Morning Dosing of Once-daily Glaucoma Medication is More Convenient and May Lead to Greater Adherence Than Evening Dosing
Bibliographic record
Abstract
PURPOSE: To determine if adherence and convenience of once-daily glaucoma medication is greater in the morning or the evening. DESIGN: Prospective, randomized crossover treatment trial. PATIENTS AND METHODS: Thirty patients newly diagnosed with glaucoma or ocular hypertension requiring intraocular pressure (IOP) reduction were started on travoprost eye drops and randomized to either morning or evening administration for 1 month. They were then crossed over to the opposite dosing schedule for the following month. Adherence was monitored using an automated dosing aid. MAIN OUTCOME MEASURES: Adherence was compared between morning versus evening dosing and first versus second month dosing. Demographic characteristics were obtained, treatment effect was measured, and patients completed a post-study questionnaire regarding the convenience of the 2 dosing regimens. RESULTS: Patient adherence overall was good (89.3%). There was no statistically significant difference (P=0.07) in adherence between morning dosing (90.9%) and evening dosing (87.3%). Adherence in the first month (91.7%) was superior to the second month (86.5%). There was no significant difference in IOP response between morning and evening dosing. Patients found morning dosing more convenient than evening dosing. CONCLUSIONS: Early adherence to treatment with a prostaglandin analogue is good, but patients prefer morning administration to evening administration. This may lead to greater adherence with morning administration, particularly among men. Adherence decreases from the first to second month after initiation of treatment. IOP response to this treatment is not significantly affected by morning versus evening administration.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".