Development and Validation of an Assessment Tool for Competency in Critical Care Ultrasound
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
BACKGROUND: Point-of-care ultrasound is an emerging technology in critical care medicine. Despite requirements for critical care medicine fellowship programs to demonstrate knowledge and competency in point-of-care ultrasound, tools to guide competency-based training are lacking. OBJECTIVE: We describe the development and validity arguments of a competency assessment tool for critical care ultrasound. METHODS: A modified Delphi method was used to develop behaviorally anchored checklists for 2 ultrasound applications: "Perform deep venous thrombosis study (DVT)" and "Qualify left ventricular function using parasternal long axis and parasternal short axis views (Echo)." One live rater and 1 video rater evaluated performance of 28 fellows. A second video rater evaluated a subset of 10 fellows. Validity evidence for content, response process, and internal consistency was assessed. RESULTS: An expert panel finalized checklists after 2 rounds of a modified Delphi method. The DVT checklist consisted of 13 items, including 1.00 global rating step (GRS). The Echo checklist consisted of 14 items, and included 1.00 GRS for each of 2 views. Interrater reliability evaluated with a Cohen kappa between the live and video rater was 1.00 for the DVT GRS, 0.44 for the PSLA GRS, and 0.58 for the PSSA GRS. Cronbach α was 0.85 for DVT and 0.92 for Echo. CONCLUSIONS: The findings offer preliminary evidence for the validity of competency assessment tools for 2 applications of critical care ultrasound and data on live versus video raters.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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