Complexity of the Airflow in COPD

Study Overview
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Brief Summary
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Recently, there has been a growing interest in the study of nonlinear dynamics as a methodology for complementary analysis to characterize the respiratory pattern. These methods are well established in studies of heart rate. The analyzes evaluate complex signals, including large-scale fractal correlations and distributions in time series, and can provide relevant clinical information. Measures such as approximate entropy and sample entropy have shown great potential in the evaluation of the complexity of the respiratory system, providing information relevant to the understanding of physiological and pathophysiological processes. These measures are based on the concept of non-linearity in the presence of a high number of interconnections, resulting in the complex behavior exhibited by physiological systems. The approximate entropy (ApEn) is related to the amount of clutter, complexity or unpredictability of a data series over time. In a complementary way, the sample entropy (SampEn), is a far more elaborate than the ApEn, to reduce possible biased estimates due to self-similarity. A study conducted by our group in asthma patients with different levels of bronchial obstruction demonstrated a significant reduction in airflow approximate entropy (ApEnV´) in asthmatic subjects. Investigators believe that in COPD, similar to that which occurs in asthma disorders that are associated with complex changes in the pathophysiology triggering breath control, possibly resulting in changes in air flow (V´). Considering the development silent changes of mechanical ventilation in COPD patients and its clinical relevance, as well as the difficulty of identifying such changes through conventional methods, we observed the need to obtain more detailed information, including the complexity of the system breathing for better understanding of factors that contribute to the illness. In this context, the objectives of this study were: (1) analyze the influence of airway obstruction in the complexity of the patterns of airflow in patients with COPD, (2) evaluate the diagnostic power of the test in identifying the changes caused by COPD.

Official Title
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Complexity of the Airflow at Different Levels of Bronchial Obstruction of COPD.

Conditions
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COPD

Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: volunteers with COPD for Patients Group; volunteers without any respiratory disease for the control group. Exclusion Criteria: individuals with history of tuberculosis or other lung disease, heart disease in general and disability in the exams.

Ages Eligible for Study
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Minimum Age: 40 Years
Maximum Age: 90 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Control group<br>Group of nonsmokers individuals without respiratory disease. | |
| NE<br>Smokers wiht normal spirometry. | |
| LV<br>Patients with COPD level I, mild. | |
| MOD<br>Patients with COPD level II, moderate. | |
| GV<br>Patients with COPD level III, severe. | |
| MGV<br>Patients with COPD level IV, very severe. | |

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Respiratory Impedance in Different Phases of the Cycle Ventilation in Patients with Chronic Obstructive Pulmonary Disease | The aim of the study was to analyze the changes in the respiratory system impedance (Zrs) in the different phases of the respiratory cycle of patients with Chronic Obstructive Pulmonary Disease (COPD). This research was conducted using a monofrequency version of the forced oscillation technique (mFOT) and consisted of a controlled observational study where 31 individuals were analyzed, 8 controls and 23 individuals with COPD. The patients presented different degrees of airway obstruction. | up to 3 years | 

 Terms related to the study
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Keywords Provided by Centre Hospitalier Valida
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COPD, Complexity, Entropy Sampling, Variability, Respiratory Mechanics, FOT