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Record W2947882626 · doi:10.1002/ccd.28347

Fracture of small Mitroflow® aortic bioprosthesis following valve‐in‐valve transcatheter aortic valve replacement with ACURATE neo valve—From bench testing to clinical practice

2019· article· en· W2947882626 on OpenAlexaff
Ignacio J. Amat‐Santos, Hipólito Gutiérrez, Janarthanan Sathananthan, John G. Webb

Bibliographic record

VenueCatheterization and Cardiovascular Interventions · 2019
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineAortic valveBalloonCardiologySurgeryAortic valve replacementValve replacementInternal medicineStenosis

Abstract

fetched live from OpenAlex

Valve-in-valve (ViV) transcatheter procedures have emerged as a feasible, less-invasive treatment option for bioprosthetic structural valve deterioration. However, in the presence of a small bioprosthesis, a significant residual gradient after ViV procedures often occurs and has been associated with poorer clinical outcomes. We report the use of the self-expandable supra-annular ACURATE neo™ valve to treat degenerated Mitroflow (Sorin) aortic bioprosthesis with severe residual elevated gradients followed by valve fracture with a postdilation using a noncompliant balloon leading to significant reduction in residual gradients. In conclusion, the use of ACURATE neo™ valve followed by the controlled fracture of the surgical bioprosthesis frame with a noncompliant balloon is a safe and effective approach for patients with Mitroflow® failing valves and residual elevated gradient after transcatheter aortic valve replacement.

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)0.000
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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.032
GPT teacher head0.344
Teacher spread0.312 · 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 designCase report
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

Citations3
Published2019
Admission routes1
Has abstractyes

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