The Adequacy of Basic Intraoperative Transesophageal Echocardiography Performed by Experienced Anesthesiologists
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.
Bibliographic record
Abstract
UNLABELLED: Transesophageal echocardiography (TEE) may improve intraoperative decision-making and patient outcome if it is performed and interpreted correctly. After revising our TEE examination to fulfill the published guidelines for basic TEE practitioners, we prospectively evaluated the ability of our cardiac anesthesiologists (all very experienced with TEE) to record and interpret this revised examination. Educational aids and regular TEE performance feedback were provided to the anesthesiologists. Their interpretations were compared with the independently determined results of experts. Compared with their own historical controls (42% recording rate), all anesthesiologists showed significant improvement in their ability to record a basic intraoperative TEE examination resulting in 81% (P < 0.0001) of all required images being recorded: 88% before cardiopulmonary bypass, 77% immediately after bypass, and 64% after chest closure. Seventy-nine percent of the images recorded at baseline were correctly interpreted, 6% were incorrectly interpreted, and 15% were not evaluated. Our attempt to assess compliance with published guidelines for basic intraoperative TEE resulted in a marked improvement in our intraoperative TEE practice. Most, but not all, standard cross-sections are recorded or interpreted correctly, even by highly experienced and motivated practitioners. IMPLICATIONS: Experienced cardiac anesthesiologists can obtain and correctly interpret most basic intraoperative transesophageal echocardiograms.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it