Sonographic Assessment of the Optic Nerve Sheath in Giant Cell Arteritis (SONIC-GCA): protocol for a prospective, multicentre diagnostic test accuracy study
Bibliographic record
Abstract
Introduction Giant cell arteritis (GCA) is a vision-threatening systemic vasculitis for which no universally accessible diagnostic tool exists. Optic nerve sheath diameter (ONSD), measurable via ultrasound, has emerged as a promising, non-invasive biomarker of cranial GCA. The Sonographic Assessment of the Optic Nerve Sheath in Giant Cell Arteritis (SONIC-GCA) aims to validate ONSD ultrasound as a diagnostic and monitoring tool in GCA. Methods and analysis SONIC-GCA is a prospective, multicentre study enrolling patients referred for the evaluation of suspected GCA. A total of 285 participants will undergo optic nerve sheath ultrasound and digital retinal funduscopy, followed by a standardised GCA assessment. All participants will be followed for a minimum of 6 months, at which time an external adjudication committee will confirm the diagnosis of GCA. Those diagnosed with GCA will be followed for 2 years, with repeated optic nerve sheath ultrasound and digital retinal funduscopy at months 3, 6, 12, 18, 24 and at relapse, if applicable. The primary outcome is the diagnostic accuracy of ONSD to detect GCA, which will be evaluated using receiver operating characteristic curve analysis, with adjudicated GCA status serving as the reference standard. Secondary outcomes will address several complementary domains: its value for relapse monitoring will be assessed through time-dependent Cox proportional hazards models, examining whether baseline or longitudinal ONSD predicts relapse risk; intraobserver and interobserver reliability will be determined using intraclass correlation coefficients, providing quantitative estimates of measurement reproducibility; and its association with retinal findings will be evaluated by correlating ONSD measurements with ocular imaging and clinical retinal outcomes. Together, these analyses will comprehensively determine the diagnostic, prognostic and operational utility of ONSD in GCA. Ethics and dissemination The study has been peer-reviewed by the scientific committee and approved by the CIUSSS du Nord-de-l’Île-de-Montréal Research Ethics Board. Each participating site will obtain local ethics approval prior to enrolment. All participants will provide informed consent. Results will be disseminated through peer-reviewed publications, conference presentations and webinars. Trial registration number NCT05749094 .
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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 | 0.081 | 0.063 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.030 | 0.009 |
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".