Topical Antiseptics in Minimizing Ocular Surface Bacterial Load Before Ophthalmic Surgery: A Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: To investigate the reduction of the ocular surface bacterial load induced by 2 commercially available ophthalmic antiseptic formulations, povidone-iodine (PVI) 0.6% and chlorhexidine (CLX) 0.02%, before ocular surgery. DESIGN: Randomized controlled trial. METHODS: Seventy adult patients undergoing intraocular surgery (phacoemulsification) were randomized to receive in the index eye PVI (group A) 4 times a day for 3 days or CLX (group B) 4 times a day for 3 days before surgery. The untreated eye was used as control. A conjunctival swab was taken in both eyes before (T0) and after (T1) therapy. Microbial DNA was quantified with real-time polymerase chain reaction (PCR) analysis. The Mick algorithm was used to compare the abundance of each genus/genera against the distribution of abundances from the reference. At T1, patients filled a questionnaire to evaluate therapy-induced symptoms. Primary outcome was the reduction of bacterial DNA at T1 (microbial load), vs control arm, expressed as mean number of real-time PCR cycle times (CTs). Secondary outcomes were taxonomic composition, differential abundance, and therapy-induced ocular symptoms. RESULTS: The T0-T1 difference in CT was significant in group B, but not in group A (mean [95% CI], 0.99 [0.33] vs 0.26 [0.15], P < .001, and 0.65 [0.3] vs 0.45 [0.41], P = .09, respectively). The taxonomic composition, alpha, and beta diversity remained consistent at all time points in both groups. The rate of patients reporting therapy-induced ocular symptoms and the mean discomfort grade were greater in group A than in group B (97% vs 26% and 4.97±2.48 vs 0.66±1.53, respectively). CONCLUSIONS: Compared with PVI 0.6%, CLX 0.02% induced a greater reduction of ocular surface bacterial load, with no significant alterations of the taxonomic composition. Moreover, CLX was better tolerated than PVI.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.003 | 0.003 |
| 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".