Repeatability of Grading Meibomian Gland Dropout Using Two Infrared Systems
Bibliographic record
Abstract
PURPOSE: To determine the interobserver and intraobserver repeatability in using the OCULUS Keratograph 4 (K4) and 5M (K5M) to grade meibomian gland (MG) dropout using meibography grading scales. METHODS: The inferior and superior eyelids of 40 participants (35 women, 5 men; mean age = 32 years) were imaged three times each on both instruments. The images were split into one training and two study sets; the latter were graded (four-point meibography scale) by two observers on two separate occasions (24 hours apart) to determine repeatability. Semiobjective quantification of percentage MG dropout was conducted using ImageJ on K4 and K5M images. A finer seven-point meibography scale was used to grade a separate set of K5M images. RESULTS: For the four-point scale, interobserver mean difference (MD) (±SD) was 0.08 (±0.55) on day 1 and 0.13 (±0.50) on day 2, and the concordance correlation coefficient (CCC) was 0.79 and 0.81 on days 1 and 2, respectively. Intraobserver MD (±SD) was 0.04 (±0.54), CCC = 0.79 for observer 1; intraobserver MD (±SD) was -0.09 (±0.60), CCC = 0.74 for observer 2. For the seven-point scale, interobserver MD (±SD) was 0.05 (±0.45), CCC = 0.89 on day 1, and interobserver MD (±SD) was 0.01 (±0.41), CCC = 0.91 on day 2. Intraobserver MD (±SD) was -0.10 (±0.35), CCC = 0.93 for observer 1, and intraobserver MD (±SD) was -0.06 (±0.30), CCC = 0.95 for observer 2. Percentage dropout measured between the K4 and K5M images showed lack of agreement, with 21.8% coefficient of repeatability. There was no significant correlation (r < 0.2; p > 0.05) between meibography score and clinical signs (corneal staining, gland expressibility, telangiectasia, vascularity, lash loss); however, there was a high correlation (r = 0.77; p < 0.05) between meibography score with percentage dropout. CONCLUSIONS: Observers graded from -1 to +1 grade units between and within themselves for a four-point scale, 95% of the time. Although the interobserver and intraobserver repeatability of the K4 and K5M were very similar, a high rate of disagreement in percentage dropout between K4 and K5M images suggests that the two instruments cannot be interchanged. Meibomian gland dropout scores did not correlate significantly with clinical signs. Using a finer scale may be beneficial for detecting change.
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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 | 0.011 | 0.025 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".