MétaCan
Menu
Back to cohort
Record W4387865268 · doi:10.1080/14779072.2023.2271395

Managing the challenge of a small aortic annulus in patients with severe aortic stenosis

2023· article· en· W4387865268 on OpenAlexaff
Alicia Prieto-Lobato, Jorge Nuche, Marisa Avvedimento, Jean‐Michel Paradis, Éric Dumont, D. Kalavrouziotis, Siamak Mohammadi, Josep Rodés‐Cabau

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsMedicineCardiac skeletonStenosisCardiologyAortic valve replacementAortic valve stenosisRadiologyValve replacementMultidetector computed tomographyInternal medicineAortic valveSurgeryComputed tomography

Abstract

fetched live from OpenAlex

INTRODUCTION: Small aortic annulus (SAA) poses a challenge in the management of patients with severe aortic stenosis requiring aortic valve replacement - both surgical and transcatheter - since it has been associated with worse clinical outcomes. AREAS COVERED: This review aims to comprehensively summarize the available evidence regarding the management of aortic stenosis in patients with SAA and discuss the current controversies as well as future perspectives in this field. EXPERT OPINION: It is paramount to agree in a common definition for diagnosing and properly treating SAA patients, and for that purpose, multidetector computer tomography is essential. The results of recent trials led to the expansion of transcatheter aortic valve replacement among patients of all the surgical-risk spectrum, and the choice of treatment (transcatheter, surgical) should be based on patient comorbidities, anatomical characteristics, and patient preferences.

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)0.003
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.018
GPT teacher head0.301
Teacher spread0.283 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueExpert Review of Cardiovascular TherapySame topicCardiac Valve Diseases and TreatmentsFrench-language works237,207