Rates of endophthalmitis before and after transition from povidone-iodine to aqueous chlorhexidine asepsis for intravitreal injection
Bibliographic record
Abstract
OBJECTIVE: To assess the rate of post-intravitreal injection endophthalmitis between 2 asepsis groups: aqueous chlorhexidine 0.1% and povidone-iodine 5%. DESIGN: Retrospective, observational cohort study. PARTICIPANTS: Patients with infectious endophthalmitis post intravitreal injection (n = 58) at a single centre from July 2009 to July 2022. METHODS: Retrospective chart review of all patients receiving intravitreal injections (216 593 injections) at a single centre over 14 years. Patients from July 2009 to February 2017 received povidone-iodine 5%, and patients from March 2017 to July 2022 received aqueous chlorhexidine 0.1%. Assessed characteristics of endophthalmitis cases included demographics, visual function, intervention type, and microbiological results. RESULTS: The rate of endophthalmitis was comparable for povidone-iodine (1.4:5000) and aqueous chlorhexidine (1.3:5000) (p = 0.77). Vitreous cultures were negative for 55% of patients. Visual acuity (VA) outcomes did not differ between asepsis groups nor between culture positive/negative groups. Patients having vitrectomy (PPV) had worse final vision (p = 0.08) but there was no VA difference between early and late PPV. CONCLUSIONS: Aqueous chlorhexidine 0.1% is a viable and safe alternative to povidone-iodine 5% for post-intravitreal injection endophthalmitis prophylaxis and may reduce ocular surface adverse events and discomfort.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".