Long-term outcomes in half-dose verteporfin photodynamic therapy for chronic central serous retinopathy
Bibliographic record
Abstract
Objective: To evaluate the short- and long-term outcomes of half-dose verteporfin with photodynamic therapy (PDT) in the treatment of chronic central serous retinopathy (CSR). Design: Retrospective case series. Participants: 45 eyes in 39 patients with chronic CSR were included. Diagnosis of chronic CSR was confirmed by fluorescein angiography and persistence of subretinal fluid by optical coherence tomography for a minimum of 3 months duration. Methods: Each patient underwent treatment with half-dose verteporfin with full-fluence PDT; initial follow-up was defined as a 6–8 week visit following the treatment, and final follow-up ranged from 5 to 70 months. Results: The average follow-up period for treatment was 19.3 months. Best-corrected visual acuity increased from logMAR means of 0.52 to 0.42 ( p <0.05). Central retinal thickness and choroidal thickness also significantly decreased at last follow-up ( p <0.05). Eight of 45 eyes (18%) demonstrated a recurrence of CSR following treatment within the follow-up period. At the final follow-up, 41 out of the 45 eyes (91%) had complete resolution of subretinal fluid accumulation. Conclusion: Half-dose PDT is an effective treatment option for chronic CSR in a Canadian population, and it is both safe and durable. The positive treatment effect is realized rapidly, with the initial 6-week result highly correlated with the final follow-up result. Keywords: central serous chorioretinopathy, photodynamic therapy, verteporfin, half-dose verteporfin
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".