Nerve Ultrasound in Pediatric Polyneuropathies: A Systematic Review
Bibliographic record
Abstract
Abstract The diagnosis of peripheral polyneuropathy in children and the differential diagnosis among its various forms often present a challenge, also because electrodiagnostic studies can be painful and sometimes yield inconclusive results. This systematic review examines the role of nerve ultrasound (n-US) in the diagnosis and follow-up of pediatric polyneuropathies. We searched PubMed and Embase from 1975 to April 1, 2025. Included studies assessed patients aged ≤ 18 years with clinically and neurophysiologically confirmed polyneuropathy, providing pediatric-specific qualitative or quantitative n-US findings. Eighteen studies met the inclusion criteria. Six focused on acquired inflammatory polyneuropathies (three on Guillain–Barré Syndrome [GBS], three on Chronic Inflammatory Demyelinating Polyneuropathy [CIDP]), eight on Charcot–Marie–Tooth disease (CMT), two on lysosomal storage disorders, one on Autosomal Recessive Spastic Ataxia of Charlevoix–Saguenay (ARSACS), and one on mixed etiologies. Most (n = 7) were case reports. Cross-sectional area and nerve enlargement (NE) distribution were the main parameters evaluated. Marked, diffuse NE was found in demyelinating CMT and lysosomal disorders; CIDP showed diffuse and multifocal NE; GBS presented mild and proximal NE. No NE was reported in axonal CMT or ARSACS. Few studies assessed echogenicity or fascicular structure; none evaluated vascularization. n-US shows promise in differentiating demyelinating conditions such as CMT, CIDP, GBS, and certain metabolic syndromes in children. However, further age-matched control studies are needed, given that nerve growth and myelination peak between 15 and 17 years. Future research should explore n-US as an early diagnostic, screening, and follow-up tool.
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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 | 0.001 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".