Identification and Prediction of Fatigue Trajectories in People With Rheumatoid Arthritis.

Objective: We aimed to identify groups demonstrating different long‐term trajectories of fatigue among people with rheumatoid arthritis and determine baseline predictors for these trajectories. Methods: Our study included 2741 people aged 18 to 75 years who were independent in daily living. Data wer...

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Publicado en:ACR Open Rheumatology Vol. 4; no. 2; pp. 111 - 119
Autores principales: Pettersson, Susanne, Demmelmaier, Ingrid, Nordgren, Birgitta, Dufour, Alyssa B., Opava, Christina H.
Formato: Journal Article
Publicado: Wiley-Blackwell Feb2022
Acceso en línea:Ver este registro en EBSCOhost
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      jtl: ACR Open Rheumatology
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      dt: Feb2022
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      pub: Wiley-Blackwell
      place: Malden, Massachusetts
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        155235476
        153488040
        10.1002/acr2.11374
        155235476
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        atl: Identification and Prediction of Fatigue Trajectories in People With Rheumatoid Arthritis.
      aug:
        au:
          Pettersson, Susanne
          Demmelmaier, Ingrid
          Nordgren, Birgitta
          Dufour, Alyssa B.
          Opava, Christina H.
        affil: Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
      sug:
      ab: Objective: We aimed to identify groups demonstrating different long‐term trajectories of fatigue among people with rheumatoid arthritis and determine baseline predictors for these trajectories. Methods: Our study included 2741 people aged 18 to 75 years who were independent in daily living. Data were collected from the Swedish Rheumatology Quality Register and questionnaires at baseline, 14 months, and 26 months. Fatigue was rated on a 100‐mm visual analog scale. K‐means cluster analysis was used to identify fatigue trajectories. Multinomial logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals for potential predictors of trajectory membership. Results: The mean age was 60 years, 73% of participants were female, and the mean baseline fatigue level was 39. Three distinct fatigue trajectories were identified, representing mild (mean 15, n = 1024), moderate (mean 41, n = 986), and severe (mean 71, n = 731) fatigue. Consistent patterns indicated that poorer health perception (ORs 1.68‐18.40), more pain (ORs 1.38‐5.04), anxiety/depression (ORs 0.85‐6.19), and activity limitation (ORs 1.43‐7.39) were associated with more severe fatigue. Those in the severe fatigue group, compared with those in the mild fatigue group, were more likely to be college educated than university educated (OR 1.56) and less likely to maintain physical activity (OR 0.54). Those in the severe fatigue group, compared with those in both the moderate (OR 0.67) and mild (OR 0.59) fatigue groups, were less likely to have one additional adult in the household. Conclusion: This study identified stable fatigue trajectories, predicted by health perception, pain, anxiety/depression, activity limitation, educational level, maintained physical activity, and household composition. Interventions aimed at reducing these disabilities and supporting physical activity behaviors may help reduce fatigue.
      pubtype: Academic Journal
      doctype: Journal Article
      ougenre: Article
    language: English
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