Identification of phenotypes in COPD patients: influence of physical activity in daily life, body composition and skeletal muscle dysfunction

• Grant number: 13/20676-9
• Support type: Scholarships in Brazil - Doctorate
• Effective date (Start): May 01, 2014
• Effective date (End): October 31, 2017
• Field of knowledge: Health Sciences - Physiotherapy and Occupational Therapy
• Principal researcher: Celso Ricardo Fernandes de Carvalho
• Grantee: Rafaella Fagundes Xavier
• Home Institution: Faculdade de Medicina (FM). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

Introduction: The chronic obstructive pulmonary disease (COPD) has systemic repercussions that negatively influence disease progression and increase mortality in these individuals. The physical activity level (PAL) and peripheral muscle strength have been widely shown to be cause of morbidity and mortality in patients with COPD, however phenotypes previously described in the literature include these factors as a determinant of phenotypes. Objectives: To identify individuals with COPD phenotypes in considering the level of physical activity in daily life, body composition and skeletal muscle dysfunction. Methods: This study will evaluate 300 patients with moderate to severe COPD and evaluations will be conducted on 2 separate days, and on day 1st there will be an initial assessment including lung function (spirometry), the clinical management of COPD (CCQ), the factors health-related quality of life (CRQ) and symptoms of dyspnea (MRC). At the end of the 1st day of evaluation, the patient will receive an accelerometer (Actigraph) for assessment of physical activity level (PAL) in daily life. After 8 days, patients return to the hospital to return the accelerometer and will assess the strength of skeletal muscles (isometric maximum) and body composition (bioimpedance) (2nd day of evaluation). After 3, 6, 9 and 12 months of these ratings, subjects will be assessed for the presence of exacerbations and hospitalizations. Statistical analysis: There will be a single cluster analysis in order to identify phenotypes in COPD. For continuous variables (age, isometric strength, and physical activity level) will select those to be included in the cluster analysis, the aim of excluding the investigated variables that show a correlation with other in order to select only the main variables. For categorical variables (FEV1, MRC, CCQ and body composition) will be subjected to a multiple correspondence analysis to transform them into mathematical independent axes. Following this procedure will be allowed to use a single cluster analysis (Ward analysis). The data are presented as median and interquartile range 10% -90% and the significance level will be set for all analysis will be 5% (p <0,05). The analyzes will be performed using SPSS version 17.0 (Chicago SPSS. Inc. III).

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

PEREIRA, ANA CAROLINA A. C.; XAVIER, RAFAELLA F.; LOPES, ALINE C.; DA SILVA, CIBELE C. B. M.; OLIVEIRA, CRISTINO C.; FERNANDES, FREDERICO L. A.; STELMACH, RAFAEL; CARVALHO, CELSO R. F. The Mini-Balance Evaluation System Test Can Predict Falls in Clinically Stable Outpatients With COPD A 12-MO PROSPECTIVE COHORT STUDY. Journal of Cardiopulmonary Rehabilitation and Prevention, v. 39, n. 6, p. 391-396, NOV 2019. Web of Science Citations: 0.

LOPES, ALINE C.; XAVIER, RAFAELLA F.; PEREIRA, ANA CAROLINA A. C.; STELMACH, RAFAEL; FERNANDES, FREDERICO L. A.; HARRISON, SAMANTHA L.; CARVALHO, CELSO R. F. Identifying COPD patients at risk for worse symptoms, HRQoL, and self-efficacy: A cluster analysis. CHRONIC ILLNESS, v. 15, n. 2, p. 138-148, JUN 2019. Web of Science Citations: 0.

XAVIER, RAFAELLA F.; PEREIRA, ANA CAROLINA A. C.; LOPES, ALINE C.; CAVALHERI, VINICIUS; PINTO, REGINA M. C.; CUKIER, ALBERTO; RAMOS, ERCY M. C.; CARVALHO, CELSO R. F. Identification of Phenotypes in People with COPD: Influence of Physical Activity, Sedentary Behaviour, Body Composition and Skeletal Muscle Strength. Lung, v. 197, n. 1, p. 37-45, FEB 2019. Web of Science Citations: 0.