Accuracy of bedside sonographic measurement of optic nerve sheath diameter for intracranial hypertension diagnosis in the emergency department
Bibliographic record
Abstract
Ultrasound measurement of the optic nerve sheath diameter (US ONSD) has been proposed as a method to diagnose elevated intracranial pressure (EICP), but the optimal threshold is unclear. The aim of this study was to assess the accuracy of US ONSD, as compared to head computed tomography (CT), in detecting EICP of both traumatic and non-traumatic origin. We conducted a prospective, cross-sectional, multicenter study. Patients presenting to the emergency department with a suspect of traumatic or non-traumatic brain injury, referred for an urgent head CT, underwent US ONSD measurement. A US ONSD ≥5.5 mm was considered positive. Sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios were calculated for three ONSD cut-offs: 5.5 (primary outcome), 5.0, and 6.0 mm. A receiver operating characteristic (ROC) curve was also generated and the area under the ROC curve calculated. Ninetynine patients were enrolled. The CT was positive in 15% of cases and the US ONSD was positive in all of these, achieving a sensitivity of 100% [95% confidence interval (CI) 78; 100] and a negative predictive value of 100% (95% CI 79; 100). The CT was negative in 85% of cases, while the US ONSD was positive in 69% of these, achieving a specificity of 19% (95% CI 11; 29) and a positive predictive value of 18% (95% CI 11; 28). The US ONSD, with a 5.5 mm cut-off, might safely be used to rule out EICP in patients with traumatic and non-traumatic brain injury in the ED. In limited-resources contexts, a negative US ONSD could allow emergency physicians to rule out EICP in low-risk patients, deferring the head CT.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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".