POSTINTRAVITREAL INJECTION AND POSTCATARACT EXTRACTION ENDOPHTHALMITIS VISUAL OUTCOMES BY ORGANISM
Bibliographic record
Abstract
PURPOSE: To compare visual outcomes of endophthalmitis following intravitreal injections (IVIs) and cataract extraction by causative organism. METHODS: Searches in Cochrane Central Register of Controlled Trials, MEDLINE, and Embase identified articles reporting visual outcomes by causative organisms in post-IVI and cataract extraction endophthalmitis cases from January 2010 to February 2022. A random-effects meta-analysis compared visual improvement among endophthalmitis cases caused by causative organisms. RESULTS: Eighty-five out of 3,317 retrieved studies were included. The highest degree of visual acuity improvement in both post-IVI and postcataract extraction endophthalmitis was seen in cases caused by coagulase-negative staphylococci, followed by gram-negative organisms and other gram-positive organisms such as streptococci and enterococci. Culture-negative cases showed more visual acuity improvement than culture-positive cases in post-IVI endophthalmitis. These results remained consistent when accounting for endophthalmitis treatment, IVI type, condition requiring IVI treatment, follow-up period, and initial preprocedural visual acuity. CONCLUSION: Coagulase-negative staphylococci and gram-negative organisms show the most visual acuity improvement in both post-IVI and postcataract extraction endophthalmitis. Other gram-positive organisms such as streptococci and enterococci are associated with less visual improvement. This updated systematic review and meta-analysis revealed that the results of the Endophthalmitis Vitrectomy Study are consistent decades later despite advancements in surgical practices and the evolution of microorganisms over time.
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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.017 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".