Bibliographic record
Abstract
Purpose. Data are provided from the Combigan Early Experience Data (CEED) study, which evaluated patients’ clinical experience of using Combigan ® in a real-life setting. Methods. CEED was a Canadian open-label, prospective 2-month surveillance trial involving 47 investigators and 453 patients. Primary outcomes were intraocular pressure (IOP) reduction and patient satisfaction. Adverse events and doctor satisfaction were secondary outcomes. Most patients were aged over 50, with 82% white, and nearly 90% had open-angle glaucoma. Combigan was used either as a replacement of, or an addition to, the patients’ existing therapy. Results. Switching to, or adding, Combigan to existing glaucoma therapy led to an additional reduction in IOP of 3.8 mmHg, and 70% of patients achieved IOP ≤18. mmHg compared with 31% at baseline. There was an additional reduction in IOP of almost 3 mmHg in patients switched from Cosopt to Combigan and the proportion of eyes achieving an IOP ≤18 mmHg more than doubled in these patients. Altogether, 92% of patients who switched from Cosopt alone to Combigan alone rated Combigan as more comfortable; 98% of doctors rated Combigan as good or excellent compared with other IOP-lowering medications. Conclusions. Combigan effectively lowered IOP over the 2-month trial, and the findings suggest that it is as effective as, or more effective than, Cosopt.
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 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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".