Defining the learning curve of point-of-care ultrasound for confirming endotracheal tube placement by emergency physicians
Bibliographic record
Abstract
BACKGROUND: Unrecognized esophageal intubations are associated with significant patient morbidity and mortality. No single confirmatory device has been shown to be 100 % accurate at ruling out esophageal intubations in the emergency department. Recent studies have demonstrated that point-of-care ultrasound (POCUS) may be a useful adjunct for confirming endotracheal tube placement; however, the amount of practice required to become proficient at this technique is unclear. The purpose of this study is to determine the amount of practice required by emergency physicians to become proficient at interpreting ultrasound video clips of esophageal and endotracheal intubations. METHODS: Emergency physicians and emergency medicine residents completed a baseline interpretation test followed by a 10 min online tutorial. They then interpreted POCUS clips of esophageal and endotracheal intubations in a randomly selected order. If an incorrect response was provided, the participant completed another practice session with feedback. This process continued until they correctly interpreted ten consecutive ultrasound clips. Descriptive statistics were used to summarize the data. RESULTS: Of the 87 eligible physicians, 66 (75.9 %) completed the study. The mean score on the baseline test was 42.9 % (SD 32.7 %). After the tutorial, 90.9 % (60/66) of the participants achieved proficiency after one practice attempt and 100 % achieved proficiency after two practice attempts. Six intubation ultrasound clips were misinterpreted, for a total error rate of 0.9 % (6/684). Overall, the participants had a sensitivity of 98.3 % (95 % CI 96.3-99.4 %) and specificity of 100 % (95 % CI 98.9-100 %) for detecting correct tube location. Scans were interpreted within an average of 4 s (SD 2.9 s) of the intubation. CONCLUSIONS: After a brief online tutorial and only two practice attempts, emergency physicians were able to quickly and accurately interpret ultrasound intubation clips of esophageal and endotracheal intubations.
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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 | 0.011 | 0.147 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| 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".