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Record W2921772573 · doi:10.1016/j.jacc.2018.12.056

Detection and Prediction of Bioprosthetic Aortic Valve Degeneration

2019· article· en· W2921772573 on OpenAlexaff
Timothy Cartlidge, Mhairi Doris, Stephanie Sellers, Tania Pawade, Audrey White, Renzo Pessotto, Jacek Kwieciński, Alison Fletcher, Carlos Alcaide, Christophe Lucatelli, Cameron G. Densem, James H.F. Rudd, Edwin J.R. van Beek, Adriana Tavares, Renu Virmani, Daniel S. Berman, Jonathon Leipsic, David E. Newby, Marc R. Dweck

Bibliographic record

VenueJournal of the American College of Cardiology · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersNIHR Cambridge Biomedical Research CentreEngineering and Physical Sciences Research CouncilNational Institute for Health and Care ResearchBritish Heart FoundationWellcome Trust
KeywordsMedicineInterquartile rangePositron emission tomographyDegeneration (medical)CardiologyEx vivoFluorideAortic valveInternal medicineRadiologyIn vivoSurgeryPathology

Abstract

fetched live from OpenAlex

Bioprosthetic aortic valve degeneration is increasingly common, often unheralded, and can have catastrophic consequences. The authors sought to assess whether 18F-fluoride positron emission tomography (PET)-computed tomography (CT) can detect bioprosthetic aortic valve degeneration and predict valve dysfunction. Explanted degenerate bioprosthetic valves were examined ex vivo. Patients with bioprosthetic aortic valves were recruited into 2 cohorts with and without prosthetic valve dysfunction and underwent in vivo contrast-enhanced CT angiography, 18F-fluoride PET, and serial echocardiography during 2 years of follow-up. All ex vivo, degenerate bioprosthetic valves displayed 18F-fluoride PET uptake that colocalized with tissue degeneration on histology. In 71 patients without known bioprosthesis dysfunction, 14 had abnormal leaflet pathology on CT, and 24 demonstrated 18F-fluoride PET uptake (target-to-background ratio 1.55 [interquartile range (IQR): 1.44 to 1.88]). Patients with increased 18F-fluoride uptake exhibited more rapid deterioration in valve function compared with those without (annualized change in peak transvalvular velocity 0.30 [IQR: 0.13 to 0.61] vs. 0.01 [IQR: −0.05 to 0.16] ms−1/year; p < 0.001). Indeed 18F-fluoride uptake correlated with deterioration in all the conventional echocardiographic measures of valve function assessed (e.g., change in peak velocity, r = 0.72; p < 0.001). Each of the 10 patients who developed new overt bioprosthesis dysfunction during follow-up had evidence of 18F-fluoride uptake at baseline (target-to-background ratio 1.89 [IQR: 1.46 to 2.59]). On multivariable analysis, 18F-fluoride uptake was the only independent predictor of future bioprosthetic dysfunction. 18F-fluoride PET-CT identifies subclinical bioprosthetic valve degeneration, providing powerful prediction of subsequent valvular dysfunction and highlighting patients at risk of valve failure. This technique holds major promise in the diagnosis of valvular degeneration and the surveillance of patients with bioprosthetic valves. (18F-Fluoride Assessment of Aortic Bioprosthesis Durability and Outcome [18F-FAABULOUS]; NCT02304276)

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.007
GPT teacher head0.269
Teacher spread0.262 · 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
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

Citations163
Published2019
Admission routes1
Has abstractyes

Explore more

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