Utilization of intraoperative transesophageal echocardiography during repair of congenital cardiac defects: A survey of north american centers
Bibliographic record
Abstract
BACKGROUND: Intraoperative transesophageal echocardiography (TEE) has been increasingly utilized during repair of congenital cardiac defects. HYPOTHESIS: The aim of this study was to assess the practice of TEE in this setting. METHODS: A survey was sent to 70 centers in the United States and Canada; replies were obtained from 65 centers (93%). Responses were grouped into four categories: (1) Performance of intraoperative echocardiography, (2) performance practices, (3) equipment and probe issues, (4) billing and reimbursement. Data were available from all responding centers unless specified below. RESULTS: All responding centers employed intraoperative echocardiography, with 98% employing TEE. All responding centers employed intraoperative echocardiography. The majority of centers (72%) utilized intraoperative echocardiography in all cases or all open cases except atrial septal defects, while the remainder employed it selectively. The average duration of TEE experience at responding centers was 6.1 years. Transesophageal echocardiography was primarily the responsibility of cardiologists, with most centers having individuals meeting published TEE training guidelines. The large majority of centers performed both pre- and postbypass TEE studies. Equipment and probes were widely available. All centers disinfected the TEE probe between studies, but for longer times than recommended. CONCLUSION: Utilization of intraoperative TEE during surgery for congenital heart disease is widespread; the results of this survey may be useful to individual institutions as they evaluate their utilization of intraoperative echocardiography.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".