Brain Point of Care Ultrasound in Young Children Receiving Computed Tomography in the Emergency Department: A Proof of Concept Study
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 (POCUS) is an important tool in pediatric emergency medicine. In neonatal intensive care medicine ultrasound is often used to evaluate the brains of sick neonates. In theory, POCUS could be used in the ED in young children to evaluate the brain for abnormal pathology. Objectives: To examine the ability of PEM faculty to use brain POCUS to identify clinically significant brain injuries in children with head injuries and/or abnormal neurological exams, and generate sensitivity and specificity of brain POCUS in assessing such findings. Methods: This study used a convenience sample of patients seen in a tertiary care pediatric centre who required a CT head. A team of physicians who were trained at a workshop for brain POCUS were on call to perform the POCUS while being blinded to the results of the CT. Results: 21 children were enrolled in the study. Five (24%) of the patients had a CT that was positive for intracranial bleeds. Of the 5 patients with a positive CT, 3 had a brain POCUS scan that was also positive. The two false negative brain POCUS scans were on patients with small bleeds (no surgical intervention required) on CT, as reported by radiology. The sensitivity of brain POCUS was 60% (CI 15% - 95%) with a specificity of 94% (CI 70%-100%). The diagnostic accuracy of brain POCUS was 86% (CI 64% - 97%). Conclusion: This small proof of concept study shows that brain POCUS is an imaging modality with reasonable sensitivity and specificity in identifying intracranial pathologies that are present on CT. Its use may be most beneficial to expedite definitive imaging and subspeciality involvement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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