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Survey of Complementary and Alternative Medicine Use in Glaucoma Patients

2010· article· en· W89822324 on OpenAlexaff
Michael J. Wan

Bibliographic record

VenueJournal of Glaucoma · 2010
Typearticle
Languageen
FieldMedicine
TopicComplementary and Alternative Medicine Studies
Canadian institutionsYork UniversityUniversity of Toronto
Fundersnot available
KeywordsGlaucomaOptometryMedicineOphthalmology

Abstract

fetched live from OpenAlex

PURPOSE: To determine the prevalence, types, and associated factors of complementary and alternative medicine (CAM) use in glaucoma patients. PATIENTS AND METHODS: Prospective, multicenter, cross-sectional survey. A total of 1516 consecutive patients attending 2 tertiary glaucoma clinics were surveyed on CAM use. Information gathered on standardized data collection sheets included demographic variables, ophthalmic history, glaucoma treatment history, and details of CAM use. RESULTS: The response rate was 92.5%. A total of 166 patients (10.9%) reported current use of CAM therapy specifically for glaucoma whereas 41 patients (2.7%) reported past use of CAM. Of the patients who reported CAM use, 62.5% had not disclosed the use of CAM to their ophthalmologist and 40.5% believed that the treatments were helping their glaucoma. The most commonly used types of CAM were herbal medications (34.5%), dietary modifications (22.7%), and vitamin/mineral supplements (18.8%). Of the 207 patients who reported current or past CAM use for their glaucoma, 3 (1.4%) indicated that they used conventional glaucoma treatments < prescribed because of their CAM use. CONCLUSIONS: Approximately 1 in 9 glaucoma patients use CAM for their disease. Many of these patients do not disclose the use of CAM to their ophthalmologist, but the vast majority report that they still take conventional glaucoma medications as prescribed.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.501

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.054
GPT teacher head0.336
Teacher spread0.282 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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