Repeatability of Grading Meibomian Gland Dropout Using Two Infrared Systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it