Sex differences in frailty and its association with low bone mineral density in rheumatoid arthritis
Notice bibliographique
Résumé
ABSTRACT Frailty in the general population is associated with poor health outcomes including low bone mass and osteoporotic fracture. The relationship between frailty and low bone mineral density (BMD) in rheumatoid arthritis (RA) is unknown. This study examined associations between frailty and BMD in RA, controlling for established osteoporosis risk factors. Methods: We performed a cross-sectional analysis of a longitudinal RA cohort (n = 138; 117 female, 21 male). Participants fulfilled ACR RA classification criteria. Frailty was evaluated using the Fried Index, categorizing each participant as robust, pre-frail or frail. To identify independent predictors of BMD, we performed a multivariable linear regression analysis. Because risk factors for low BMD differ between sexes, we performed additional sex-stratified multivariable analyses. Results: Mean age and disease duration were 58.0 ± 10.8 and 19 ± 10.9 years, respectively. The majority of participants were categorized as pre-frail (70%) or frail (10%). Females had higher rates of frailty than males. In the whole cohort, both pre-frail and frail had independent negative associations with BMD (β = −0.074 and −0.092 respectively, p < 0.05). In sex-stratified analyses, frailty did not have a significant association with BMD in females, but had a strong independent negative association in males (β = −0.247, p = 0.001). Conclusion: Frailty was associated with BMD in patients with RA. Females had higher rates of frailty than males, yet frailty was independently associated with BMD in males but not in females. Frailty appears to be an important factor associated with low BMD; sex may influence this relationship in RA. Frailty, defined as “an excess of vulnerability to stressors” with a lack of resilience after a stressful event, is an important consideration in the management of patients with chronic illnesses (Walston et al., 2006). Frailty is associated with increased mortality independent of comorbid conditions (Walston et al., 2006; Fried et al., 2001). Both frailty and rheumatoid arthritis (RA) are independently associated with osteoporotic fractures, which lead to considerable morbidity and mortality (Book et al., 2009; Staa et al., 2006; Ensrud et al., 2007). To date, few investigators have examined the rates and consequences of frailty in RA. Previous studies have found frailty was associated with higher disease activity scores and that frailty occurs both at a younger age and at a higher prevalence in RA than in non-RA geriatric cohorts (Chen et al., 2009; Salaffi et al., 2019; Andrews et al., 2017; Haider et al., 2019). Prior to this year, the association between frailty and osteoporosis in RA had been unstudied. A recent Canadian registry-based study by Li et al., found that frailty measured by a Rockwood-type patient-reported index (Rockwood et al., 2005), was associated with a hospital visit for fracture in persons with RA (Li et al., 2019). The study by Li et al. was foundational, yet it had limitations. The frailty index used was developed ad hoc, and therefore, was not validated against accepted frailty measures, and Li et al. were unable to control for bone mineral density (BMD) (Li et al., 2019). The aim of the current study was to explore the association of frailty and osteoporosis in RA further, by evaluating a cohort of RA. Keywords: Frailty Bone mineral density Sex differences Body composition
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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) | 0,002 | 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 ».