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Record W2136770925 · doi:10.1177/1089253207311789

Impact of Perioperative Transesophageal Echocardiography in Aortic Valve Replacement

2007· review· en· W2136770925 on OpenAlex
Baqir Qizilbash, Pierre Couture, André Denault

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.

Bibliographic record

VenueSeminars in Cardiothoracic and Vascular Anesthesia · 2007
Typereview
Languageen
FieldMedicine
TopicCardiac Valve Diseases and Treatments
Canadian institutionsUniversité de MontréalMontreal Heart Institute
Fundersnot available
KeywordsMedicineCardiopulmonary bypassPerioperativeAortic valve replacementHemodynamicsCardiologyVentricular outflow tractInternal medicineVentricular outflow tract obstructionProsthesisSurgeryMitral valveStenosis

Abstract

fetched live from OpenAlex

Intraoperative transesophageal echocardiography (TEE) is currently being used routinely during aortic valve replacement (AVR). TEE provides information that can lead to modifications of anesthetic and surgical care that leads to improved outcome. Numerous studies have shown that modifications in therapy occur from 10% to more than 40% of cases. The impact of TEE can be divided among modifications of therapy before, during, and after cardiopulmonary bypass. Before cardiopulmonary bypass, TEE can provide prognostic information, optimize hemodynamics, and diagnose conditions that were not appreciated before surgery, including patient-prosthesis mismatch. TEE can guide and modify the placement of various bypass cannulae. After bypass, TEE verifies the surgical result, rules out left and right ventricular outflow tract obstruction, and assures stable hemodynamics. Although current guidelines state that aortic valve surgery is a class IIa indication for TEE use, the authors' experience suggests that TEE should be routinely used in AVR.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.654
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.013
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 head0.025
GPT teacher head0.407
Teacher spread0.382 · 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