Controversies, Consensuses, and Guidelines on Preventing, Diagnosing and Managing Acute-onset Bacterial Endophthalmitis after Cataract Surgery by the Academy of Asia-Pacific Professors of Ophthalmology (AAPPO), the Asia-Pacific Vitreo-retina Society (APVRS), and the Asia-Pacific Society of Ocular Inflammation and Infection (APSOII)
Bibliographic record
Abstract
BACKGROUND: Postcataract surgery endophthalmitis is a serious but largely preventable clinical entity. The implementation of uniform preoperative, intraoperative, and postoperative protocols is essential to reduce its incidence. METHODS: In light of emerging evidence and considerable variability in clinical practices, a panel of international experts from the Academy of Asia-Pacific Professors of Ophthalmology (AAPPO), the Asia-Pacific Vitreo-retina Society (APVRS), and the Asia-Pacific Society of Ocular Inflammation and Infection (APSOII) convened to develop evidence-based guidelines addressing all phases of cataract surgery. This consensus manuscript is the product of a systematic review of the current literature, informed by the collective experience and expertise of the panel members. The panel engaged in structured discussions, critical evaluation of clinical data, and formal voting to establish agreement across three key domains: (1) preoperative and intraoperative prophylactic strategies, (2) diagnostic approaches for early postoperative acute bacterial endophthalmitis, and (3) standardized management protocols. Voting on each proposed statement was conducted using a 5-point Likert scale (strongly agree, agree, neutral, disagree, strongly disagree). Consensus was defined as ≥75% of experts voting either "strongly agree" or "agree." RESULTS: A total of 45 consensus statements were evaluated, of which 21 (46.6%) achieved the predefined level of consensus. CONCLUSIONS: This document aims to establish standardized guidelines to improve cataract surgery outcomes by minimizing the risk of postoperative endophthalmitis. For areas where consensus was not achieved, the panel recommends further investigation and continued research to guide future updates to clinical practice.
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 | 0.049 | 0.144 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.006 | 0.005 |
| Research integrity | 0.010 | 0.019 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".