Corneal Confocal Microscopy Detects Neuropathy in Subjects With Impaired Glucose Tolerance
Bibliographic record
Abstract
OBJECTIVE: Impaired glucose tolerance (IGT) represents one of the earliest stages of glucose dysregulation and is associated with macrovascular disease, retinopathy, and microalbuminuria, but whether IGT causes neuropathy is unclear. RESEARCH DESIGN AND METHODS: Thirty-seven subjects with IGT and 20 age-matched control subjects underwent a comprehensive evaluation of neuropathy by assessing symptoms, neurological deficits, nerve conduction studies, quantitative sensory testing, heart rate variability deep breathing (HRVdb), skin biopsy, and corneal confocal microscopy (CCM). RESULTS: Subjects with IGT had a significantly increased neuropathy symptom profile (P < 0.001), McGill pain index (P < 0.001), neuropathy disability score (P = 0.001), vibration perception threshold (P = 0.002), warm threshold (P = 0.006), and cool threshold (P = 0.03), with a reduction in intraepidermal nerve fiber density (P = 0.03), corneal nerve fiber density (P < 0.001), corneal nerve branch density (P = 0.002), and corneal nerve fiber length (P = 0.05). No significant difference was found in sensory and motor nerve amplitude and conduction velocity or HRVdb. CONCLUSIONS: Subjects with IGT have evidence of neuropathy, particularly small-fiber damage, which can be detected using skin biopsy and CCM.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".