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Record W4406562466 · doi:10.1016/j.jvscit.2025.101741

Cadaveric training model for the management of type B aortic dissection using thoracic endovascular aortic repair along with the PETTICOAT technique

2025· article· en· W4406562466 on OpenAlexaff
Péter Osztrogonácz, Bahar Alasti, Rebecca Barnes, Alan B. Lumsden, Maham Rahimi

Bibliographic record

VenueJournal of Vascular Surgery Cases and Innovative Techniques · 2025
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsMcMaster University
FundersHouston Methodist Research InstituteHouston Methodist Hospital
KeywordsMedicineCadaveric spasmAortic dissectionDissection (medical)SurgeryAorta

Abstract

fetched live from OpenAlex

This model gives residents and fellows practice in the surgical repair of a type B aortic dissection using thoracic endovascular aortic repair implantation by the Provisional Extension To Induce Complete Attachment (PETTICOAT) technique. A human cadaveric model was created to simulate the procedure. A Dacron graft was pulled into the aorta distal to the left subclavian artery using two glidewires. Imaging confirmed the creation of a second lumen by the graft positioned within the aorta to simulate an aortic dissection. The PETTICOAT technique was then implemented with the implantation of a Cook Dissection stent. This proved the method to be a reproducible means to train residents and fellows in type B aortic dissection repair using the PETTICOAT technique.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.373

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.063
GPT teacher head0.333
Teacher spread0.271 · 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 designOther design
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

Citations2
Published2025
Admission routes1
Has abstractyes

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