P183 Cognitive function in polymyalgia rheumatica
Notice bibliographique
Résumé
Abstract Background/Aims Over the past decade our understanding of the prevalence, and indeed impact, of cognitive impairment in rheumatic diseases has increased. An aging population coupled with systemic inflammation have been postulated as key drivers of increased cognitive decline in these conditions. Intact cognitive function is imperative not only for quality of life and maintenance of one’s functional capacity, but also for the successful therapeutic management of disease, namely the adherence to treatment regimens. The prevalence of cognitive impairment in community dwelling adults above the age of 65 in Ireland has been estimated at 13%.1 To date, the prevalence of cognitive impairment in PMR has not been studied. The aim of this research is therefore to explore the prevalence and potential associated factors of cognitive impairment in those with PMR. Methods Patients with a diagnosis of PMR (fulfilling the 2012 EULAR/ACR Provisional Classification Criteria) who were in clinical remission and on active treatment with glucocorticoids were recruited from two centres. Patients were >3 months and <12 months from diagnosis. Cognitive function was evaluated using the Montreal Cognitive Assessment (MoCA) test which was conducted by trained interviewers. Cognitive impairment was defined by the previously validated MoCA cut-off score of < 26. Demographics, clinical and laboratory data, in addition to patient reported outcomes (PROs) were collected. PROs included anxiety using the Generalised Anxiety Disorder Assessment (GAD-7), mood using the Patient Health Questionnaire (PHQ-9), fatigue using the Functional Assessment of Chronic Illness Therapy-Fatigue Scale (FACIT-F), pain using the visual analogue scale (VAS) and overall health-related quality of life using the Health Assessment Questionnaire-Disability Index (HAQ-DI). The associations between categorical variables were compared using the -test or Fishers exact test. The association between continuous variables and categorical variables were assessed using the Kruskal-Wallis test. Correlations were calculated using Pearson’s r. All analyses were conducted using R (R Core Team, 2022). A p-value of < 0.05 was considered as statistically significant. Results 51 consecutive patients with PMR were recruited, of which 56.9% (n = 29) were female. 70.6% (n = 36) of patients were cognitively impaired, with visuo-spatial, delayed recall and abstraction the most commonly affected cognitive domains. Interestingly, those with cognitive impairment had a younger age, versus those without (p = 0.514). Although not statistically significant, median BMI, anxiety, depression and pain scores were all higher in those who were cognitively impaired. Moreover, median fatigue scores were also worse in the cognitively impaired group. No statistically significant difference in serum markers was observed. Conclusion This study demonstrates that the burden of cognitive impairment in PMR is significant, and is markedly higher than that observed usually at population level. Future studies exploring specific etiologic contributors are needed. Disclosure P. Harkins: Grants/research support; British Society for Rheumatology. S. Cowley: None. R. Harrington: None. D. Kane: None. R. Conway: None.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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) | 0,001 | 0,001 |
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 tête enseignante, 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 ».