Chronic Respiratory Failure

The aim of the data collection is to create an advanced reliable method to remotely monitor patient on chronic home non-invasive ventilation (NIV), both regarding ventilatory efficacy and patient comfort, both in the hospital and at home by assessing gas exchange, lung mechanics and the interaction between the patient and the ventilator. For this purpose, we will set-up of databank of synchronously acquired datasets of already standard care monitored parameters during NIV (transcutaneous monitoring of gas exchange; ventilator data including data on PVA), and newly non-invasively acquired data on patient effort (EMG, patient ratings) and lung (hyper)inflation (EIT), during the set-up and follow-up of standard care chronic NIV.

Amyotrophic lateral sclerosis (ALS) is a disease that causes weakness of the muscles of the body. The disease can eventually lead to severe breathing problems, which is the most common cause of death from ALS. The treatment for breathing is non-invasive ventilation (NIV). It is a machine that helps a person breathe by pushing air in and out of their lungs through a mask worn over the face. Research has shown that NIV can improve the quality of life and survival of someone with ALS. Unfortunately, NIV is not equally beneficial for everyone. The investigators do not yet know the best time or method for starting NIV in ALS. Europe and Canada allow starting NIV much earlier in ALS than the United States. Current recommendations for starting NIV are based on the opinion of experts rather than large research studies. Medical insurance companies will not cover NIV until significant breathing weakness occurs. After NIV is started, there is no evidence-based guidance on the best way to adjust NIV to benefit patients as much as possible. Some patients have difficulty tolerating NIV, but it is not clear how to identify these individuals ahead of time. The investigators have created a new prediction tool that can identify patients at high risk of breathing problems within the next 6 months. This may help the study team identify who is more likely to benefit from starting NIV early. The investigators have published a paper that shows that NIV helps people with ALS live longer. This paper also showed that patients get more benefit with use NIV for at least 4 hours per day. The investigators published another paper that measured a gas called carbon dioxide (CO2), which goes high if someone's breathing is weakened. This paper showed that patients with ALS may live longer when CO2 levels are lowered using NIV. The investigators also have data suggesting that certain characteristics may predict who is less likely to use NIV at least 4 hours per day. In this study, the investigators will collect pilot data on starting early NIV in individuals with ALS who do not yet meet insurance criteria for covering NIV. The research team will first use their previously published prediction tool to identify patient risk. Then, subjects would be randomized to start early NIV or to usual care. The usual care group would eventually start NIV as would occur if the participants were not in the study. The purpose of this study is to collect data to help the investigators plan a larger randomized clinical trial. This study has 4 objectives. First, the project aims to identify individuals who would benefit from earlier NIV. The research team will use the original prediction tool to identify risk of severe breathing problems within the next 6 months. Second, the project aims to show that it is feasible to start NIV early. Third, the project aims to gather data on the effect of randomization on symptoms, CO2 levels, and outcomes. Fourth, the project aims to identify traits that may make someone less likely to use NIV.

The aim of this multicenter crossover trial is to describe the effect of adding a therapeutic dose of exertional oxygen therapy, in terms of exercise performance, gas exchange, heart rate, symptoms perception and subjective easiness of performance, in a cohort of subjects hospitalized in specialized pulmonary rehabilitation centers with a diagnosis of chronic respiratory failure and/or exertional hypoxemia due to chronic obstructive pulmonary disease or interstitial lung disease. Researchers will compare the walking performance during 6-minute walk test performed with the liters of oxygen administered as prescribed at rest (for patients with chronic respiratory failure) or in room air (for patients with exertional hypoxemia only), to the performance during a 6-minute walk test performed with the double the flow rate prescribed at rest, or with 2 L/min for patients with exertional hypoxemia only. The two tests will be performed in random order, at least 3 hours apart and no later than 24 hours apart from each other. The main outcome will be the difference between the distance walked in the two 6-minute walk test in the two conditions. Furthermore, will be also collected and compared: the oxygen saturation and heart rate every minute, the initial and final dyspnea and fatigue, as assessed by Borg scale, and the easiness of performance through a dedicated questionnaire. The estimated sample size will be 114 patients. This study will provide some basis for a more accurate prescription of exercise-related oxygen therapy, offering insights into the phenotype of patients who may derive the greatest benefit from this intervention. It will also stimulate discussion regarding the optimal timing and dosing of oxygen administration during exertion in patients with respiratory failure.

This study aims to evaluate the psychometric properties, including reliability and validity, of the Turkish version of the Severe Respiratory Insufficiency Questionnaire for Non-Invasive Ventilation (S3-NIV). The S3-NIV is a specific tool designed to assess difficulties and compliance in patients receiving home non-invasive ventilation. A total of 120 stable patients using home NIV for at least 3 months will be enrolled across multiple centers.

Study of the applicability of machine learning tools in detecting inspiratory leakage in longterm non-invasive ventilation. The study was conducted in two stages. Firstly the ML model was trained on both bench model created scenarios and then ten patients. And secondly the success of the model was assessed in a proof of concept pilot study of ten patients.

This research will study whether noninvasive ventilation (NIV) used to treat chronic respiratory insufficiency in patients with amyotrophic lateral sclerosis (ALS) can be initiated as successfully in the outpatient setting as in the conventional inpatient setting, and what the costs of these alternative initiation methods are.

Currently, there is no holistic solution for patients with respiratory diseases that includes oxygenation and management of a patient with respiratory disease, combining dynamic and automatic O2 administration and the detection of clinical worsening, generating a diagnostic suspicion, a management proposal, and notifying the medical team. For device validation, prospective studies will be conducted in patients in respiratory intermediate care units, conventional hospitalization, during physical activity in the hospital setting, and in an out-of-hospital setting. The device will be evaluated in terms of oxygenation efficacy, response time, patient safety, efficiency, versatility, clinical benefit, and adaptability.

This study is testing whether a new type of home oxygen therapy, called high-flow nasal cannula (HFNC), can improve breathing comfort and quality of life for people with long-term lung or heart conditions who need oxygen after leaving the hospital. HFNC delivers warm, humidified oxygen at higher flow rates than standard oxygen therapy, which may reduce shortness of breath, improve sleep, and make daily activities easier. The therapy will be provided using the myAirvo™3 device, which also allows doctors to check patients' oxygen levels, heart rate, and symptoms remotely. All patients will also wear a small device (RootiREX) to monitor heart rhythm, sleep quality, and detect breathing pauses at night. Participants will try both treatments - HFNC and standard oxygen therapy - for short periods, in random order, so that researchers can directly compare the effects within the same patient. Each treatment period will last two weeks, with a short break in between. The main goal of the study is to see whether HFNC reduces shortness of breath (measured by the modified Medical Research Council scale). Other outcomes include comfort, sleep quality, quality of life, oxygen levels, and how well patients are able to use the devices at home. The study will last six weeks in total for each participant. Researchers expect that HFNC will improve breathing comfort, stabilize oxygen levels, and reduce the need for hospital visits during this time.

The study is a multicentric prospective randomised cross-over study. It evaluates the compatibility of patients with the device without altering the routine treatment applied. During this evaluation, either the clinician-adjusted values on the device or the standard pre-set values are used to obtain hourly and 30-minute PVA (Patient Ventilator Asynchrony) recordings. These recordings will be analysed offline to identify the settings used and to compare the hourly and 30-minute PVA (Patient Ventilator Asynchrony) values when synchronisation is automatically set. The relationships and differences between these values will be analysed. For this purpose, the IntelliSync+ option, already available on the device, will be used. This software continuously analyses waveform signals at least a hundred times per second. This allows for the immediate detection of patient efforts and the initiation of inspiration and expiration in real time, thereby replacing traditional trigger settings for inspiration and expiration. If the patient is already synchronised with this option, it will then be possible to switch to traditional synchronisation settings for comparison. Statistical analyses will be conducted using SPSS 24.0, JASP (Just Another Statistical Programme), Jamovi ( fork of JASP), or R software. Initially, all numerical and categorical data will be evaluated using descriptive statistical methods. The distributions of numerical variables will be examined using visual (histograms and probability plots) and analytical methods (Kolmogorov-Smirnov/Shapiro-Wilk tests). Mean/SD (standard deviation) or median/interquartile range (IQR) will be used as measures of distribution. For comparing numerical data that follows a normal distribution, the Student-t test will be used, and for non-normally distributed data, the Mann-Whitney U or Wilcoxon signed-rank tests will be employed. PVA (Patient Ventilator Asynchrony) values will be statistically compared. For the analysis of categorical data, the Chi-Square test will be applied. Bayesian analysis may also be used as necessary during the writing of the study. The results obtained will be interpreted and reported by the researchers. Results with a "p" value below 0.05 will be considered statistically significant.