Antimicrobials and antiseptics: Lowering effect on ocular surface bacterial flora – A systematic review
Bibliographic record
Abstract
Topical antimicrobials and antiseptics are used perioperatively to reduce the ocular surface bacteria flora (OSBF) that are involved in the development of post-operative infectious complications. However, their effectiveness is still a controversial topic. This systematic review, performed according to the PRISMA guidelines and registered in PROSPERO, aims to provide an overview of the efficacy of the agents currently used in peri-cataract surgery and -intravitreal injections (IVI) in lowering the OSBF. Although effective in lowering OSBF, perioperative topical antimicrobials are associated with the risk of resistance development, with no obvious additional benefit compared with topical antisepsis. Conversely, the effectiveness of topical antiseptics before cataract surgery and IVI is strongly supported. Based on the available evidence, perioperative antimicrobials are not recommended, whereas the perioperative use of antiseptics is strongly recommended as prophylactic treatment for lowering the infection due to OSBF. Post-operative antimicrobials may be considered in eyes at higher risk for infection.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".