Variables associated with corneal confocal microscopy parameters in healthy volunteers: implications for diabetic neuropathy screening
Bibliographic record
Abstract
AIM: Corneal confocal microscopy is a promising screening method for diabetic neuropathy. Although much research in this field has been accomplished, we aimed to determine and confirm the known clinical and eyewear variables associated with the parameters of corneal confocal microscopy specifically in healthy volunteers, in particular associations with corneal nerve fibre length. METHODS: Clinical characteristics, electrophysiological examination and a general clinical eye history were collected from 64 healthy volunteers. Corneal confocal microscopy was performed to determine corneal nerve fibre length, corneal nerve branch density, corneal nerve fibre density and tortuosity coefficient. Univariate and multivariate linear regression analysis was used to determine clinical variables associated with corneal nerve fibre length parameters. RESULTS: We observed that corneal nerve fibre length has a broad distribution in healthy volunteers (18 ± 4 mm/mm(2), 95% confidence interval, 12.3-25.7 mm/mm(2)). Multivariate regression analysis demonstrated that HbA(1c) was the only independent clinical factor to account for variations in corneal nerve fibre length, independent of age and status of contact lens wear. CONCLUSIONS: This study does not provide convincing evidence that corneal nerve fibre length is independently associated with age or the wearing of contact lenses, and that these factors are therefore unlikely to hinder valid screening for polyneuropathies such as diabetic neuropathy. Furthermore, the strong inverse association of corneal nerve fibre length with glycaemic exposure may support the use of this parameter to detect subclinical pre-diabetic nerve injury.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".