Systematic Review of Clinical Practice Guidelines for Post-Cataract Surgery Endophthalmitis Prophylaxis from 2008-2023
Bibliographic record
Abstract
Postoperative endophthalmitis remains a significant concern following cataract surgery with a potential for severe vision loss. Although numerous clinical practice guidelines (CPGs) have been published worldwide, they offer differing recommendations for prophylactic measures. This systematic review aimed to synthesize and evaluate existing guidelines for endophthalmitis prophylaxis after cataract surgery. A comprehensive search including citation and gray literature search was conducted. Authors' contact with peer international ophthalmologists was also employed. Clinical practice guidelines specifically on post-cataract surgery endophthalmitis prophylaxis published between 2008 and 2023 were included in this study. Quality assessment was done using the Appraisal of Guidelines for Research and Evaluation II (AGREE II) tool. Twenty-one guidelines were identified, assessed, and extracted. Intracameral antibiotics, instillation of povidone-iodine into the conjunctival sac, and periorbital skin preparation with povidone-iodine were the most commonly endorsed measures, although recommended concentrations, dosages, and contact times varied. Several guidelines did not address ancillary measures, such as face washing, postoperative eye protection or adjunctive topical antibiotics. While core prophylactic strategies were broadly agreed upon, significant differences persisted likely due to disparate local regulations, idiosyncratic practices, and interpretations of the evidence. Careful selection and employment of any procedure should be tailored according to patient characteristics and circumstances.
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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 | 0.029 | 0.152 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.008 |
| Bibliometrics | 0.028 | 0.027 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 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".