Retinopathy in the Era of Routine Hydroxychloroquine Monitoring
Bibliographic record
Abstract
To the Editor: Hydroxychloroquine (HCQ) is a vital component of systemic lupus erythematosus (SLE) treatment, but it carries a significant risk of irreversible blindness from HCQ retinopathy. HCQ retinopathy is relatively rare, but new, more sensitive diagnostic techniques report a prevalence of up to 7.5%1. Moreover, HCQ retinopathy may progress even after cessation of therapy2, so early detection and primary prevention are critical. Currently, primary prevention consists of controlling the daily dose and/or cumulative dose to prevent overdosage3. We therefore read with great interest “Hydroxychloroquine Blood Levels in Systemic Lupus Erythematosus: Clarifying Dosing Controversies and Improving Adherence” by Durcan, et al 4 in The Journal of Rheumatology . We point out the implications of their findings for the use of weight-based dosing and the evidence base for HCQ retinopathy prevalence. In their study, Durcan, et al described how regularly measuring blood levels of HCQ in patients with SLE resulted in a higher … Address correspondence to E. Weinlander, Department of Ophthalmology and Visual Sciences, University of Wisconsin-Madison, 2870 University Avenue, Suite 206, Madison, Wisconsin 53705, USA. E-mail: eweinlander{at}wisc.edu
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.010 | 0.010 |
| Insufficient payload (model declined to judge) | 0.002 | 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".