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Record W2766901764 · doi:10.1002/ccd.27184

Novel use of cutting balloon to treat subintimal hematomas during chronic total occlusion interventions

2017· article· en· W2766901764 on OpenAlexaff
Minh Vo, Emmanouil S. Brilakis, J. Aaron Grantham

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2017
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsCanadian VIGOUR Centre
Fundersnot available
KeywordsMedicineCutting balloonBalloonConventional PCIAngioplastyHematomaRadiologyPercutaneousOcclusionCoronary occlusionPercutaneous coronary interventionSurgeryReentryDissection (medical)StentCardiologyMyocardial infarctionRestenosis

Abstract

fetched live from OpenAlex

Contemporary chronic total occlusion (CTO) percutaneous coronary interventional (PCI) techniques are increasingly dependent upon dissection and reentry techniques (DARTs) especially for long occluded lesions. DARTs can result in compressive hematomas during CTO interventions and traditional treatment with balloon angioplasty and/or coronary stenting are often suboptimal and may extend the hematoma distally. We describe the novel use of a cutting balloon to "express" these compressive hematomas and restore antegrade coronary blood flow.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.313
Teacher spread0.258 · 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

Citations17
Published2017
Admission routes1
Has abstractyes

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