Variation of Bruch's membrane opening in response to intraocular pressure change during scleral lens wear, in a population with keratoconus
Bibliographic record
Abstract
PURPOSE: The present study aimed to determine the potential impact of scleral lenses on intraocular pressure (IOP) by analysing the Bruch's membrane opening-minimum rim width (BMO-MRW) while the lenses are worn, in a population with keratoconus. METHODS: Participants were required to have keratoconus and be successfully fitted with scleral lenses for at least 3 months. A new pair of optimised scleral lenses was provided before the study. During the first session, corneal biomechanics was assessed using an air tonometer, coupling Scheimpflug technology. Then, a scan of the optic nerve was carried out using optical coherence tomography (OCT) at 2 h intervals for 6 h. Particular attention was paid to identifying the BMO-MRW, which represents the smallest distance between the BMO and the internal limiting membrane. These tests were repeated, respecting the time at which the initial measurements were taken, while the scleral lens was worn. Results from only one eye were analysed. RESULTS: A statistically significant change of 10.5 ± 3.6 μm (95% CI [241.3-473.1]; p = 0.02) in BMO-MRW was observed after 6 h of scleral lens wear, compared to measurements without lenses (4.8 ± 3.4 μm; 95% CI [285.1-439.7]; p = 0.18). The fluctuation was greater in participants with keratoconus than found in a previous study of regular corneas. CONCLUSION: BMO-MRW became significantly thinner after 6 h of scleral lens wear compared with measurements without lenses. These variations may be associated with a rise in IOP during lens wear. Close monitoring for optic head changes should be carried out for patients at risk. These results should be compared with future longer-term studies including a larger cohort of patients.
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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 | 0.002 |
| 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) | 0.001 | 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".