Antimalarials as a risk factor for elevated muscle enzymes in systemic lupus erythematosus
Bibliographic record
Abstract
OBJECTIVE: To investigate the relationship between antimalarials (AM) and elevated muscle enzymes in systemic lupus erythematosus (SLE). PATIENTSMETHODS: 325 lupus patients with abnormal creatine phosphokinase (CPK) for at least two consecutive clinic visits were enrolled; 54 patients on statins/fibrates (n = 43) and/or active myositis (n = 14) were excluded. The control group consisted of 1453 lupus patients with no CPK elevation during follow-up. Descriptive statistics and Cox regression analyses were performed, p < 0.05 was considered significant. RESULTS: Cases and controls did not differ regarding age at SLE diagnosis, gender ratio, or disease duration. AM use was more frequent in cases, which had more prolonged AM use. Total frequency of elevated CPK in AM users was 216/1322 (16.3%). Chloroquine was associated with a 3.3-fold, and hydroxychloroquine with a 3.1-fold, increased risk for CPK elevation. Black race was associated with higher CPK (HR = 2.941), whereas female gender was protective (HR = 0.697). 203 patients were followed for 7.3 ± 5.6 years; 49.8% had persistent and 14.8% intermittent CPK elevation, while in 35.4% CPK was normalized. Clinical proximal muscle weakness developed in 5/203 patients. CONCLUSIONS: Chronic AM use is a potential risk factor for muscle enzyme elevation in SLE patients. CPK abnormalities persist in almost two thirds of the patients, but this remains mainly a biochemical finding, evolving to clinical myopathy in about 2.5%.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".