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Record W4233183849 · doi:10.5489/cuaj.371

Urologic medications and ophthalmologic side effects: a review

2013· review· en· W4233183849 on OpenAlexaffvenue
Johan Gani, Nathan Perlis, Sidney B. Radomski

Bibliographic record

VenueCanadian Urological Association Journal · 2013
Typereview
Languageen
FieldMedicine
TopicIntraocular Surgery and Lenses
Canadian institutionsToronto Western HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineGlaucomaAnticholinergicOptic neuropathyUrinary retentionOphthalmologyAnesthesiaSurgeryOptic nerve

Abstract

fetched live from OpenAlex

Commonly prescribed urologic medications can have significantophthalmologic side effects. The existing information can be conflicting. We looked at alpha-blockers and intraoperative floppy iris syndrome (IFIS), phosphodiesterase type 5 (PDE5) inhibitors and non-arteritic ischemic optic neuropathy (NAION) and lastly anticholinergic medications and glaucoma. There is no conclusive scientific data on what to do if the risk of urinary retention is low to moderate, however, we recommend that patients having cataract surgery should stop alpha-blocker medications preoperatively. If there is a high risk of urinary retention, the alpha-blocker should not be withheld, with the active involvement of the ophthalmologist. The role of using 5 alpha-reductase inhibitors (5ARIs) can be considered. There is no convincing evidence that PDE5 inhibitors cause non-arteritic anterior ischemic optic neuropathy (NAION), but patients should be advised of the possible risk of visual loss, especially in patients with risk factors of ischemic heart disease. Acute angle closure glaucoma (AACG or closed angle glaucoma) is very rarely caused by anticholinergic medications in patients withnarrow angle anterior eye chambers. However, these medications are safe in patients with open angle glaucoma or treated closed angle glaucoma. Urologists should inquire about the patient’s glaucoma history from his/her ophthalmologist before starting an anticholinergic medication.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.937
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0010.001

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.

Opus teacher head0.029
GPT teacher head0.299
Teacher spread0.270 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations17
Published2013
Admission routes2
Has abstractyes

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