Cross‐sectional area reference values for peripheral nerve ultrasound in adults: A systematic review and meta‐analysis—Part II: Lower 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 such as entrapment syndromes and inflammatory polyneuropathies. We performed a systematic review and meta‐analysis of published CSA reference values for lower extremity nerves. Methods We included available‐to‐date nerve ultrasound studies on healthy adults and provide meta‐analysis for CSA of the following nerves: fibular nerve at fibular head, popliteal fossa; tibial nerve at popliteal fossa, malleolus; and sural nerve at the level of the two heads of gastrocnemius muscle. We report regression and correlation analyses for age, gender distribution, height, weight, and geographic continent. Results We included 16 studies with 1001 healthy volunteers (mean age = 47.9 years) and 4023 examined nerve sites. Calculated mean pooled CSA of fibular nerve at fibular head was 8.4 mm2 (95% confidence interval [CI] = 6.8–9.9 mm2, n = 1166), at popliteal fossa was 7.9 mm2 (95% CI = 6.6–9.2 mm2, n = 995), of tibial nerve at popliteal fossa was 25.9 mm2 (95% CI = 17.5–34.4 mm2, n = 771), at malleolus was 10.0 mm2 (95% CI = 7.7–12.4 mm2, n = 779), and of sural nerve was 2.4 mm2 (95% CI = 1.7–3.1 mm2, n = 312). Substantial heterogeneity across studies (I2 > 50%) was found only for tibial nerve at popliteal fossa. Subgroup analysis revealed a lower CSA of tibial nerve at popliteal fossa and sural nerve in studies conducted in Europe than in North America and New Zealand. Conclusions We provide the first meta‐analysis on CSA reference values for the lower extremities with no or low heterogeneity of reported CSA values in all nerve sites except tibial nerve at popliteal fossa. 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 | 0.048 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.025 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 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".