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Record W2139846541 · doi:10.1016/j.euje.2007.05.007

Images in cardiovascular medicine: Prosthetic aortic valve and conduit dehiscence with large periconduit cavity, ascending aortic aneurysm and severe mitral regurgitation

2007· article· en· W2139846541 on OpenAlexaff
Emma Ivens, Christopher Thompson, Richard B. Moss, Brad Munt, Hilton Ling

Bibliographic record

VenueEuropean Journal of Echocardiography · 2007
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineDehiscenceRegurgitation (circulation)CardiologyCardiac skeletonMitral regurgitationMitral valveInternal medicineAneurysmAortic valveAscending aortaMitral valve replacementAortic valve replacementSurgeryAortaStenosis

Abstract

fetched live from OpenAlex

Prosthetic aortic valve and conduit dehiscence with periconduit cavity and ascending aortic aneurysm is an uncommon complication of aortic root surgery. It is usually recognizable at echocardiography due to an abnormal position of the prosthetic valve and conduit in relation to the native aortic annulus in conjunction with an abnormal echolucent periconduit space that fills with color flow. Mitral regurgitation is an unusual complication of this condition. We present a patient with severe mitral regurgitation secondary to prosthetic aortic valve and conduit dehiscence with a large periconduit cavity and aneurysm of the intervalvular fibrosa. The mechanism of mitral regurgitation is secondary to functional involvement of the anterior mitral valve leaflet and intervalvular fibrosa with anterior mitral leaflet restriction in conjunction with mild left ventricular remodeling. Significant mitral regurgitation persisted post resection of the periconduit cavity and aortic valve replacement, requiring mitral valve replacement. This case study reports a new mechanism of mitral regurgitation in the setting of prosthetic aortic valve and conduit dehiscence.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.844

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.010
GPT teacher head0.276
Teacher spread0.267 · 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

Citations4
Published2007
Admission routes1
Has abstractyes

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