INTRAVITREAL BEVACIZUMAB ALONE VERSUS COMBINED VERTEPORFIN PHOTODYNAMIC THERAPY AND INTRAVITREAL BEVACIZUMAB FOR CHOROIDAL NEOVASCULARIZATION IN AGE-RELATED MACULAR DEGENERATION
Bibliographic record
Abstract
PURPOSE: The purpose of the study was to compare the mean change in visual acuity between bevacizumab and combined bevacizumab and photodynamic therapy for the treatment of choroidal neovascularization from age-related macular degeneration after 12 months of follow-up. METHODS: This study included a retrospective cohort of patients with untreated choroidal neovascularization. The generalized estimating equation was used to account for the correlation between eyes and to construct multivariate models to control for confounding factors of visual acuity change. RESULTS: One hundred and thirty-nine eyes treated with bevacizumab were compared with 236 eyes that received bevacizumab and photodynamic therapy (combination treatment). The monotherapy eyes showed an improvement of 0.101 +/- 0.619 logarithm of minimum angle of resolution units (5.05 letters) after a mean follow-up of 409.6 days versus 0.096 +/- 0.611 (4.8 letters) after a mean follow-up of 416.7 days with combination therapy; there was no difference between the groups (P = 0.970). The monotherapy eyes received 3.32 +/- 1.71 injections versus 3.14 +/- 1.52 injections in the combination therapy group (P = 0.665). The multivariate analysis did not show any difference between groups at the end of the study period in terms of visual improvement, worsening, stabilization, or the number of bevacizumab injections used. CONCLUSION: Long-term visual outcomes for the treatment of choroidal neovascularization in age-related macular degeneration are not improved with the addition of photodynamic therapy to bevacizumab nor are fewer injections needed.
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 | 0.002 | 0.002 |
| 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".