Aqueous humor penetration of gatifloxacin and moxifloxacin eyedrops given by different methods before cataract surgery
Bibliographic record
Abstract
PURPOSE: To determine whether the penetration into the aqueous humor of 2 new fourth-generation fluoroquinolone antibiotics, gatifloxacin (Zymar) and moxifloxacin (Vigamox) eyedrops, was affected by different methods of administration before cataract surgery. SETTING: Pasqua Hospital, Regina, Saskatchewan, Canada. METHODS: This prospective randomized study comprised 193 patients. The patients were divided into 2 main groups. One group received gatifloxacin eyedrops and the other, moxifloxacin eyedrops. Each group was subdivided into 4 subgroups. All patients received the drops 4 times a day starting 2 days preoperatively. The first subgroup did not receive any more antibiotics. The second subgroup received the antibiotic drops 3 times, starting approximately 2 hours preoperatively. The third subgroup received a wick soaked in a dilating mixture containing the antibiotic. The fourth subgroup received the wick and the antibiotic drops at the time of preparation for surgery. At the beginning of surgery, 0.1 mL of aqueous humor was aspirated, frozen, and sent under ice by courier to the Provincial Laboratory for analysis by high-performance liquid chromatography. RESULTS: The study included 124 women and 69 men. The mean concentrations in the aqueous humor were 0.19, 0.82, 0.22, and 0.30 microg/mL in the 4 gatifloxacin subgroups, respectively, and 0.38, 2.16, 0.88, and 0.97 microg/mL in the 4 moxifloxacin subgroups, respectively. Analysis of variance showed the differences between the 2 antibiotics to be statistically significant. CONCLUSIONS: Moxifloxacin penetrated the aqueous humor better than gatifloxacin regardless of the method of administration. Both antibiotics penetrated the aqueous humor well when given in drop form. They reached and exceeded the minimum inhibitory concentration levels for the most common ocular pathogens causing endophthalmitis. Only moxifloxacin reached these levels when the wick was used.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".