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Standardized Definition of Structural Valve Degeneration for Surgical and Transcatheter Bioprosthetic Aortic Valves

2018· review· en· W2785020011 on OpenAlexafffund
Danny Dvir, Thierry Bourguignon, Catherine M Otto, Rebecca T. Hahn, Raphaël Rosenhek, John G. Webb, Hendrik Treede, Maurice Enriquez‐Sarano, Ted Feldman, Harindra C. Wijeysundera, Yan Topilsky, Michel Aupart, Michael J. Reardon, G. Burkhard Mackensen, Wilson Y. Szeto, Ran Kornowski, James S. Gammie, Ajit P. Yoganathan, Yaron Arbel, Michael A. Borger, Matheus Simonato, Mark Reisman, Raj Makkar, Alexandre Abizaid, James M. McCabe, Gry Dahle, Gabriel S. Aldea, Jonathon Leipsic, Philippe Pîbarot, Neil Moat, Michael J. Mack, A. Pieter Kappetein, Martin B. Leon

Bibliographic record

VenueCirculation · 2018
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSunnybrook HospitalUniversité LavalMontreal Heart InstituteSt. Paul's Hospital
FundersHouston Methodist Research InstituteMedizinische Universität WienGeorgia Institute of TechnologyTel Aviv UniversityEmory UniversityUniversity of TorontoUniversität WienCedars-Sinai Medical CenterErasmus Medisch CentrumUniversité LavalNorthShore University HealthSystemUniversity of WashingtonUniversity of Pennsylvania
KeywordsMedicineDegeneration (medical)TerminologyHeart valveComparabilityValve replacementSurgeryIntensive care medicineRadiologyStenosisPathology

Abstract

fetched live from OpenAlex

Bioprostheses are prone to structural valve degeneration, resulting in limited long-term durability. A significant challenge when comparing the durability of different types of bioprostheses is the lack of a standardized terminology for the definition of a degenerated valve. This issue becomes especially important when we try to compare the degeneration rate of surgically inserted and transcatheter bioprosthetic valves. This document, by the VIVID (Valve-in-Valve International Data), proposes practical and standardized definitions of valve degeneration and provides recommendations for the timing of clinical and imaging follow-up assessments accordingly. Its goal is to improve the quality of research and clinical care for patients with deteriorated bioprostheses by providing objective and strict criteria that can be utilized in future clinical trials. We hope that the adoption of these criteria by both the cardiological and surgical communities will lead to improved comparability and interpretation of durability analyses.

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)0.006
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.008
Threshold uncertainty score0.030

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0080.004
Science and technology studies0.0000.002
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.382
Teacher spread0.328 · 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 designNot applicable
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

Citations472
Published2018
Admission routes2
Has abstractyes

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