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Record W4285089916 · doi:10.3390/jcdd9070223

TAVR for All? The Surgical Perspective

2022· review· en· W4285089916 on OpenAlexaff
Xiling Zhang, Thomas Puehler, Derk Frank, Janarthanan Sathananthan, Stephanie Sellers, David Meier, Marcus Both, Philipp Blanke, Hatim Seoudy, Mohammed Saad, Oliver J. Müller, Lars Søndergaard, Georg Lutter

Bibliographic record

VenueJournal of Cardiovascular Development and Disease · 2022
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsVancouver General HospitalSt. Paul's HospitalUniversity of British ColumbiaProvidence Health Care
FundersDeutsches Zentrum für Herz-Kreislaufforschung
KeywordsMedicineValve replacementRegurgitation (circulation)Bicuspid aortic valveCardiologyMitral regurgitationCoronary artery diseaseInternal medicineConcomitantSurgeryAortic valveStenosis

Abstract

fetched live from OpenAlex

In spite of the noninferiority of transcatheter aortic valve replacement (TAVR) in high- and intermediate-risk patients, there are still obstacles that need to be overcome before the procedure is further expanded and clinically integrated. The lack of evidence on the long-term durability of the bioprostheses used for TAVR remains of particular concern. In addition, surgery may be preferred over TAVR in patients with bicuspid aortic valve (BAV) or with concomitant pathologies such as other valve diseases (mitral regurgitation/tricuspid regurgitation), aortopathy, and coronary artery disease. In this review, we discuss and summarize relevant data from clinical trials, current trends, and remaining obstacles, and provide our perspective on the indications for the expansion of TAVR.

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)0.001
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0050.002

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 head0.050
GPT teacher head0.372
Teacher spread0.322 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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