Retinal Complications in Patients with Systemic Lupus Erythematosus Treated with Antimalarial Drugs
Bibliographic record
Abstract
OBJECTIVE: Hydroxychloroquine (HCQ) and chloroquine (CQ) are key drugs in systemic lupus (SLE) and related diseases. Retinal toxicity remains the most worrisome complication. We studied factors potentially associated with retinal toxicity, using case-control analyses. METHODS: Within our SLE clinic cohort, we identified patients with retinal changes using the Systemic Lupus International Collaborating Clinics Damage Index. We confirmed HCQ/CQ retinopathy with chart review, and selected up to 3 SLE controls for each case, matched by age at SLE diagnosis and SLE duration. RESULTS: Over an average 12.8 years of followup, within 326 patients exposed to antimalarial drugs, 18 (5.5%) developed retinal toxicity. The minimum number of years of HCQ/CQ exposure before retinopathy developed was 8 years (maximum 33 yrs). Median HCQ/CQ duration was statistically similar in cases [19 yrs, interquartile range (IQR) 14-20] and controls (16 yrs, IQR 11-22), likely due to our matching on SLE duration. Versus controls, cases tended to have more renal disease (cases 22.2%, controls 14.8%) and were slightly less likely to be white (cases 61.1%, controls 74.1%), but neither variable reached statistical significance. Among patients with retinal toxicity, the number previously exposed to CQ was more than 3 times that in controls. CONCLUSION: Just over 5% of patients developed antimalarial retinal complications, over an average of 12.8 years. No cases were detected in the first 5 years of therapy. Past CQ use was more common in cases versus controls. Future studies using larger cohorts are under way to better define the roles of therapy duration, race/ethnicity, and other factors.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".