The effect of systemic and topical ophthalmic medications on choroidal thickness: A review
Bibliographic record
Abstract
The choroid plays an important role in various ocular pathologies and retinal blood supply. There is a knowledge gap on how the choroid is affected by systemic and topical medications. Systemic medications that affect microvasculature elsewhere in the body can also affect the microvasculature of the choroid. This review summarizes current knowledge on associations between systemic and topical medications and changes in choroidal thickness (CT). This review included 71 studies on mydriatics/cycloplegics, intraocular pressure (IOP)-lowering therapies, antihypertensives, adrenergic antagonists, statins, corticosteroids, hydroxychloroquine, isotretinoin, hormonal contraceptives, phosphodiesterase inhibitors, antipsychotics, antineoplastic agents, ethanol, caffeine and nicotine. IOP-lowering therapies, atropine eye drops, and systemic administration of β blockers and ethanol are associated with a significant increase in CT. Cyclopentolate and phenylephrine are associated with a CT reduction. Systemic medications that decrease CT include caffeine and nicotine. Tropicamide, angiotensin-converting enzyme inhibitors, angiotensin receptor blockers, statins, corticosteroids, hydroxychloroquine and hormonal contraceptives have mixed findings. CT increase associated with IOP-lowering therapies is possibly achieved by enhancing aqueous humour flow to the choroid thus elevating choroidal blood flow and thickness. CT changes appear to be independent from systemic blood pressure changes, suggesting that a significant association with an antihypertensive could be due to an idiosyncratic drug property. Statins and candesartan decrease macrophage accumulation and intercellular adhesion molecule 1 expression in the choroid. The choroid and its response to various disease processes and systemic medication can be further investigated to improve patient care, particularly in patients with choroid and retina pathologies.
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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 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".