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Record W2908876215 · doi:10.7326/acpjc-2019-170-2-005

A wearable cardioverter–defibrillator did not reduce arrhythmic death in MI with reduced ejection fraction

2019· letter· en· W2908876215 on OpenAlexaffabout
Kristen Sullivan, Harriette G.C. Van Spall

Bibliographic record

VenueAnnals of Internal Medicine · 2019
Typeletter
Languageen
FieldMedicine
TopicCardiac pacing and defibrillation studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineImplantable cardioverter-defibrillatorMyocardial infarctionEjection fractionInternal medicineCardiologySudden cardiac deathHeart failure

Abstract

fetched live from OpenAlex

ACP Journal Club15 January 2019A wearable cardioverter–defibrillator did not reduce arrhythmic death in MI with reduced ejection fractionKristen Sullivan, MD, Harriette G.C. Van Spall, MD, MPH, FRCPCKristen Sullivan, MDMcMaster University, Hamilton, Ontario, Canada (K.S., H.G.V.)Search for more papers by this author, Harriette G.C. Van Spall, MD, MPH, FRCPCMcMaster University, Hamilton, Ontario, Canada (K.S., H.G.V.)Search for more papers by this authorAuthor, Article, and Disclosure Informationhttps://doi.org/10.7326/ACPJC-2019-170-2-005 SectionsAboutFull TextPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinkedInRedditEmail Source CitationOlgin JE, Pletcher MJ, Vittinghoff E, et al; VEST Investigators. Wearable cardioverter-defibrillator after myocardial infarction. N Engl J Med. 2018;379:1205-15. https://pubmed.ncbi.nlm.nih.gov/30280654Clinical Impact RatingsCardiology: References1 Hohnloser SH, Kuck KH, Dorian P, et al; DINAMIT Investigators. Prophylactic use of an implantable cardioverter-defibrillator after acute myocardial infarction. N Engl J Med. 2004;351:2481-8. [PMID: 15590950] Google Scholar2 Steinbeck G, Andresen D, Seidl K, et al; IRIS Investigators. Defibrillator implantation early after myocardial infarction. N Engl J Med. 2009;361:1427-36. [PMID: 19812399] Google Scholar3 Tseng ZH, Olgin JE, Vittinghoff E, et al. Prospective countywide surveillance and autopsy characterization of sudden cardiac death: POST SCD Study. Circulation. 2018;137:2689-2700. [PMID: 29915095] Google Scholar Author, Article, and Disclosure InformationAffiliations: McMaster University, Hamilton, Ontario, Canada (K.S., H.G.V.)This article was published at Annals.org on 1 January 2019. PreviousarticleNextarticle Advertisement FiguresReferencesRelatedDetails Metrics 15 January 2019Volume 170, Issue 2Page: JC5KeywordsArrhythmiaEjection fractionImplantable cardioverter defibrillatorsMortalityMyocardial infarctionRevascularizationShockSudden cardiac deathTachycardiaThorax ePublished: 15 January 2019 Issue Published: 15 January 2019 Copyright & PermissionsCopyright © 2019 by American College of Physicians. All Rights Reserved.PDF downloadLoading ...

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)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.032
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0320.002

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 head0.055
GPT teacher head0.334
Teacher spread0.279 · 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 designObservational
Domainnot available
GenreCommentary

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

Citations0
Published2019
Admission routes2
Has abstractyes

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