The Effect of Brimonidine 0.15% on the Development of Bulbar Redness Following Femtosecond Laser Assisted Cataract Surgery
Bibliographic record
Abstract
Purpose: To assess the effect of brimonidine tartrate 0.15% on reducing subconjunctival hemorrhage, measured with a bulbar redness score, following femtosecond laser assisted cataract surgery (FLACS). Patients and Methods: A prospective, masked randomized controlled study was done using single-blinded simple randomization. All FLACS cases completed between June and August 2019 were included except those on anticoagulation or with prior conjunctival surgery. All operated eyes received usual preoperative eye drops, while Study group received added brimonidine. Exclusion criteria included >1 vacuum attempt during FLACS and any intraoperative complications. All subjects received Bulbar Redness (BR) Score and Analyzed Area (AA) imaging by Oculus 5M Keratograph preoperatively and postoperatively. AA including non-conjunctival structures, <25mm2, or postoperative AA values >10% different from preoperative values were excluded from final analysis. Absolute values and differences between mean postoperative and preoperative BR and AA were compared using Student’s t-test. Results: 62 eyes (Study group=25, Control group=37) of 56 patients were randomized and included for analysis. Baseline demographic comparison between the two groups were similar. Preoperative BR score in the Study group trended higher (1.62) than Control (1.40, p=0.07), while postoperative BR score remained similar between groups (p=0.70). Difference in postoperative and preoperative BR score was significantly larger in the study group (-0.21±0.56) than controls (+0.06±0.43, p=0.036). Conclusions: The use of preoperative brimonidine in FLACS reduces the amount of postoperative subconjunctival hemorrhage following FLACS, as observed by reduced bulbar redness. Oculus 5M BR scoring has potential to be used as an objective method of quantifying subconjunctival hemorrhage after ophthalmic surgeries and procedures.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".