Active clinical trials for "Respiratory Distress Syndrome"

A prospective cohort study aims to evaluate the predictive value of thoracic fluid content measured by electric bioimpedance for detecting the need for surfactant administration or positive pressure ventilation requirement; whether invasive or non-invasive; in preterm neonates with respiratory distress and to compare it to lung ultrasound.

This study will seek to enroll neonates requiring Nasal Continuous Airway Pressure (NCPAP) respiratory support and randomize them to either oscillatory (Osc-NCPAP, study group) or non-oscillatory (NCPAP, control group) mode. The goal of the research is to determine if Osc-NCPAP provides improved ventilation support compared to routine NCPAP, i.e. NCPAP without oscillations. This will be measured by need for change to ventilator support, improvement in pCO2 values, and reduction in respiratory rate and frequency of apnea during the period of NCPAP treatment. Other respiratory outcomes will also be compared, including time on NCPAP, time on High-Flow Nasal Cannula support following NCPAP, and time-averaged PiO2 from start of study to end of respiratory treatment.

This is a null hypothesis study. The investigators hypothesize that there will be no difference in changes in dynamic compliance when measured at 15, 30, 45 and 60 minute intervals after administration of either surfactant and there will be no differences in the number of doses needed between the two surfactants in premature infants admitted to our NICU.

In some ARDS patients, a mild chest compression (5 kg) improves lung compliance. We aim to determine wether such an improvement is due to a better recruitment or to a reduction of overdistension

This study will evaluate the correlation between invasively measured parameters (work of breathing/power of breathing, resistance and elastance), derived using esophageal pressure measurements, and their corresponding non-invasive estimated values (noninvasive work of breathing/power of breathing, resistance and elastance), computed using airway pressure and flow measurements only.

The objective of this work is to compare standard intubation with video laryngoscope (Glide scope Ranger ) in French pre hospital multicentric study.

In Canada each year, there are approximately 800 infants born between 28 and 32 weeks gestation. Up to 60% of these infants will require breathing tube placement for Respiratory Distress Syndrome or RDS. RDS is a lung disease of prematurity due to a lack of a compound called surfactant. The breathing tube is placed as a conduit for placing surfactant into the babies' lungs to improve the lung disease. Most babies are then placed on a breathing machine or ventilator. Ventilation is not without harm and can be associated with lung damage, delays in feeding, increased hospital stay and interruption of bonding. An alternative that does not require the presence of a breathing tube is Continuous Positive Airway Pressure (CPAP). We will randomize babies to either ventilation or CPAP to try to minimize the length of time the baby is kept on respiratory support.

Artificial intelligence (AI) shows promising in identifying abnormalities in clinical images. However, systematically biased AI models, where a model makes inaccurate predictions for entire subpopulations, can lead to errors and potential harms. When shown incorrect predictions from an AI model, clinician diagnostic accuracy can be harmed. This study aims to study the effectiveness of providing clinicians with image-based AI model explanations when provided AI model predictions to help clinicians better understand the logic of an AI model's prediction. It will evaluate whether providing clinicians with AI model explanations can improve diagnostic accuracy and help clinicians catch when models are making incorrect decisions. As a test case, the study will focus on the diagnosis of acute respiratory failure because determining the underlying causes of acute respiratory failure is critically important for guiding treatment decisions but can be clinically challenging. To determine if providing AI explanations can improve clinician diagnostic accuracy and alleviate the potential impact of showing clinicians a systematically biased AI model, a randomized clinical vignette survey study will be conducted. During the survey, study participants will be shown clinical vignettes of patients hospitalized with acute respiratory failure, including the patient's presenting symptoms, physical exam, laboratory results, and chest X-ray. Study participants will then be asked to assess the likelihood that heart failure, pneumonia and/or Chronic Obstructive Pulmonary Disease (COPD) is the underlying diagnosis. During specific vignettes in the survey, participants will also be shown standard or systematically biased AI models that provide an estimate the likelihood that heart failure, pneumonia and/or COPD is the underlying diagnosis. Clinicians will be randomized see AI predictions alone or AI predictions with explanations when shown AI models. This survey design will allow for testing the hypothesis that systematically biased models would harm clinician diagnostic accuracy, but commonly used image-based explanations would help clinicians partially recover their performance.

The primary objective of this study is to evaluate the effects of a 15-week home telerehabilitation program and a detraining period on cardiorespiratory fitness and muscular efficiency in patients with post-COVID-19 sequelae compared to a control group of COVID-19 patients. We hypothesize that cardiorespiratory fitness and muscular efficiency significantly improve in patients who carry out the home telerehabilitation program. However, the cardiorespiratory and muscular adaptations achieved and tolerance to exercise are lost over time as an effect of detraining.

The objective of this study is to assess the effectiveness of online formative feedback and debriefing on nursing and medical students enrolled in the HBB course in comparison to traditional face-to-face feedback. The working hypothesis is that online feedback and debriefing during hands-on training sessions are as effective as face-to-face feedback and debriefing in teaching clinical skills to medical and nursing students.