Photodynamic Therapy in Young Patients
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE To present a consecutive case series of patients 50 years or younger who underwent photodynamic therapy (PDT) for choroidal neovascularization (CNV) from etiologies other than age-related macular degeneration. PATIENTS AND METHODS Retrospective chart review of 35 consecutive eyes of 34 patients. RESULTS Visual acuity remained stable or improved in 20 of 35 eyes. Thirteen eyes with myopic degeneration had pre-treatment and post-treatment mean visual acuities of 20/100 and 20/200, respectively. Eight eyes with idiopathic CNV had an improvement of mean visual acuity from 20/200 to 20/125. Six eyes with ocular histoplasmosis displayed a stable mean visual acuity of 20/50. Of 3 eyes with angioid streaks, visual acuity remained stable in 2 eyes and declined in 1 eye. Five eyes with other etiologies all had improved vision. CONCLUSION Although the current literature shows evidence that PDT is beneficial in treating CNV secondary to myopic degeneration, the evidence for etiologies such as idiopathic causes, ocular histoplasmosis, and angioid streaks is optimistic but remains unproven. Our study suggests that PDT may be beneficial in stabilizing and improving vision when treating CNV from these etiologies. [ Ophthalmic Surg Lasers Imaging 2006;37:182-189.] AUTHORS From the Retina Service, Wills Eye Hospital, Thomas Jefferson University, Philadelphia, Pennsylvania. Accepted for publication February 26, 2006. Presented at the 23rd Annual Meeting of the American Society of Retina Specialists in Montreal, Quebec, Canada, July 16-20, 2005. Address reprint requests to Allen C. Ho, MD, Retinovitreous Associates, 910 East Willow Grove Ave., Wyndmoor, PA 19038.
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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 | 0.001 |
| 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) | 0.003 | 0.001 |
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".