One-year outcome of combination therapy with intravitreal aflibercept and photodynamic therapy for polypoidal choroidal vasculopathy
Bibliographic record
Abstract
BACKGROUND: To investigate the one-year visual and anatomical outcomes of combination therapy with intravitreal aflibercept (IVA) and photodynamic therapy (PDT) for treating polypoidal choroidal vasculopathy (PCV). METHODS: This was a retrospective case-series study, including 30 eyes from 30 patients with treatment-naïve PCV treated by combination therapy with IVA and PDT. Best-corrected visual acuity (BCVA), central retinal thickness (CRT), complete polyp regression rate, and dry macula rate were recorded every 3 months during 12-month follow-up. Clinical factors associated with final visual outcome and retreatment were investigated. RESULTS: The mean LogMAR BCVA was significantly improved from 0.73 ± 0.65 at baseline to 0.51 ± 0.60 (p = 0.01), and the mean CRT was also significantly improved from 339 ± 96 μm at baseline to 244 ± 43 μm at 12-month follow-up (p < 0.001). Complete regression of polypoidal lesions was 76.7%, and dry macula rate was 100% at 12 months. Better final BCVA was associated with younger age and better baseline BCVA (p = 0.02 and p < 0 001). The patients without complete polyp regression at 3-month follow-up were associated with retreatment (p = 0.03). CONCLUSION: In this study, combination therapy with IVA and PDT had significant visual and anatomical improvements to PCV patients during one-year follow-up. Better baseline BCVA and younger age were found to be associated with better visual outcome.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".