Frequency of adverse drug reactions in patients with systemic lupus erythematosus.
Bibliographic record
Abstract
OBJECTIVE: The literature suggests that patients with systemic lupus erythematosus (SLE) have a higher frequency of adverse drug reactions (ADR). We performed this case control study to compare the prevalence of ADR in patients with SLE and controls with inflammatory arthritis. METHODS: We surveyed 249 patients, 145 with SLE and 104 age and sex matched controls with other types of inflammatory arthritis, such as rheumatoid arthritis (RA), probable RA, and psoriatic arthritis. We asked about exposure and ADR to the following classes of drugs: (1) beta-lactam antibiotics, (2) sulfonamides, (3) other antibiotics, (4) disease modifying antirheumatic drugs (DMARD), and (5) nonsteroidal antiinflammatory drugs (NSAID). Personal and family atopic histories were obtained. The 2 groups were obtained from a single rheumatologic practice and had similar characteristics and drug exposures. RESULTS: The response rate was 63% in the SLE patients and 64% in the control group. The mean age was 47.8 +/- 1.5 years in patients with SLE and 46.1 +/- 1.7 years in controls (p < 0.51). Ninety-two percent of SLE patients and 88% of controls were female (p < 0.42). Both groups had been exposed similarly to all antibiotics, as there were no significant differences between groups (exposure to sulfa antibiotics 53% in SLE patients vs 46% in controls), and to NSAID (84% SLE group vs 93% controls). Few patients from the SLE group had DMARD exposure, with the exception of plaquenil (65% SLE group vs 30% controls; p < 0.0001) and azathioprine (18% SLE group vs 4% controls; p < 0.006). There were between-groups differences with respect to total number of ADR with sulfa antibiotics (exposed had 25/48 reactions in SLE group vs 6/31 in controls; p < 0.003), but not with other drugs. Most ADR to sulfa antibiotics were cutaneous (rash). Subjects with an allergic or atopic history had more ADR (p < 0.0005). There were no differences between SLE patients and controls in having an allergic history (p < 0.88). Subjects with a positive family history of allergies were more likely to have ADR (p < 0.0043). SLE patients and controls with a personal versus family history of environmental allergies did not differ in having ADR (p < 0.16 and p < 0.83, respectively). CONCLUSION: Both intolerances and true allergic reactions were not dissimilar in patients with SLE compared to controls with inflammatory arthritis, with the exception of cutaneous reactions to sulfa antibiotics in SLE patients. This has not been the experience of other investigators (with increased ADR with several antibiotics in SLE groups) who used healthy, best friend, and relative controls with dissimilar frequencies of drug exposures. Perhaps differences observed in the past (where SLE patients have more ADR than healthy controls) are true of other inflammatory arthritis subjects (who have different drug exposures than healthy individuals) rather than just SLE. Differences could also exist in the pharmacogenetics, as our sample population was mostly Caucasian.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".