Quantification of Optic Nerve and Sheath Diameter by Transorbital Sonography: A Systematic Review and Metanalysis
Bibliographic record
Abstract
ABSTRACT BACKGROUND AND PURPOSE To date, normal values for optic nerve diameter (OND) and optic nerve sheath diameter (ONSD) for transorbital sonography (TOS) have only been reported by individual small‐scale studies, exposing a great variability in the measurement of the OND and ONSD. METHODS We performed a systematic review and metanalysis of available to date studies on TOS evaluation of adults without elevated intracranial pressure to provide an overview of the published literature, measuring methods and further specify normal values for OND and ONSD. RESULTS In total, we included 39 studies with 2,927 healthy volunteers (mean age 36.1 years, 44.4% female), so that a total of 5,854 eyes were examined. All pooled analyses were based on random effect models. Mean values for OND were provided in 13 studies. Calculated mean pooled OND value was 3.08 mm (95% confidence interval [CI], 2.9‐3.25), with low heterogeneity across studies (I2= 12.7%). Thirty‐four studies provided mean values for ONSD measurement. The pool of mean ONSD measurements was 4.78 mm (95% CI, 4.63‐4.94), with evidence of substantial heterogeneity between estimates ONSD (I2= 50.6%). There were no significant differences (P= .139) in the subsequent subgroup analysis for the different geographic continents. Also, no significant differences could be recorded for the effect of age (P= .824) or gender (P= .093). CONCLUSIONS TOS is a frequently described and widely used method. We provide reference values of OND and ONSD that are based on metanalytical analysis. Different measuring methods of ONSD result in higher heterogeneity. Subgroup analysis revealed no significant correlation between ONSD and age, gender, or geographic origin.
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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 | 0.014 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.025 |
| Bibliometrics | 0.010 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".