International trends in rigid contact lens prescribing (2000–2023): An update
Bibliographic record
Abstract
PURPOSE: Rigid contact lenses have an important role in contact lens practice. The purpose of this work is to update earlier surveys by describing global trends in rigid lens fitting between 2000-2023. METHOD: An annual contact lens prescribing survey was sent to eye care practitioners in up to 71 countries between 2000 and 2023. Data relating to 342,500 fits undertaken in 20 countries returning reliable longitudinal data were analysed in respect of rigid lens fitting, defined as the fitting of any design of a contact lens manufactured in a rigid material. RESULTS: Overall, rigid lens prescribing increased slightly over time, from 14.2 % of lens fits in 2000 to 15.2 % in 2023 (p < 0.0001). However, post-hoc analysis shows that the change over time is best described as a decline between 2000 and 2012, followed by a steady increase subsequently. There were significant differences in rigid lens prescribing between countries (p < 0.0001). The difference between the percentage of males fitted with rigid lenses, as a proportion of all contact lenses (12.7 %), and females (12.0 %) is significant (p < 0.0001), although not clinically meaningful. Rigid lens wearers are older at fitting than soft lens wearers (38.7 vs 31.3 years, respectively) (p < 0.0001). Analysis of 5,994 rigid lens fits prescribed currently (2019-2023) were categorised as: corneal sphere - 30 %; scleral and corneo-scleral - 28 %; corneal myopia control/orthokeratology - 21 %; and corneal complex (including toric, multifocal and monovision) - 16 %. CONCLUSION: There has been a slight increase in rigid lens fitting during the second decade of this century. This increase is apparently due to a 'repurposing' of rigid lenses, with the growth of scleral/corneo-scleral and myopia control/orthokeratology lens fits essentially replacing conventional spherical corneal lens fits.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.009 | 0.022 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".