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Record W2939348117

Transcatheter Edge-to-edge Repair of Severe Tricuspid Regurgitation

2018· article· en· W2939348117 on OpenAlexaff
Shu-I Lin, Mizuki Miura, Francesco Maisano, Michel Züber, Mara Gavazzoni, Edwin Ho, Alberto Pozzoli, Maurizio Taramasso

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2018
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsRegurgitation (circulation)MedicineCardiologyEnhanced Data Rates for GSM EvolutionInternal medicineComputer scienceArtificial intelligence
DOInot available

Abstract

fetched live from OpenAlex

Despite the increasing knowledge of the long-term adverse consequence of severe tricuspid regurgitation (TR), most patients with moderate-to-severe TR are still treated conservatively because of the high risk of surgery. Percutaneous procedures have emerged as an attractive alternative treatment. Transcatheter edge-to-edge repair is a validated technique to treat mitral regurgitation. In recent years, the same concept has been applied to patients with TR and prohibitive operative risk. Early trials have shown feasibility and safety. More clinical experiences and long-term results are still being gathered. In this article, we provide an overview of transcatheter edge-to-edge repair and look at the current evidence and clinical results regarding procedure.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.103
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.323
Teacher spread0.305 · 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 teacher head, 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

Citations0
Published2018
Admission routes1
Has abstractyes

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