Ultrasonography in Distal Ulnar Nerve Neuropathy: Findings in 33 Patients
Bibliographic record
Abstract
PURPOSE: Although there are many case reports on the role of ultrasonography (US) in distal ulnar nerve neuropathy (Guyon canal syndrome), there is a paucity of large series in the literature because of its rarity. During an 8-year period, 33 instances of electrodiagnostically confirmed cases underwent US imaging. These cases were analyzed to determine the role of US in uncovering the cause of distal ulnar nerve neuropathy and its contribution to further management. METHODS: This was a retrospective study of patients diagnosed with distal ulnar nerve neuropathy based on electrodiagnostic criteria, who also had undergone US (measurement of the cross-sectional area and documentation of causes such as cysts and neuromas). RESULTS: US showed normal ulnar nerve in 5, cysts in 10, neuromas in 2, and nonspecific enlargement in 16 patients. Surgery was performed in 15 patients, and the US findings were corroborated in those with cysts and neuromas; 1 patient had an aberrant muscle, and two had fibrous bands constricting the ulnar nerve in the Guyon canal (not detected preoperatively by US imaging). CONCLUSIONS: US imaging detected the underlying cause of distal ulnar nerve neuropathy in a significant percentage of patients, potentially contributing to effective treatment.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".