow-up data in the registry. The primary outcome was detection of PBD and all-cause mortality. A total of 2666 patients were identified with a device subject to the advisory. In all, 1687 patients (63.2%) had RM at baseline. There were 487 deaths during follow-up. At a mean follow-up of 5.7 ± 0.7 years, mortality was higher in those without a remote monitor compared with RM at baseline (24.7% vs. 14.5%; P < 0.001). Pre-mature battery depletion was identified in 36 patients (2.1%) with RM vs. 7 (0.7%) without RM (P = 0.004). Time to battery replacement was significantly reduced in patients on RM (median 5 vs. 13 days, P = 0.001). CONCLUSION: The use of RM in patients with ICD and cardiac resynchronization therapy under advisory improved detection of PBD, time to device replacement, and was associated with a reduction in all-cause mortality. The factors influencing the association with mortality are unknown and deserve 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".