Hydroxychloroquine in Stage 1 Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: Innate immune responses may be involved in the earliest phases of type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS: To test whether blocking innate immaune cells modulated progression of the disease, we randomly assigned 273 individuals with stage 1 T1D to treatment with hydroxychloroquine (n = 183; 5 mg/kg per day to a maximum of 400 mg) or placebo (n = 90) and assessed whether hydroxychloroquine treatment delayed or prevented progression to stage 2 T1D (i.e., two or more islet autoantibodies with abnormal glucose tolerance). RESULTS: After a median follow-up of 23.3 months, the trial was stopped prematurely by the data safety monitoring board because of futility. There were no safety concerns in the hydroxychloroquine arm, including in annual ophthalmologic examinations. Preplanned secondary analyses showed a transient decrease in the glucose average area under the curve to oral glucose in the hydroxychloroquine-treated arm at month 6 and reduced titers of anti-GAD and anti-insulin autoantibodies and acquisition of positive autoantibodies in the hydroxychloroquine arm (P = 0.032). CONCLUSIONS: We conclude that hydroxychloroquine does not delay progression to stage 2 T1D in individuals with stage 1 disease. Drug treatment reduces the acquisition of additional autoantibodies and the titers of autoantibodies to GAD and insulin.
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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 | 0.001 | 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) | 0.002 | 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".