Diagnostic Accuracy of Point-of-Care Ultrasound for Acute Pediatric Ankle Injuries
Bibliographic record
Abstract
OBJECTIVES: The aim of this study was to determine test performance characteristics of point-of-care ultrasound (POCUS) in the diagnosis of pediatric ankle fractures compared with ankle x-rays. Secondary objectives were to determine if POCUS can reduce the number of x-rays, analyze diagnostic errors, compare the Ottawa Ankle Rules (OAR) with POCUS, and determine if the outcome of the ultrasound results is affected by the musculoskeletal ultrasound experience of the pediatric emergency physicians. METHODS: This was a prospective study of children aged 6 to 18 years who presented to the emergency department with ankle injuries with no prior x-rays. The physicians received a 2-hour training session, performed an ultrasound with a standardized protocol, and documented the POCUS results as positive or negative for fracture. The reference standard was the radiologist's x-ray interpretation. RESULTS: We enrolled 118 patients with a median age of 12 years (interquartile range, 10 to 14 years). There were 17 fractures among 15 patients; 8 were clinically significant. Overall, POCUS would reduce x-rays by 105 (89%), but miss 6 fractures, including 1 clinically significant fracture. For detecting all ankle fractures, POCUS yielded a sensitivity of 60% (95% CI, 32.3-83.7), a specificity of 96% (95% CI, 90.4-98.9), a positive predictive value of 69.2 (95% CI, 44.2-86.5), and a negative predictive value of 94.3 (95% CI, 89.9-96.9). For the detection of clinically significant fractures, POCUS yielded a sensitivity of 87.5% (95% CI, 47.4-99.7), a specificity of 94.6% (95% CI, 88.5-97.9), a positive predictive value of 53.9 (95% CI, 33.9-72.6), and a negative predictive value of 99.1 (95% CI, 94.3-99.9). The sensitivity of POCUS + OAR and OAR alone was 90% (95% CI, 55.5-99.8), but the specificity was 0% (95% CI not computed). CONCLUSIONS: POCUS alone or combined with OAR is an inadequate screening tool to detect pediatric ankle fractures.
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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 | 0.005 | 0.061 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".