P6546Canadian Registry of Electronic Device Outcomes (CREDO): remote monitoring outcomes in the abbott battery performance alert, a multicentre cohort
Bibliographic record
Abstract
Abstract Background Cardiac implantable electronic devices have been known to have lead and device malfunctions leading to advisories. Increased use of remote monitoring of devices has been suggested to allow the identification of abnormal device performance and allow early intervention. We sought to describe the outcomes of patients with and without remote monitoring of in devices in the Abbott Premature Battery Depletion advisory with data from a Canadian registry Methods Patients with an Abbott device subject to the Battery Performance Alert Advisory from nine ICD implanting centres in Canada were included in the registry. The use of remote monitoring was identified from baseline and followup data in the registry. The primary outcome was detection of premature battery depletion and all cause mortality. Results 2679 patents were identified with a device subject to the advisory. Devices were implanted between 2010 and 2017. 1716 patients (64%) had remote monitoring at baseline with this increasing to 83.7% at followup at 12 months. Premature battery depletion occurred in 43 patients (1.6%). Discovery of premature battery depletion was detected by remote monitoring in 70% of patients. There were 492 deaths during the follow up. Mortality was higher in those without a remote monitor compared to those with a remote monitor at follow-up and remote monitor at baseline and follow-up (11.3%, 2.6% versus 6.1% respectively; p=0.0186). There were no deaths attributed to premature battery depletion Conclusion The use of remote monitoring in patients with ICD and CRT under advisory reliably detected device failure and was associated with a reduction in all-cause mortality.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".