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Record W3156869543 · doi:10.1093/eurheartj/ehaa799

Valve Academic Research Consortium 3: updated endpoint definitions for aortic valve clinical research

2020· article· en· W3156869543 on OpenAlexafffund
Philippe Généreux, Nicolò Piazza, Maria Alu, Tamim Nazif, Rebecca T. Hahn, Philippe Pîbarot, Jeroen J. Bax, Jonathon Leipsic, Philipp Blanke, Eugene H. Blackstone, Matthew Finn, Samir Kapadia, Axel Linke, Michael J. Mack, Raj Makkar, Roxana Mehran, Jeffrey J. Popma, Michael J. Reardon, Josep Rodés‐Cabau, Nicolas M. Van Mieghem, John G. Webb, David J. Cohen, Martin B. Leon

Bibliographic record

VenueEuropean Heart Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversity of British ColumbiaSt. Paul's HospitalUniversité LavalMcGill University Health Centre
FundersMicroPortIdorsia PharmaceuticalsCanada Excellence Research Chairs, Government of CanadaAbiomedJanssen Scientific AffairsClaret MedicalAbbott VascularAbbott LaboratoriesRegeneron PharmaceuticalsMedicines CompanyBoston Scientific CorporationBristol-Myers SquibbAstraZenecaCSL BehringSanofiPfizerCardinal HealthEdwards Lifesciences
KeywordsMedicineEndpoint DeterminationClinical endpointClinical trialClinical researchAortic valveIntensive care medicineMedical physicsInternal medicine

Abstract

fetched live from OpenAlex

AIMS: The Valve Academic Research Consortium (VARC), founded in 2010, was intended to (i) identify appropriate clinical endpoints and (ii) standardize definitions of these endpoints for transcatheter and surgical aortic valve clinical trials. Rapid evolution of the field, including the emergence of new complications, expanding clinical indications, and novel therapy strategies have mandated further refinement and expansion of these definitions to ensure clinical relevance. This document provides an update of the most appropriate clinical endpoint definitions to be used in the conduct of transcatheter and surgical aortic valve clinical research. METHODS AND RESULTS: Several years after the publication of the VARC-2 manuscript, an in-person meeting was held involving over 50 independent clinical experts representing several professional societies, academic research organizations, the US Food and Drug Administration (FDA), and industry representatives to (i) evaluate utilization of VARC endpoint definitions in clinical research, (ii) discuss the scope of this focused update, and (iii) review and revise specific clinical endpoint definitions. A writing committee of independent experts was convened and subsequently met to further address outstanding issues. There were ongoing discussions with FDA and many experts to develop a new classification schema for bioprosthetic valve dysfunction and failure. Overall, this multi-disciplinary process has resulted in important recommendations for data reporting, clinical research methods, and updated endpoint definitions. New definitions or modifications of existing definitions are being proposed for repeat hospitalizations, access site-related complications, bleeding events, conduction disturbances, cardiac structural complications, and bioprosthetic valve dysfunction and failure (including valve leaflet thickening and thrombosis). A more granular 5-class grading scheme for paravalvular regurgitation (PVR) is being proposed to help refine the assessment of PVR. Finally, more specific recommendations on quality-of-life assessments have been included, which have been targeted to specific clinical study designs. CONCLUSIONS: Acknowledging the dynamic and evolving nature of less-invasive aortic valve therapies, further refinements of clinical research processes are required. The adoption of these updated and newly proposed VARC-3 endpoints and definitions will ensure homogenous event reporting, accurate adjudication, and appropriate comparisons of clinical research studies involving devices and new therapeutic strategies.

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)0.366
metaresearch head score (Gemma)0.347
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Reporting · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.634
Threshold uncertainty score0.782

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3660.347
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0050.008
Bibliometrics0.0180.022
Science and technology studies0.0030.004
Scholarly communication0.0210.008
Open science0.0100.014
Research integrity0.0070.017
Insufficient payload (model declined to judge)0.0040.004

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 head0.537
GPT teacher head0.567
Teacher spread0.030 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designNot applicable
DomainReporting
GenreMethods

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

Citations840
Published2020
Admission routes2
Has abstractyes

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