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Record W3187779196 · doi:10.1177/15266028211038592

Percutaneous Treatment of Concomitant Severe Aortic Stenosis and Thoracoabdominal Aortic Aneurysm

2021· article· en· W3187779196 on OpenAlexaff
Ariane-Sophie Painchaud-Bouchard, Jeannot Potvin, Jessica Forcillo, Ricardo Ruz, Stéphane Elkouri

Bibliographic record

VenueJournal of Endovascular Therapy · 2021
Typearticle
Languageen
FieldMedicine
TopicAortic Disease and Treatment Approaches
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversité de Montréal
Fundersnot available
KeywordsMedicineStenosisPercutaneousSurgeryRadiologyAortic aneurysmConcomitantAneurysmThoracic aortic aneurysm

Abstract

fetched live from OpenAlex

PURPOSE: Although rare in occurrence, symptomatic severe aortic stenosis and large thoracoabdominal aortic aneurysm (TAAA) found in combination pose a real therapeutic challenge, especially in elderly frail patients. Surgical approaches for combined treatment are complex and at high risk of complications while staged procedures carry the risk of an unfavorable evolution of the condition temporarily left untreated. Minimally invasive approaches may therefore prove a more suitable strategy for these patients. CASE REPORT: We present the case of a 78-year-old woman with symptomatic severe aortic stenosis (AS) and a TAAA of 7.8 cm in diameter. Transcatheter treatment of both conditions was successfully performed in a staged manner. The first intervention consisted of combined transfemoral transcatheter aortic valve implantation (TAVI) immediately followed by a zone 3 thoracic endovascular aortic endoprosthesis deployment. In order to reduce the extent of intercostal arteries coverage and mitigate the risk of medullar ischemia, a second-stage percutaneous endovascular treatment of the TAAA was performed with a customized 4-fenestration prosthesis. Early and 12-month clinical and radiologic follow-up were favorable. CONCLUSION: This case demonstrates how a strong multidisciplinary collaboration allows for successful resolution of complex clinical scenarios.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.403
Threshold uncertainty score0.566

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.030
GPT teacher head0.282
Teacher spread0.252 · 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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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