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Record W3084651845 · doi:10.1016/j.cjco.2020.09.008

Canadian Registry of Electronic Device Outcomes (CREDO): The Abbott ICD Premature Battery Depletion Advisory, a Multicentre Cohort Study

2020· article· en· W3084651845 on OpenAlexafffundabout
Jason Davis, Bernard Thibault, Iqwal Mangat, Benoit Coutu, Matthew T. Bennett, François Philippon, Roopinder K. Sandhu, Laurence D. Sterns, Vidal Essebag, Pablo B. Nery, George A. Wells, Raymond Yee, Derek V. Exner, Andrew D. Krahn, Ratika Parkash

Bibliographic record

VenueCJC Open · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsMcGill UniversityRoyal Jubilee HospitalUniversity of British ColumbiaSt. Michael's HospitalUniversity Health NetworkHamilton Health SciencesSouthlake Regional Health CenterMontreal Heart InstituteUniversité LavalQueen Elizabeth II Health Sciences Centre
FundersAbbott CanadaMedtronicNovartis
KeywordsCohortMedicineCohort studyGerontologyMedical emergencyEmergency medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Premature or rapid battery depletion may compromise the performance and reliability of an implantable cardioverter defibrillator (ICD), potentially resulting in harm or death to patients. We sought to describe the outcomes and clinical management of devices included in the Abbott ICD Premature Battery Depletion Advisory, using data from a Canadian registry. METHODS: This prospective observational study includes patients with an Abbott device subject to the advisory, from 9 centres in Canada. The incidence and outcomes related to device revision owing to premature battery depletion were identified and adjudicated by a committee. RESULTS: There were 2678 patients enrolled with a device subject to the advisory. Devices were implanted between 2010 and 2017; follow-up time was 5.7 ± 0.7 years. Device revision occurred in 222 patients (8.3%). Revision for premature battery depletion occurred in 43 patients (1.6%). Devices were revised at physician discretion on notice of the advisory in 16 patients (0.6%), and at patient request in 5 patients (0.2%). A total of 63 (2.4%) devices reached routine end of battery life. A further 95 (3.5%) patients underwent revision for other reasons. There were no reported major complications or adverse events with device revision owing to the advisory. There were no deaths attributed to premature battery depletion. CONCLUSIONS: The rate of premature battery depletion associated with the Abbott ICD Premature Battery Depletion Advisory is low. There were no clinically adverse events identified that were associated with the battery performance of devices under advisory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.021
GPT teacher head0.304
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations2
Published2020
Admission routes3
Has abstractyes

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