Clinical, physiological and pathological characterisation of the sensory predominant peripheral neuropathy in copper deficiency
Bibliographic record
Abstract
INTRODUCTION: Myelopathy is considered the most common neurological complication of copper deficiency. Concurrent peripheral neuropathy has been recognised in association with copper deficiency but has not been well characterised. OBJECTIVES: To characterise the clinical, physiological and pathological features of copper-deficient peripheral neuropathy. METHODS: Patients with simultaneous copper deficiency (<0.78 μg/mL) and peripheral neuropathy seen at the Mayo Clinic from 1985 to 2005 were identified. RESULTS: 34 patients were identified (median age 55 years, range 36-78) including 24 women and 10 men. Myelopathy was found in 21 patients. Median serum copper level was 0.11 μg/mL (range 0-0.58). The most frequent clinical and electrophysiological pattern of neuropathy was a sensory predominant length-dependent peripheral neuropathy (71%). Somatosensory evoked potentials demonstrated central slowing supporting myelopathy (96%). Quantitative sensory testing demonstrated both small and large fibre involvement (100%). Autonomic reflex screens (77%) and thermoregulatory sweat test (67%) confirmed sudomotor dysfunction. 14 cutaneous nerve biopsies revealed loss of myelinated nerve fibres (86%), increased regenerative clusters (50%), increased rates of axonal degeneration (91%) and increased numbers of empty nerve strands (73%). 71% of biopsies demonstrated epineurial perivascular inflammation. CONCLUSIONS: An axonal, length-dependent sensory predominant peripheral neuropathy causing sensory ataxia is characteristic of copper deficiency usually co-occurring with myelopathy. Neurophysiological testing confirms involvement of large, greater than small fibres. The pathological findings suggest axonal degeneration and repair. Inflammatory infiltrates are common but are small and of doubtful pathological significance.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".