Reliability of confocal corneal microscopy for measurement of dendritic cell density in suspected small fiber neuropathy
Bibliographic record
Abstract
INTRODUCTION/AIMS: Dendritic cells (DCs) and their contacts with corneal nerves are described in animal models of nerve damage. Dendritic cell density (DCD) is a potential marker of immune activity in suspected small-fiber neuropathy (SFN). Here, we aim to evaluate the intra- and inter-rater reliability of DCD measurements in suspected SFN. METHODS: This retrospective study collected DCD from confocal microscopy images from the corneal sub-basal epithelium of the eye from 48 patients (mean age 49.6 ± 12.1 y, 61% female). Two examiners, each blinded to the other's examinations and measurements, assessed DCD to evaluate inter-rater reliability. For intra-rater reliability, the first examiner performed a second measurement after 14 days. DCs were classified into two cell morphological subtypes: mature and immature. RESULTS: Test-retest reliability for total DCD showed excellent agreement, with an intraclass correlation coefficient of 0.96 and inter-rater reliability intraclass correlation coefficient of 0.77. The immature cell subtype showed excellent intra-rater reliability but lower inter-rater reliability. DISCUSSION: We found that DCD measurements in the corneal sub-basal epithelium are sufficiently reliable for consideration in clinical studies of patients with suspected SFN.
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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 | 0.015 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".