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Unexpected ICD Pulse Generator Failure Due to Electronic Circuit Damage Caused by Electrical Overstress

2001· article· en· W2020106067 on OpenAlexaff
Robert G. Hauser, David L. Hayes, Adrian K. Almquist, Andrew E. Epstein, Victor Parsonnet, G. Frank O. Tyers, Stephen C. Vlay, Mark H. Schoenfeld

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2001
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineDefibrillationShock (circulatory)Incidence (geometry)Pulse generatorMedical emergencyCardiologyVoltageInternal medicineElectrical engineering

Abstract

fetched live from OpenAlex

Because it is a lifesaving device, the unexpected failure of an ICD can be catastrophic. We report ICD electronic circuit failure due to electrical overstress damage (EOS) to the high voltage hybird circuit and other electronic components in a series of ICD pulse generator models. Data were obtained from the Multicenter Registry of Pacemaker and ICD Pacemaker and Lead Failures, and from the manufactures' adverse event reports, that were in the FDA's Manufacturer and User Facility Device Experience (MAUDE) database. Of 16 nonbattery Guidant/CPI ICD pulse generator failures reported to the registry, 6 (38%) have been confirmed by the manufacturer to be EOS related, and Guidant/CPI has reported 273 such failures to the FDA as of 12/29/00. The signs of failure included loss of telemetry and inability to deliver therapy, and some patients have experienced serious adverse events. Hybrid circuit damage may have occurred during capacitor charging or reform, and the majority appears to have happened during normal ICD function. While the incidence of this problem is unknown, a management strategy should be adopted that includes routine follow-up every 3 months and device evaluation after a shock or exposure to external defibrillation or electrosurgical devices. This study suggests that additional data are needed to determine the incidence of this problem, and that our present methods for monitoring the performance of ICD's following market release are inadequate.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.018
GPT teacher head0.312
Teacher spread0.294 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designCase report
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

Citations41
Published2001
Admission routes1
Has abstractyes

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