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Prediction of Optimal Deployment Projection for Transcatheter Aortic Valve Replacement

2012· article· en· W2548740394 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueCirculation Cardiovascular Interventions · 2012
Typearticle
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsSt. Paul's Hospital
Fundersnot available
KeywordsMedicineProsthesisValve replacementAortic rootRadiologyAortic valveProjection (relational algebra)Regurgitation (circulation)Nuclear medicineCardiologySurgeryMathematicsAortaStenosisAlgorithm

Abstract

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BACKGROUND: Identifying the optimal fluoroscopic projection of the aortic valve is important for successful transcatheter aortic valve replacement (TAVR). Various imaging modalities, including multidetector computed tomography (MDCT), have been proposed for prediction of the optimal deployment projection. We evaluated a method that provides 3-dimensional angiographic reconstructions (3DA) of the aortic root for prediction of the optimal deployment angle and compared it with MDCT. METHODS AND RESULTS: Forty patients undergoing transfemoral TAVR at St Paul's Hospital, Vancouver, Canada, were evaluated. All underwent preimplant 3DA and 68% underwent preimplant MDCT. Three-dimensional angiographic reconstructions were generated from images of a C-arm rotational aortic root angiogram during breath-hold, rapid ventricular pacing, and injection of 32 mL contrast medium at 8 mL/s. Two independent operators prospectively predicted perpendicular valve projections. The implant angle was chosen at the discretion of the physician performing TAVR. The angles from 3DA, from MDCT, the implant angle, and the postdeployment perpendicular prosthesis view were compared. The shortest distance from the postdeployment perpendicular prosthesis projection to the regression line of predicted perpendicular projections was calculated. All but 1 patient had adequate image quality for reproducible angle predictions. There was a significant correlation between 3DA and MDCT for prediction of perpendicular valve projections (r=0.682, P<0.001). Deviation from the regression line of predicted angles to the postdeployment prosthesis view was 5.1±4.6° for 3DA and 7.9±4.9° for MDCT (P=0.01). CONCLUSIONS: Three-dimensional angiographic reconstructions and MDCT are safe, practical, and accurate imaging modalities for identifying the optimal perpendicular valve deployment projection during TAVR.

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.

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 categoriesMeta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.017
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 head0.064
GPT teacher head0.348
Teacher spread0.284 · 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