Acquisition and retention of lung ultrasound skills by respiratory therapists: A curriculum for respiratory therapists
Bibliographic record
Abstract
Purpose: Lung point-of-care ultrasound (POCUS) is a versatile bedside tool. The utility of POCUS has grown during the coronavirus disease 2019 pandemic, as it allows clinicians to obtain real-time images without requiring transport of the patient outside the intensive care unit. As respiratory therapists (RTs) are involved in caring for those with respiratory failure, there is a good rationale for their adoption of lung ultrasound. However, no training standards have been defined. Our objective was to develop and implement a training programme for RTs to achieve and sustain competence in lung ultrasound. Methods: This was a single-centre, prospective, single-cohort observational study. A total of 10 RTs completed our curriculum and were tasked with independently completing and interpreting 10 initial lung ultrasound exams and 3 subsequent exams after a 6-week interim period. All exams were blindly overread by a local expert in lung ultrasound. Results: After completing the curriculum, RTs were able to acquire and accurately interpret their images over 85% of the time. They were more successful in the upper lung zone image acquisition and interpretation compared with the lower lung zones. After 6 weeks, the RTs' lung POCUS skills remained stable, and their lower lung zone image interpretation improved. The RTs reported that their confidence improved throughout the study. Conclusion: The RTs in our study have demonstrated competence in acquisition and interpretation of upper lung zone images. They have also reported confidence in acquiring and interpreting upper lung zone images. More experience appears to be required to gain competence and confidence in lower lung zone ultrasound. Next steps would be to repeat the present study with a higher number of RTs completing at least 20 lung POCUS studies.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".