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The ROVT Elan Valved Biplex Conduits for the Reconstruction of the Right Ventricular Outflow Tract

2016· article· en· W2336066466 on OpenAlexaff
Robert Guidoin, Yijun Fu, Bin Li, Nihal Weerasena, Jean‐Michel Bourget, R.W. Paynter, Xinxin Li, Jing Lin, Lu Wang, Boyin Qin, Randolph Guzman, Denis Desaulniers, Guy Dionne, Lucie Germain, Ze Zhang

Bibliographic record

VenueJournal of Long-Term Effects of Medical Implants · 2016
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsUniversity of ManitobaInstitut National de la Recherche ScientifiqueSt. Boniface HospitalUniversité Laval
Fundersnot available
KeywordsVentricular outflow tractElectrical conduitOutflowMedicineThrombusCardiologyEvent (particle physics)SurgeryIntensive care medicineInternal medicineEngineeringGeology

Abstract

fetched live from OpenAlex

The reconstruction of the right ventricular outflow tract (RVOT) system represents a considerable challenge for both manufacturers and surgeons because the patients requiring this type of devices have a very diverse set of anatomical challenges that can lead to complications and subsequent early device failures. We conducted an indepth investigation of a porcine-valve conduit explanted from a patient following an adverse event. A control device was analyzed as a reference. The rapid aging of the porcine valve in the right side of the heart together with major thrombus formation raises several questions. The difficulties encountered with materials used and also the design features of the conduits are once again highlighted. This group of patients continues to increase in number due to success in the surgical outcomes in early childhood. Therefore, there is a greater demand for an appropriate device. However, much work is still needed to achieve this goal, and the best approach to achieving success remains unanswered.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.305
Teacher spread0.291 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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Same venueJournal of Long-Term Effects of Medical ImplantsSame topicCongenital Heart Disease StudiesFrench-language works237,207