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Record W2125239069 · doi:10.1586/14779072.2015.1096778

Reducing periprocedural complications in transcatheter aortic valve replacement: review of paravalvular leaks, stroke and vascular complications

2015· review· en· W2125239069 on OpenAlexaff
Jean‐Michel Paradis, Omar Abdul‐Jawad Altisent, Josep Rodés‐Cabau

Bibliographic record

VenueExpert Review of Cardiovascular Therapy · 2015
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsMontreal Heart Institute
Fundersnot available
KeywordsMedicineValve replacementStenosisStroke (engine)CardiologyStandard of careSurgeryAortic valve stenosisAortic valve replacementInternal medicine

Abstract

fetched live from OpenAlex

Transcatheter aortic valve replacement has been established as the standard of care for inoperable patients and a valid alternative for high-risk individuals with severe symptomatic native aortic stenosis. Over the last decade, substantial improvement has been made in the transcatheter technology. Nevertheless, this less-invasive procedure is still associated with complications like paravalvular leaks, strokes and vascular complications. This review article discusses these worrisome complications associated with transcatheter aortic valve replacement and proposes methods to prevent these hurdles.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.398
Teacher spread0.349 · 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 designSystematic review
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

Citations1
Published2015
Admission routes1
Has abstractyes

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