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Record W2293842313 · doi:10.1111/pace.12850

Estimating the Risks and Benefits of Implantable Cardioverter Defibrillator Generator Replacement: A Systematic Review

2016· review· en· W2293842313 on OpenAlexaff
Krystina B. Lewis, Dawn Stacey, Sandra Carroll, Laura Boland, Lindsey Sikora, David H. Birnie

Bibliographic record

VenuePacing and Clinical Electrophysiology · 2016
Typereview
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsMcMaster UniversityOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsMedicineImplantable cardioverter-defibrillatorIntensive care medicineQuality of life (healthcare)Emergency medicineInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Every 4-7 years an implantable cardioverter defibrillator (ICD) pulse generator must be replaced surgically. This procedure is not without risk. In some cases, the risk versus benefit ratio may be against replacement. We aimed to synthesize the evidence on risks, benefits, and costs related to ICD replacement. METHODS: A systematic review was conducted using electronic databases from 2000 onward. Literature screening, quality appraisal, and data extraction were independently conducted by two reviewers. Outcomes included major and minor complications, ICD therapies, and costs, which were synthesized descriptively. RESULTS: Of 1,483 citations, 17 nonrandomized studies met criteria. Median rate of major complications was 4.05% (range 0.55-7.37%) and minor complications was 3.50% (range 0.36-7.37%). Without non-ICD control groups, the true risk reduction provided by the ICD following replacement is unknown. Following ICD replacement, annualized rate of appropriate ICD therapy was 10.52% (range 2.42-75.00%). Of these, patients without therapies during their first generator life and those no longer meeting ICD criteria received appropriate therapies at nontrivial rates. CONCLUSION: Rates of complications associated with ICD replacement are substantial. No study had nonreplacement groups, hence the true risk reduction provided by the ICD following replacement is unknown. Our analysis did not identify a subgroup at low risk of therapies following replacement. Shared discussions should occur with patients about the evidence, healthcare goals, risk tolerances, and feelings about life and death trade-offs to enable high-quality decisions about ICD replacement.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.101
Threshold uncertainty score0.773

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0080.001
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 head0.080
GPT teacher head0.398
Teacher spread0.318 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations30
Published2016
Admission routes1
Has abstractyes

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