Treatment of Atopic Dermatitis Using a Full-Body Blue Light Device (AD-Blue): Protocol of a Randomized Controlled Trial
Bibliographic record
Abstract
BACKGROUND: Irradiation with visible blue light (wavelength 400-495 nm) is a promising, effective, and safe new treatment option for chronic inflammatory skin diseases such as psoriasis and atopic dermatitis. OBJECTIVE: We will perform a multicenter, placebo-controlled, double-blinded, 3-armed, prospective, randomized controlled trial to investigate the efficacy and safety of full-body blue light devices (wavelengths: 415 nm and 450 nm) compared with that of placebo irradiation for the treatment of atopic dermatitis. METHODS: We are planning to enroll a total of 150 patients at the University hospitals in Göttingen (Germany), Marburg (Germany), and Geneva (Switzerland). RESULTS: The trial was approved by the lead ethics committee of the medical faculty of the University of Göttingen (21/11/16). Further approvals were obtained from local and federal authorities (ethics committee Marburg, Cantonal Commission for Research Ethics Geneva, Suisse Medic, and Bundesinstitut für Arzneimittel und Medizinprodukte). CONCLUSIONS: We will disseminate the results in a peer-reviewed journal. TRIAL REGISTRATION: ClinicalTrials.gov NCT03085303; https://clinicaltrials.gov/ct2/show/NCT03085303 (Archived by WebCite at http://www.webcitation.org/73ucqkkA1). INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/11911.
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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 | 0.034 | 0.028 |
| Meta-epidemiology (narrow) | 0.006 | 0.002 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.008 | 0.007 |
| Insufficient payload (model declined to judge) | 0.049 | 0.009 |
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".