Tear exchange and contact lenses: A review
Bibliographic record
Abstract
Tear exchange beneath a contact lens facilitates ongoing fluid replenishment between the ocular surface and the lens. This exchange is considerably lower during the wear of soft lenses compared with rigid lenses. As a result, the accumulation of tear film debris and metabolic by-products between the cornea and a soft contact lens increases, potentially leading to complications. Lens design innovations have been proposed, but no substantial improvement in soft lens tear exchange has been reported. Researchers have determined post-lens tear exchange using several methods, notably fluorophotometry. However, due to technological limitations, little remains known about tear hydrodynamics around the lens and, to-date, true tear exchange with contact lenses has not been shown. Further knowledge regarding tear exchange could be vital in aiding better contact lens design, with the prospect of alleviating certain adverse ocular responses. This article reviews the literature to-date on the significance, implications and measurement of tear exchange with contact lenses. El intercambio de lágrima bajo las lentes de contacto facilita la reposición continua de fluido entre la superficie ocular y las lentes. Dicho intercambio es considerablemente menor con el uso de lentes blandas en lugar de rígidas. Como resultado, se incrementa la acumulación de desechos de la película de lágrimas y los sub-productos metabólicos entre la córnea y las lentes de contacto blandas, lo que conlleva complicaciones potenciales. Se han propuesto innovaciones en el diseño de las lentes, pero no se ha reportado ninguna mejora sustancial en lo referente al intercambio de lágrima con las lentes de contacto blandas. Los investigadores han determinado el intercambio de lágrimas tras el uso de lentes utilizando diversos métodos, principalmente la fluorofotometría. Sin embargo, debido a las limitaciones técnicas, se conoce poco acerca de la hidrodinámica relacionada con las lentes y, hasta la fecha, no se ha mostrado un intercambio de lágrima substancial con lentes de contacto. El conocimiento adicional sobre el intercambio de lágrima podría resultar esencial para ayudar a diseñar lentes de contacto mejoradas, con la perspectiva de aliviar ciertas respuestas oculares adversas. Este artículo revisa la literatura hasta la fecha acerca de la importancia, implicaciones y medición del intercambio de lágrima con lentes de contacto.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".