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Record W2317071400 · doi:10.1583/13-4228.1

A Proof-of-Concept In Vitro Study to Determine if EndoAnchors Can Reduce Gutter Size in Chimney Graft Configurations

2013· article· en· W2317071400 on OpenAlexaff
Wouter W. Niepoth, Jorg L. de Bruin, Kak Khee Yeung, Rutger J. Lely, Andrea N. Devrome, Willem Wisselink, Jan D. Blankensteijn

Bibliographic record

VenueJournal of Endovascular Therapy · 2013
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsMedicineChimney (locomotive)AneurysmStentBalloonBiomedical engineeringAbdominal aortic aneurysmAortaRadiologyNuclear medicineSurgeryGeology

Abstract

fetched live from OpenAlex

PURPOSE: To investigate the feasibility of using endoanchor technology to reduce chimney graft-related gutter size in a juxtarenal aneurysm model. METHODS: In silicone juxtarenal aortic aneurysm models with two sizes of branch arteries and two sizes of aorta, single chimney graft (CG) configurations were constructed using 6-mm Atrium balloon-expandable stent-grafts in association with two sizes of Gore Excluder main grafts (23 and 28.5 mm). Configurations without Aptus EndoAnchors, with suprarenal placement of EndoAnchors, and with additional infrarenal placement of EndoAnchors were investigated. A total of 12 CG configurations were scanned using 64-slice computed tomography. Gutter volume and gutter areas at the top and bottom of the sealing zone were measured with image processing software. RESULTS: The combination of supra- and infrarenal placement of endoanchors led to a reduction in gutter volume compared to unanchored configurations. The same configurations also led to a decrease in gutter area at the bottom of the sealing zone. CONCLUSION: It is feasible to reduce gutters in CG configurations with the use of endoanchors in an in vitro juxtarenal aneurysm model.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.682

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.021
GPT teacher head0.289
Teacher spread0.268 · 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 designBench or experimental
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

Citations32
Published2013
Admission routes1
Has abstractyes

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