Optic Nerve Sheath Measurement on Ultrasound: A Novel Diagnostic Test for Giant Cell Arteritis
Bibliographic record
Abstract
OBJECTIVE: Optic nerve sheath enhancement on magnetic resonance imaging has been reported in patients with giant cell arteritis (GCA), with or without visual manifestations. Whether similar findings can be documented on ultrasound is unknown. Optic nerve ultrasound is a point-of-care, easy to learn, rapid, and noninvasive technique. This study aims to investigate whether optic nerve sheath diameter (ONSD) measured on ultrasound is useful in the diagnosis of active, new-onset GCA. METHODS: A single-center, diagnostic accuracy study was performed from June to November 2022 on consecutive eligible patients referred for suspected GCA. Optic nerve ultrasound was performed on both eyes. The ONSD (includes the optic nerve and its sheath) and optic nerve diameter (OND) were measured 3 mm behind the ocular globe. The presence or absence of GCA was confirmed clinically 6 months later. Multivariable linear regression, adjusting for age and sex, was used to determine the association between optic nerve ultrasound measures and final GCA diagnosis. RESULTS: Thirty participants were enrolled, including nine participants with a final diagnosis of GCA. Mean ± SD ONSD was 5.98 ± 1.17 mm in patients with GCA and 4.02 ± 0.99 mm in patients without GCA. Mean ONSD was greater by 1.26 mm in patients with GCA (95% confidence interval 0.30-2.21 mm, P = 0.01) compared with those without GCA, adjusting for age and sex. Mean ± SD OND was 2.97 ± 0.46 mm in patients with GCA and 2.47 ± 0.58 mm in patients without GCA. There was no evidence of an association between GCA diagnosis and OND. CONCLUSION: Patients with GCA had a significantly greater ONSD on ultrasound than patients without GCA. Optic nerve ultrasound may represent a novel, rapid, bedside diagnostic test for GCA. A large prospective study is required to confirm these findings and evaluate whether ONSD can be used as a disease activity biomarker in GCA.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 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".