Frequency of adverse drug reactions in patients with systemic lupus erythematosus.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».