The Effectiveness of Grenz Ray Therapy for Chronic Dermatoses of the Hands and Feet
Bibliographic record
Abstract
BACKGROUND: Grenz ray therapy (GRT) has been used for inflammatory and neoplastic dermatologic diseases for over 100 years. Its use is declining, possibly because of the difficulties maintaining radiation certification and insurance coverage. OBJECTIVE: The aim of this study is to evaluate the safety and effectiveness of GRT in chronic inflammatory dermatoses of the hands and feet. METHODS: We performed a retrospective chart review of patients treated with GRT at the Oregon Health & Science University from 2006 to 2009. Candidates identified for the study were then mailed questionnaires to supplement data acquired from chart review. RESULTS: Most patients (73%; 95% confidence interval [CI], 65%-80%) experienced at least moderate improvement. This improvement persisted for at least 1 month in 66% of patients (95% CI, 57%-74%), with 18 patients (23%; 95% CI, 15%-33%) clear for over 1 year. Minimal adverse effects were reported, and most patients (63%; 95% CI, 52%-72%) stated that they would repeat GRT if available. CONCLUSIONS: Grenz ray therapy seems to be a safe and effective modality for chronic hand and foot dermatoses with some patients experiencing prolonged remissions. Grenz ray therapy, when available, should be considered before the use of systemic agents, which are often associated with higher costs and potential toxicities.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.002 | 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".