Cross‐sectional area reference values for peripheral nerve ultrasound in adults: a systematic review and meta‐analysis—Part I: Upper extremity nerves
Bibliographic record
Abstract
Abstract Background and purpose Measurement of the cross‐sectional area (CSA) of peripheral nerves using ultrasound is useful in the evaluation of focal lesions like entrapment syndromes and inflammatory polyneuropathies. Here, a systematic review and meta‐analysis of published CSA reference values for upper extremity nerves was performed. Methods Available to date nerve ultrasound studies on healthy adults were included and a meta‐analysis for CSA was provided of the following nerves: median nerve at the wrist, forearm, upper arm; ulnar nerve at the Guyon's canal, forearm, elbow, upper arm; radial nerve at the upper arm. Regression and correlation analyses for age, gender, height, weight, geographic continents and publication year are reported. Results Seventy‐four studies with 4186 healthy volunteers (mean age 42.7 years) and 18,226 examined nerve sites were included. The calculated mean pooled CSA of the median nerve at the wrist was 8.3 mm2 (95% confidence interval [95% CI] 7.9–8.7, n = 4071), at the forearm 6.4 mm2 (95% CI 5.9–6.9, n = 3021), at the upper arm 8.3 mm2 (95% CI 7.5–9.0, n = 1388), of the ulnar nerve at the Guyon's canal 4.1 mm2 (95% CI 3.6–4.6, n = 1688), at the forearm 5.2 mm2 (95% CI 4.8–5.7, n = 1983), at the elbow 5.9 mm2 (95% CI 5.4–6.5, n = 2551), at the upper arm 6.6 mm2 (95% CI 5.1–6.1, n = 1737) and of the radial nerve 5.1 mm2 (95% CI 4.0–6.2, n = 1787). Substantial heterogeneity across studies (I2 > 50%) was found only for the radial nerve. Subgroup analysis revealed a positive effect of age for the median nerve at the wrist and for height and weight for different sites of the ulnar nerve. Conclusion The first meta‐analysis on CSA reference values for the upper extremities with no or only low heterogeneity of reported CSA values in most nerve sites is provided. Our data facilitate the goal of an international standardized evaluation protocol.
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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 | 0.015 | 0.041 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.022 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".