Leonardo Rios Diniz1, Sandor Balsamo2, Talita Yokoy de Souza3, Luciana Feitosa Muniz3, Wagner Rodrigues Martins4, Licia Maria Henrique da Mota5. 1. Univesidade de Brasília (UnB), Faculdade de Medicina, Programa de Pós-Graduação em Ciências Médicas, Brasília, DF, Brazil. Electronic address: lrdiniz@gmail.com. 2. Univesidade de Brasília (UnB), Faculdade de Medicina, Programa de Pós-Graduação em Ciências Médicas, Brasília, DF, Brazil. 3. Univesidade de Brasília (UnB), Hospital Universitário de Brasília, Serviço de Reumatologia, Brasília, DF, Brazil. 4. Univesidade de Brasília (UnB), Faculdade de Fisioterapia, Brasília, DF, Brazil. 5. Univesidade de Brasília (UnB), Faculdade de Medicina, Programa de Pós-Graduação em Ciências Médicas, Brasília, DF, Brazil; Univesidade de Brasília (UnB), Hospital Universitário de Brasília, Serviço de Reumatologia, Brasília, DF, Brazil.
Abstract
OBJECTIVE: To assess the prevalence of fatigue in a Brazilian population with early rheumatoid arthritis using multiple instruments, and the predictors of these instruments by differents independent variables. METHODS: Cross-sectional study with direct interview and medical records review. Fatigue, dependent variable, was assessed using eight instruments: Profile of Mood States (POMS), Multidimensional Assessment of Fatigue scale (MAF), Fatigue Severity Scale (FSS), Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire (BRAF-MDQ), Numerical Rating Scales (BRAF-NRS), Short-form Survey 36 (SF-36), Functional Assessment of Chronic Illness Therapy Fatigue Scale (FACIT-F) and Visual Analogic Scale for Fatigue (VASf). INDEPENDENT VARIABLES: sociodemographic, clinical and serological, were measured using medical records and direct interview. Disability and disease activity were assessed using the Health Assessment Questionnaire (HAQ) and disease activity assessed using the Disease Activity Score 28 joints (DAS28). The scores of scales demonstrated the level of fatigue and multiple linear regression method used in statistical analysis to demonstrate prediction models. RESULTS: A total of 80 patients was assessed, and 57 reported clinically relevant fatigue (VASf>2), representing 71.25% prevalence point (51 women [89.5%], mean age 48.35±15 years, and mean disease duration of 4.92±3.8 years). Eight predictive models showed statistical significance, one for each fatigue instrument. The highest coefficient of determination (R2) was 56% for SF-36 and the lowest (R2=21%) for FSS. The HAQ was the only independent variable to predict fatigue on all instruments. CONCLUSION: Clinically relevant fatigue is a highly prevalent symptom and is mostly predicted by disability and age in the population assessed.
OBJECTIVE: To assess the prevalence of fatigue in a Brazilian population with early rheumatoid arthritis using multiple instruments, and the predictors of these instruments by differents independent variables. METHODS: Cross-sectional study with direct interview and medical records review. Fatigue, dependent variable, was assessed using eight instruments: Profile of Mood States (POMS), Multidimensional Assessment of Fatigue scale (MAF), Fatigue Severity Scale (FSS), Bristol Rheumatoid Arthritis Fatigue Multidimensional Questionnaire (BRAF-MDQ), Numerical Rating Scales (BRAF-NRS), Short-form Survey 36 (SF-36), Functional Assessment of Chronic Illness Therapy Fatigue Scale (FACIT-F) and Visual Analogic Scale for Fatigue (VASf). INDEPENDENT VARIABLES: sociodemographic, clinical and serological, were measured using medical records and direct interview. Disability and disease activity were assessed using the Health Assessment Questionnaire (HAQ) and disease activity assessed using the Disease Activity Score 28 joints (DAS28). The scores of scales demonstrated the level of fatigue and multiple linear regression method used in statistical analysis to demonstrate prediction models. RESULTS: A total of 80 patients was assessed, and 57 reported clinically relevant fatigue (VASf>2), representing 71.25% prevalence point (51 women [89.5%], mean age 48.35±15 years, and mean disease duration of 4.92±3.8 years). Eight predictive models showed statistical significance, one for each fatigue instrument. The highest coefficient of determination (R2) was 56% for SF-36 and the lowest (R2=21%) for FSS. The HAQ was the only independent variable to predict fatigue on all instruments. CONCLUSION: Clinically relevant fatigue is a highly prevalent symptom and is mostly predicted by disability and age in the population assessed.
Authors: Laura S Castro; Tracy A Balboni; Talita C Lobo; Rita Simone L Moreira; Harold G Koenig; John R Peteet; Fatima Cintra Journal: J Relig Health Date: 2021-03-12