Peripheral Nerve Ultrasound in Small Fiber Neuropathy (P6.086)
Bibliographic record
Abstract
Objective: The aim of this study was to determine if structural changes in distal peripheral nerve are apparent on ultrasound (US) in patients with small fiber neuropathy (SFN). Background: Small fiber neuropathy can be an early presentation of chronic axonal polyneuropathies. The diagnosis of SFN is based on abnormal function of small nerve fibers, such as abnormal quantitative thermal thresholds, and morphological changes with reduced intraepidermal nerve fiber density (IENFD) in the setting of normal nerve conduction studies. Prior studies have shown that US of peripheral nerve is able to detect structural changes in nerves with documented large fiber involvement including CIDP and diabetes neuropathy. This study aims to determine if structural changes in distal peripheral nerve are apparent on US in patients with SFN. Methods and Design: 15 patients with SFN diagnosed by reduced IENFD and 15 healthy controls were recruited for US of motor and sensory nerves of the dominant lower limb. Two groups were matched in age, gender and body mass index (BMI). The cross sectional area (CSA) and flattening ratio (FR) of the sural nerve at the level of the lateral malleolus, superficial peroneal and tibial nerves at the lower third of the leg were measured by US. Results: The mean CSA of the sural nerve in SFN patients was 3.08 ± 0.77 mm2 with a median value of 3.26 and interquartile range of 2.52-3.65 (25%-75%) and in healthy controls was 2.50 ±0 .53 mm2 with a median value of 2.51 and interquartile range of 2.13-2.81 (25%-75%) (p< 0.01). The FR was the same in both groups. US parameters in other nerves were not different between groups. Conclusion: Ultrasound can show structural changes, i.e.: enlarged cross sectional area of distal large sensory nerve, in patients diagnosed with small fiber neuropathy.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".