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Record W2121899839 · doi:10.1111/pace.12418

Heart Rhythm Society Members’ Views on Pacemaker and Implantable Cardioverter‐Defibrillator Reuse

2014· article· en· W2121899839 on OpenAlexaboutno aff
Andrew B. Hughey, Nimit Desai, Timir S. Baman, Lindsey Gakenheimer, Lindsay Hagan, James N. Kirkpatrick, Hakan Oral, Kim A. Eagle, Thomas Crawford

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2014
Typearticle
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsnot available
FundersWilliam and Flora Hewlett Foundation
KeywordsMedicineHeart RhythmReuseImplantable cardioverter-defibrillatorFamily medicineMedical emergencyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Reuse of cardiac implantable electronic devices (CIEDs) may help address the unmet need among patients in low- and middle-income countries (LMICs). METHODS: To examine Heart Rhythm Society (HRS) physicians' opinions regarding CIED reuse, an online survey eliciting attitudes toward CIED reuse was sent to all 3,380 HRS physician members. RESULTS: There were 429 responses (response rate 13%). A large majority of respondents agreed or strongly agreed that resterilization of devices for reimplantation in patients who cannot afford new devices may be safe (370, 87%) and, if proven to be safe, would be ethical (375, 88%). A total of 340 (81%) respondents would be comfortable asking their patients to consider donating their device, and 353 (84%) would be willing to reimplant a resterilized device if it were legal. The most commonly cited concerns about device reuse were infection (270, 64%) and device malfunction (125, 29%). Respondents from the United States and Canada had more favorable impressions of device reuse than respondents from other high-income countries (P < 0.05 for three of five positive statements regarding reuse), and were less likely to cite ethical concerns (P < 0.001). However, when responses from all high-income countries were compared with lower- and upper-middle income countries, there were no significant differences in the rates of approval. CONCLUSIONS: HRS survey respondents support the concept of CIED reuse for patients in LMICs who cannot afford new devices. Studies are needed to demonstrate the clinical efficacy and safety of this practice and to identify potential barriers to adoption among physicians.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.681

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 head0.030
GPT teacher head0.337
Teacher spread0.307 · 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 designNot applicable
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

Citations26
Published2014
Admission routes1
Has abstractyes

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