Impact of Perioperative Transesophageal Echocardiography in Aortic Valve Replacement
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".