Small fibre neuropathy: role in the diagnosis of diabetic sensorimotor polyneuropathy
Bibliographic record
Abstract
Small fibres constitute 70-90% of peripheral nerve fibres and regulate several key functions such as tissue blood flow, temperature and pain perception as well as sweating, all of which are highly relevant to the clinical presentation and adverse outcomes associated with foot ulcerations in patients with diabetes. Recent studies demonstrated significant abnormalities in the small fibres in subjects with impaired glucose tolerance and diabetes, despite normal electrophysiology, suggesting that the earliest nerve fibre damage is to the small fibres. Unfortunately, guidelines and consensus statements focus on large fibres and continue to advocate electrophysiology as a diagnostic modality and as a primary end point for the assessment of therapeutic benefit. (In part, this reflects the difficulties in quantifying small fibre dysfunction and damage.) We have therefore critically assessed currently available techniques that measure small fibre dysfunction in diabetic neuropathy, using quantitative sensory and sudomotor testing. We have assessed the role of identifying structural damage by quantifying intraepidermal nerve fibre density in skin biopsies and corneal nerve morphology using corneal confocal microscopy. Finally, we propose a definition for diabetic neuropathy that incorporates small fibre damage.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".