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Association Between the Use of Glaucoma Medications and Mortality

2010· article· en· W2109507336 on OpenAlexaff

Bibliographic record

VenueArchives of Ophthalmology · 2010
Typearticle
Languageen
FieldMedicine
TopicGlaucoma and retinal disorders
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGlaucomaMedicineOptometryAssociation (psychology)OphthalmologyPsychology

Abstract

fetched live from OpenAlex

OBJECTIVE: To evaluate the relationship between glaucoma medication use and death. METHODS: This study uses longitudinal data from 2003 to 2007 on persons 40 years and older with glaucoma or suspected glaucoma enrolled in a large managed care network. Cox regression analysis was performed to estimate the hazard of death associated with the use of various glaucoma medication classes and combinations thereof. Multivariable models were adjusted for demographic characteristics and comorbid medical conditions. RESULTS: Of 21 506 participants with glaucoma or suspected glaucoma, 237 (1.1%) died during the study period. The use of any class of glaucoma medication was associated with a 74% reduced hazard of death (adjusted hazard ratio [HR], 0.26; 95% confidence interval [CI], 0.16-0.40) compared with no glaucoma medication use. This association was observed for use of a single agent alone, such as a topical beta-antagonist (0.44; 0.24-0.83) or a prostaglandin analogue (0.31; 0.18-0.54), and for use of different combinations of drug classes. CONCLUSIONS: After adjustment for potential confounding variables, the use of glaucoma medications was associated with a reduced likelihood of death in this large sample of US adults with glaucoma. Future investigations should explore this association further because these findings may have important clinical implications.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.150

Codex and Gemma teacher scores by category

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

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.

Opus teacher head0.033
GPT teacher head0.310
Teacher spread0.278 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations19
Published2010
Admission routes1
Has abstractyes

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