Avaliação da prevalência e fatores associados à fragilidade em pacientes com diagnóstico de lúpus eritematoso sistêmico

Abstract

Introduction: The term frailty, over time, has been used into the vocabulary of other health professionals, as well as geriatricians and gerontologists, although there is no consensus on its use. Frailty can be synonymous with disability or dependence in activities of daily life, but recently, some authors have attempted to standardize its definition, using criteria to classify this syndrome. Previously, it was believed that she attacked solely elderly, but is now seen as something more complex and may be related to unfavorable outcomes, even in other age groups. Other age groups have been the target of research about the frailty, being related to chronic diseases such as obesity, chronic kidney disease, chronic obstructive pulmonary disease and cardiovascular disease. One hypothesis for the relationship between frailty and other diseases, even in young people, is an imbalance between the production of cytokines, leading to elevation of inflammatory markers, as well as an imbalance in the neuroendocrine system. These changes lead to a decrease in lean body mass with consequent sarcopenia, muscle weakness, exhaustion and physical inactivity. Knowing that lupus erythematosus (SLE) has the effect of pain, fatigue, bone loss and the use of immunosuppressive drugs in their treatment, especially corticosteroids, is believed to be a relationship between fragility and LES. The aim of this study was to evaluate the prevalence, clinical, laboratory and quality of life (QOL), associated with frailty in this population. Patients and Methods: We performed a cross-sectional study, which were all eligible patients seen by rheumatology clinic of the University Hospital of the Juiz de Fora Federal University. Inclusion criteria were: patients older than 18 years diagnosed with SLE according to the criteria established by the American College of Rheumatology and have signed the informed consent form. The inclusion criteria were: symptomatic patients from the standpoint osteomioarticular, pregnant women with diabetes mellitus, other autoimmune diseases, acute infectious diseases, viral hepatitis B and C and AIDS. The control group consisted of healthy subjects, matched for age, sex and body mass index (BMI). Sociodemographic, clinical and laboratory data as well as disease activity (SLEDAI) were collected from medical records. Frailty was assessed according to criteria adapted by Fried. Statistical analysis: We performed descriptive statistics, normality was evaluated by Shapiro and Wilk. Variables were described as mean ± standard deviation or percentage as the characteristic of each variable. The variables in the patient group and the control group were compared using the Student T test or χ2. The comparison between groups classified as frail, pre frail and non-frail were performed using ANOVA or χ2. The correlation of clinical, laboratory data and frailty syndrome were made by Pearson or Spearmman correlation. We calculated the odds ratio for frailty among groups and adopted the confidence interval equal to 95% (p ≤ .05). All analyzes were performed using the statistical package SPSS version 15.0. Results: We evaluated 33 patients and 26 controls. The prevalence of frailty was 7 (21%) in the group of patients and 0 (0%) in the control group, with a confidence interval (15.0). We also observed weak correlation between BMI (p = 0.01, r = -0, 041), SLEDAI (p = 0.01, r = 0.44), corticosteroid dose (p = 0.001, r = 0.56) and the number of immunosuppressants (p = 0.03, r = 0.37). Among the laboratory variables correlation between frailty and hemoglobin (p = 0.001, r = -0.56), serum globulin (p = 0.04, r = 0.35), ESR (p = 0.005, r = 0.47), CRP (p = 0.03, r = 0.37), IL6 ( p = 0.01, r = 0.43) and tendency related to serum calcium (p = 0.06, r = -0.036) and ANA (p = 0.08, r = 0.30). When evaluating the SF-36 and the classification of Frailty in SLE patients, we realized that only the State General health was statistically significant (p = 0.001), while Pain and Vitality tended to values (p = 0.073) and ( p = 0.090). Regarding body composition, we observed that patients with SLE and frail had higher average lean mass with less body fat compared to other groups: BMI not fragile: 30.38 kg/m2, pre-frail and 27.76 kg/m2 fragile 21.70 kg/m2 (p = 0.049), body fat percentage is not fragile: 39.56%, 39.57% pre-frail and frail 30.01% (p = 0.009), percent lean mass not fragile: 55.12%, 55.64% pre-frail and frail 65.56% (p = 0.008). Conclusion: We conclude that there was a higher prevalence of frailty syndrome in patients than in controls (0 (0%) among controls and 7 (21.21%) among patients), mainly associated with inflammatory markers (VHS, p = 0.011, PCR, p = 0.053 and IL-6, p = 0.041). The evaluation of this sample also allowed Frailty, a broader patient's assessment of the areas proposed in quality of life by SF-36 alone. About the data on body composition is noteworthy that these do not corroborate those seen previously in the literature. However we emphasize the low representativeness of the sample to evaluate this parameter and the need for a randomized prospective study to monitor the possible outcomes.