Analysis of Breathing Pattern Post COVID-19

Shirley Lima Campos100 enrolled

Overview

The COVID-19 pandemic, a disease caused by the SARS-CoV-2 virus, has generated an inexplicable scenario for global health, causing different complications and degrees of functional impairment in millions of people who manage to recover from the disease. The respiratory system is the main system to be directly impacted during COVID-19 infection, and its treatment can generate changes in the respiratory function of individuals surviving the exacerbation of the disease, which may promote subjective and quantitative changes in the respiratory pattern, requiring an evaluation with high-cost instruments, an evaluation necessary to outline a better planning therapeutic for this population. The goal of this study is evaluate the breathing pattern variables using a device called RESPIRATORY DIAGNOSTIC ASSISTANT (RDA) and verify the relationship between the breathing pattern variables with the variables of pulmonary function, respiratory muscle strength and respiration in patients after involvement by COVID-19. This is a observational and validation study, prospective with follow-up of respiratory function for 6 months, a subproject linked to the project already approved by the research ethics committee under opinion: 4.362.977/4.596.02. Data collection will be carried out in a single day and divided into a few steps that will take place at the cardiopulmonary physiotherapy laboratory located at the physiotherapy department of the Federal University of Pernambuco. The first step is to conduct an interview with the participants to collect clinical data and perform a physical examination. Subsequently, a multidimensional evaluation of respiratory function will be performed. Statistical analysis will be performed using the Statistical Package For Social Science (SPSS) software version 20.0 for Windows. The Kolmogorov-Smirnov test will be used to verify the type of distribution, regarding the normality of the variables, and the significance level adopted will be 95% (α \<0.05) for all analyses. Finally, the data obtained will be presented in tables and/or graphs.

The sample will consist of volunteers with laboratory confirmed COVID-19 results who have SARS COV 2 variants tracked by the epidemiological surveillance of Caruaru-Pernambuco and will be recruited by coexistence in a non-probabilistic way. The sample study will be obtained through data provided by the municipal health department of the city of Caruaru-Pernambuco with a predicted sample of 131 people. In order to minimize sample losses, 10% will be added to the total sample, which corresponds to 144 participants. The software that can be used is known as GPower (version 3.13 for Windows) considering a statistical power (β) of 80% and a significance level (α) of 5%.

Eligibility

Sex: ALLMin age: 18 YearsMax age: 100 Years

Medical Language ↔ Plain English

Inclusion Criteria: * Older than 18 years; * Diagnosed with COVID-19; * After the period of home isolation or hospital discharge; * More than 40 days without the presence of symptoms associated with COVID-19; Exclusion Criteria: * Participants who are unable to perform the assessment tests or who present contraindications to the assessment of respiratory function; * Those patients who prove reinfection by the new Coronavirus; * Pregnant patients; * Refusal to sign the Free and Informed Consent Form (FICF)

Outcomes

Primary Outcomes

Breathing pattern diagnosis

The algorithm of the "Respiratory Diagnostic Assistant" device relates the variables respiratory rate, tidal volume, minute volume, inspiratory flow, expiratory flow, relationship between inspiratory and expiratory times, providing classification of breathing pattern during rest breathing. The "Respiratory Diagnosis Assistant" algorithm provides through graphs allowing the classification of the diagnosis in normal or altered. * Normal breathing pattern described in frequency of cases. It is defined no changes by the algorithm of the "Respiratory Diagnostic Assistant". * Altered breathing pattern described in frequency of cases. It is defined by changing the breathing pattern variables captured by the flow sensor of the "Respiratory Diagnostic Assistant" device during breathing at rest.