Treatment and prophylaxis of radiation optic neuropathy: A systematic review and meta-analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: Radiation optic neuropathy (RON) generally follows radiation therapy that exceed 50 Gy to the visual axis and occurs within three years of therapy. Currently, there are no universally accepted treatments or prophylaxis for RON. The review aimed to examine the efficacy of all treatments and prophylaxis for RON. METHODS: MEDLINE, Embase, the Cochrane Library, and gray literature were searched to December 2020. Studies on treatment(s) and/or prophylaxis of RON were included. Results were meta-analyzed using a random-effects model. Primary outcomes included the proportions of patients who experienced improvement, no change, or worsening of visual acuity (VA) for each treatment. Secondary outcome was the incidence of RON for studies on prophylaxis. RESULTS: Overall, 50 studies (n = 5397) were included. Meta-analysis (n = 1752) showed significantly lower incidence of RON in patients who underwent intravitreal anti-VEGF prophylaxis compared to control (RR 0.64, 95%CI [0.48, 0.86]) for uveal melanoma. Intravitreal anti-VEGF injections (n = 68), hyperbaric oxygen therapy alone (n = 14), and pentoxifylline (n = 5) resulted in improved or stable vision ≤1 logMAR in 54.5%, 42.9%, and 40.0% of patients, respectively. Systemic corticosteroids (n = 82), anticoagulants (n = 12), and systemic bevacizumab (n = 7) showed improved or stable vision ≤1 logMAR in 17.1%, 33.3%, and 14.3% of patients, respectively. Overall risk of bias was low, but evidence was limited to retrospective studies. CONCLUSION: Intravitreal anti-VEGF injections reduced incidence of RON in irradiated uveal melanoma patients. Systemic corticosteroids, systemic bevacizumab, and warfarin alone are likely ineffective treatments. Early hyperbaric oxygen therapy and intravitreal anti-VEGF injections were most effective among those investigated and require further investigation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.002 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 it