PHOTODYNAMIC THERAPY FOR JUXTAFOVEAL CHOROIDAL NEOVASCULARIZATION DUE TO OCULAR HISTOPLASMOSIS SYNDROME
Bibliographic record
Abstract
PURPOSE: To report the use of photodynamic therapy with verteporfin in patients with juxtafoveal choroidal neovascularization (CNV) for ocular histoplasmosis syndrome (OHS). METHODS: Retrospective review. Data regarding the following variables were extracted from patient charts: demographic characteristics, previous surgeries, angiographic features, number and time of treatments, follow-up time, and change in visual acuity. RESULTS: This study sample consisted of 23 eyes of 23 consecutive patients who were treated with photodynamic therapy for the management of juxtafoveal CNV. When post-treatment visual acuity (mean logMAR acuity=0.321) was compared to baseline acuity (mean logMAR visual acuity=3.89) vision improved by more than three Snellen lines in 30% of eyes, remained the same (+/-2 Snellen lines) in 52% of eyes, and worsened (greater than a two-line loss in visual acuity) in 18% of eyes. Although this series was uncontrolled, the patients had a trend toward a therapeutic benefit when compared to published natural history of similar cases (OR=0.292, P value=0.071 when compared to data from the Macular Photocoagulation Study for treatment of juxtafoveal lesions). CONCLUSION: Photodynamic therapy with verteporfin may be beneficial in patients with juxtafoveal CNV secondary to OHS in terms of both visual stabilization and improvement.
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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 | 0.000 | 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".