Decrease in Anti-VEGF Injections After Post-injection Endophthalmitis in Patients With Neovascular Age-Related Macular Degeneration
Bibliographic record
Abstract
Introduction: To evaluate the effect of antivascular endothelial growth factor (anti-VEGF)–related endophthalmitis on intravitreal injection (IVI) frequency in patients with neovascular age-related macular degeneration (nAMD). Methods: A retrospective chart review was performed of all cases of post IVI endophthalmitis that occurred in Edmonton, Alberta, Canada, between 2012 and 2019. Contralateral eyes affected by nAMD but without endophthalmitis served as a control group. The main outcome measures were the frequency of anti-VEGF injections, visual acuity, and activity of choroidal neovascularization before and after endophthalmitis. Results: Seventeen eyes met the inclusion criteria, 2 (12%) of which never resumed IVI after endophthalmitis because of the quiescence of disease. Post-endophthalmitis eyes received IVI less frequently in the 1 year after endophthalmitis (mean 0.52 ± 0.42 IVI/month) than those that received IVI 1 year before endophthalmitis (1.09 ± 0.36 IVI/month) ( P = .001). The 17 contralateral eyes also received anti-VEGF injections less frequently after endophthalmitis than before ( P = .001). There was no significant change in optical coherence tomography markers of disease activity in cases or controls. Conclusions: In patients with nAMD, endophthalmitis resolution is associated with a decrease in anti-VEGF injection frequency. The same decrease in anti-VEGF injection frequency is also seen in contralateral eyes unaffected by endophthalmitis. Markers of disease activity remain unchanged in both eyes, suggesting disease quiescence despite reduced IVI frequency.
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".