POLYPHARMACY AMONG PEOPLE LIVING WITH SYSTEMIC LUPUS ERYTHEMATOSUS
Notice bibliographique
Résumé
PV054 / #546 Poster Topic: AS06 - Comorbidities Background/Purpose Polypharmacy is known to be associated with adverse health outcomes in the general population. Recent studies have reported high rates of polypharmacy among people living with systemic lupus erythematosus (SLE). However, the relationship between polypharmacy and health outcomes in SLE remains unknown. This study aimed to 1) Identify demographic and clinical characteristics associated with polypharmacy; and 2) Determine the association between baseline polypharmacy and subsequent risk of mortality among people living with SLE. Methods This was a secondary analysis of data from a prospective observational cohort of adults with SLE followed at a single academic medical center between 2000 and 2021. All participants met the 1997 revised American College of Rheumatology (ACR) classification criteria for SLE and were assessed annually for medication use, disease activity (measured using the Systemic Lupus Erythematosus Disease Activity Index 2000 [SLEDAI-2K]), organ damage (measured using the SLICC/ACR Damage Index [SDI]), and other measures. The baseline visit for this analysis was defined as the first study visit for each patient at which data were available for all relevant variables. Polypharmacy was defined as the concurrent exposure to 5 or more medications at the baseline visit. Mortality was defined as any recorded death within the follow-up period. Chi-square tests and Wilcoxon rank-sum tests were used to assess the difference in baseline characteristics between those with vs without baseline polypharmacy. Cox proportional hazards regression was used to evaluate the association between baseline polypharmacy and subsequent mortality risk during follow-up. The multivariable model was adjusted for potential confounders, including baseline age, baseline SDI score, and baseline corticosteroid use. Results The 226 included patients (89.4% female) had a median (IQR) age of 45 (34-54) years and a median (IQR) disease duration of 10.0 (2.3-15.6) years at baseline. Polypharmacy was present in 134 patients (59.3%) at baseline. At baseline, polypharmacy was associated with increased age, higher SDI scores, corticosteroid use, immunosuppressive use, and frailty (Table 1). The Kaplan-Meier curves for mortality risk by baseline polypharmacy status are shown in (Figure 1). There was a significant association between baseline polypharmacy and mortality risk during follow-up in the unadjusted analysis (hazard ratio [HR] 4.16, 95% CI 1.93-8.97). After adjusting for baseline age, SDI score, and corticosteroid use, the association was no longer statistically significant (HR 2.02, 95% CI 0.87-4.71, p=0.10). Table 1. Baseline characteristics of SLE patients with versus without baseline polypharmacy. Figure 1. Kaplan-Meier survival curves for mortality risk during follow-up among SLE patients with baseline polypharmacy (in red) versus without baseline polypharmacy (in blue). Conclusions Among people living with SLE, baseline polypharmacy was associated with increased risk of mortality during follow-up, but these results were no longer statistically significant after accounting for potential confounders. Future research will aim to understand the association of polypharmacy with other health outcomes (eg, organ damage accrual), as well as the trajectories of polypharmacy and high-risk medication use over time in people living with SLE.
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 | 0,000 | 0,001 |
| 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 | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».