Bibliographic record
Abstract
PURPOSE: To critically review the published literature on orbital radiotherapy as a treatment modality for thyroid eye disease (TED). METHODS: A systematic review and analysis of the relevant published literature was performed. RESULTS: Thyroid eye disease is an autoimmune condition that is amenable to treatments that modulate the immune response, including orbital radiotherapy (ORT). Ideal candidates for ORT are patients in the early, active phase of TED with moderate to severe, or rapidly progressive, disease, including patients with significant motility deficits and compressive optic neuropathy. Patients with progressive strabismus may also benefit. Patients with mild or inactive disease will not benefit from ORT when compared with the natural history of the disease. Orbital radiotherapy should generally be used in conjunction with corticosteroid therapy, with response to corticosteroids demonstrating the immunomodulatory therapeutic potential of ORT. When treating TED-compressive optic neuropathy, ORT may help obviate the need for urgent surgical decompression, or postpone it until the stable, inactive phase of the disease. Orbital radiotherapy treatment doses should approach 20 Gy in most cases, but lower doses may be considered in younger patients without significant dysmotility. The safety profile of ORT is well established, and side effects are minimal in appropriately selected patients. CONCLUSIONS: Radiotherapy is a safe and effective treatment for active TED in appropriately selected patients.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".