Diagnostic utility of point-of-care ultrasound and optical coherence tomography for papilloedema in children: a prospective pilot study
Bibliographic record
Abstract
BACKGROUND/AIMS: Papilloedema is an important sign of serious neurological disease, but it can be difficult to detect on funduscopy. The purpose of this study was to determine the diagnostic accuracy of point-of-care ultrasound (POCUS) and optical coherence tomography (OCT) for detecting papilloedema in children. METHODS: This was a prospective observational study at a tertiary care paediatric hospital. Patients were eligible for the study if they underwent a lumbar puncture with opening pressure and had high-quality POCUS and OCT imaging. RESULTS: A total of 63 eyes from 32 patients were included in the study, 41 (65%) with papilloedema and 22 (35%) without. There were statistically significant differences between the groups in the optic disc elevation (ODE) (p<0.001) and optic nerve sheath diameter (ONSD) (p<0.001) on POCUS, and in the average retinal nerve fibre layer (rNFL) thickness on OCT (p<0.001). Average rNFL thickness had the highest diagnostic accuracy with an area under the curve (AUC) of 0.999 and a 100% sensitivity and 95% specificity for papilloedema (threshold value of ≥108 µm). ODE had an AUC of 0.866 and a 93% sensitivity and 55% specificity (threshold value of ≥0.5 mm). ONSD had an AUC of 0.786 and a 93% sensitivity and 45% specificity (threshold value of ≥5.5 mm). CONCLUSION: Both OCT and POCUS are potentially useful tools to help diagnose papilloedema in children. Larger studies are needed to further define the role and accuracy of POCUS and OCT in assessing papilloedema in children.
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.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".