Evaluation of a Novel Point-of-Care Ultrasound Curriculum for First-Year Pediatric Residents
Bibliographic record
Abstract
OBJECTIVE: The aim of the study is to evaluate a novel point-of-care ultrasound (POCUS) educational curriculum for pediatric residents. METHODS: The cohort study in graduate medical education was completed from January 2017 to March 2019. Postgraduate year 1 (PGY1) pediatric residents attended the educational curriculum that consisted of 3 half-day sessions over a 3-month period. Each session consisted of a lecture (introduction, extended focused assessment with sonography for trauma, soft tissue/musculoskeletal, cardiac, and resuscitative applications) followed by supervised hands-on scanning sessions. Group ratio was 3 learners to 1 machine/expert instructor. Main outcome measures included pre- and post-written test scores, as well as objective structured clinical examination (OSCE) scores. RESULTS: Forty-nine PGY1 residents (78% women) completed the curriculum. The mean (SD) pretest score was 68% (8.5), and the mean posttest score was 83% (8.3) with a difference of 15 (95% confidence interval, 12.5-17.6; P < 0.001). Mean (SD) focused assessment with sonography for trauma OSCE score after the curriculum was 88.7% (11.9). The number of PGY1 pediatric residents that were comfortable performing POCUS examinations increased from pretraining to posttraining for soft tissue/musculoskeletal (14%-61%, P < 0.001), extended focused assessment with sonography for trauma (24%-90%, P < 0.001), and cardiac (18%-86%, P < 0.001). All participants found the curriculum useful, and 42 of 49 (86%) stated the curriculum increased their ability to acquire and interpret images. CONCLUSIONS: Postgraduate year 1 pediatric residents learned the basics of POCUS through 3 brief educational sessions. The increase in posttest scores demonstrated improved POCUS knowledge, and the high OSCE score demonstrated their ability to acquire ultrasound images. Point-of-care ultrasound guidelines are needed for pediatric residency programs.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".