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Showing 1-4 of 4 trials
NCT07423338
Acute respiratory failure is a common, life-threatening condition where the lungs cannot provide enough oxygen to the body. Many patients are treated with non-invasive respiratory support (NRS) such as high-flow nasal oxygen (HFNO), continuous positive airway pressure (CPAP), or bilevel positive airway pressure (BiPAP). However, up to half of patients receiving NRS still deteriorate and require intubation and invasive ventilation, which is linked to longer hospital stays, more complications, and slower recovery. A major challenge in caring for these patients is that clinicians currently cannot directly see how well the breathing muscles (especially the diaphragm and parasternal intercostal muscles) and the lungs are working while the patient is using NRS. Existing bedside measures, such as respiratory rate or oxygen levels, only show part of the picture. They do not indicate how hard the patient is working to breathe or whether their respiratory muscles are becoming fatigued. This lack of information may delay important decisions about adjusting NRS settings or switching to other treatments. This study aims to find out whether two advanced but non-invasive, radiation-free bedside monitoring tools can be used effectively in routine care: 1. Ultrasound, which can measure breathing muscle thickness, movement, and lung aeration 2. Electrical impedance tomography (EIT), which uses a soft belt of small electrodes around the chest to measure changes in air and blood flow within different regions of the lungs in real time These tools have shown promise in earlier research, and interviews with patients and clinicians suggest they are comfortable, well-tolerated, and potentially useful. However, they have not yet been evaluated together in a real-world hospital environment where many acute respiratory failure patients are cared for outside the ICU. What the study will involve: Up to 100 adults with acute respiratory failure requiring any type of non invasive respiratory support will be recruited with the goal of obtaining complete data from at least 50 patients. Each participant will undergo ultrasound and EIT assessments up to seven times during the first 72 hours after starting NRS, plus an additional measurement if they improve enough to stop NRS or if they deteriorate and require intubation. These assessments take place at the bedside, require brief exposure of the upper chest, and last approximately 15-45 minutes. Routine clinical data-such as heart rate, oxygen levels, and breathing measures-will also be recorded. In parallel, clinical staff caring for these patients will complete a short Healthcare System Usability Scale questionnaire to rate how useful, understandable, and practical they find the information generated by ultrasound and EIT. Some staff may also take part in optional interviews to explore usability in more depth. What the study is trying to learn: The primary aim is to determine the usability of these monitoring methods meaning understanding if they are practical, easy to use, and helpful for clinicians making decisions about NRS treatment. Secondary aims include understanding: * how the respiratory muscles and lungs change over time during NRS * whether these changes are linked to treatment settings (e.g., flow rate, pressure support) * whether certain patterns are associated with treatment success or failure (intubation or death) * whether these tools could help identify patients at risk of deterioration earlier Risks and benefits: Both ultrasound and EIT are widely used, safe, and non-invasive. They involve no radiation, needles, or harmful exposure. Minor temporary discomfort from the gel or belt placement is possible. Participation will not change any clinical treatments. Although patients may not directly benefit, the study may help future patients by improving understanding of breathing muscle function and supporting more personalised respiratory care. By contributing to this research, patients and clinicians will help determine whether advanced monitoring can be realistically implemented in busy hospital settings and whether it could lay the groundwork for future trials aimed at improving outcomes for people with acute respiratory failure.
NCT07293078
This is a prospective, unmasked, randomized, multicenter clinical trial evaluating the impact of point-of-care large language model (LLM)-based decision support on diagnostic accuracy and clinical outcomes in adult medical intensive care unit (MICU) patients. Consecutive adult ICU admissions at participating community hospitals (initially MetroWest Medical Center and St. Vincent Hospital) will be screened for eligibility. Eligible patients will be randomized 1:1 to standard care or an AI-assisted group. In both arms, initial evaluation and management will follow usual practice. For patients randomized to AI assistance, de-identified admission data (history and physical, labs, imaging reports, and other relevant documentation) will be formatted and submitted to a state-of-the-art LLM (ChatGPT-5) at the time of admission. The AI-generated differential diagnosis and therapeutic recommendations will be provided to the admitting team for consideration. For the standard care arm, LLM output will be generated but not shared with clinicians. After discharge, a masked chart review will determine the "ground truth" primary diagnosis and extract outcomes including: Primary Outcome - a composite of medical errors (from time of ICU admission through day 7 of ICU stay, or ICU discharge, whichever comes first); Secondary Outcomes - 90-day mortality, ICU and hospital length of stay, and ventilator-free days.
NCT07265882
The goal of this study is to learn about the respiratory mechanics in patients undergoing mechanical ventilation. The investigators can achieve this through the offline analysis of data provided by the ventilator. Within the field of respiratory mechanics, the study focuses particularly on the quantification of lung instability. What does lung instability mean? By this definition, the investigators refer to the part of lung tissue that opens during inspiration and then collapses during the subsequent expiration. The more diseased the lung (for example, in the case of viral pneumonia), the greater the quantity of this tissue. How is lung instability measured? In the context of the study analysis, lung instability is measured through the analysis of the low flow pressure-volume loop during ventilation. This graph illustrates how the volume of air in the lungs varies in response to the pressures applied by the ventilator during slow inflation and deflation phases. This maneuver is considered quick and safe and has been an integral part of our clinical practice for several years. Through this maneuver, investigators can examine the range of pressures provided by the ventilator during tidal ventilation. To assess lung instability, hysteresis is analyzed, which represents a distinctive characteristic of the pressure-volume loop. Greater hysteresis indicates a higher degree of lung instability. During the study, investigators will record not only hysteresis but also classical respiratory mechanics parameters (for example, elastance of the respiratory system, i.e., how stiff the lung is), parameters regarding gas exchange (blood oxygen and carbon dioxide levels), biometric data (for example, height and weight), and imaging (CT scans, lung ultrasound, and electrical impedance tomography) to relate them to the degree of lung instability.
NCT07182695
Dyspnea is common and distressing in patients with acute respiratory failure. In our intensive care unit, some patients receive a cervical erector spinae plane (ESP) block to help relieve dyspnea. This study will observe patients who receive bilateral cervical ESP blocks and measure changes in dyspnea using validated scales at predefined time points over 24 hours. We will also track vital signs, arterial blood gas values, and diaphragm movement on ultrasound.