INCIDENCE OF ACUTE EXUDATIVE MACULOPATHY AFTER REDUCED-FLUENCE PHOTODYNAMIC THERAPY
Bibliographic record
Abstract
PURPOSE: To describe the incidence and features of acute exudative maculopathy (AEM) after half-fluence photodynamic therapy (PDT) and/or very minimal fluence PDT. METHODS: Retrospective chart review of all patients treated over a 7-year period. RESULTS: A total of 52 patients (58 eyes, 140 treatments) were treated with half-fluence PDT and/or very minimal fluence PDT. Patients were diagnosed with either central serous chorioretinopathy (CSCR) or neovascular age-related macular degeneration (nAMD). Two patients (1 CSCR and 1 nAMD) returned to the clinic with acute vision loss after treatment and were identified as having developed AEM. In the CSCR case, resolution occurred after intravitreal bevacizumab treatment. The nAMD case resolved with topical difluprednate treatment. We were unable to identify any risk factors for the development of AEM. CONCLUSION: AEM seems to be a rare (incidence 1.4% per treatment) and unpredictable reaction related to the proinflammatory effects of half-fluence PDT and very minimal fluence PDT. Because of the inherent limitations of this study, the true incidence of AEM after reduced-fluence PDT may be higher.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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".