View clinical trials related to Respiratory Aspiration.
Filter by:The objective of the study was to evaluate the degree of improvement in lung function in patients with chronic obstructive pulmonary disease (COPD) after treatment with tiotropium inhalation capsules compared to salmeterol inhalation aerosol .
The purpose of this research is to study and improve the methods used to detect childhood breathing problems during sleep that can affect daytime behavior at home and school. Early diagnosis of these sleep disorders may allow doctors to treat children at a time when the consequences can still be reversed.
Some babies have difficulty breathing, sucking, and swallowing at birth. The purpose of this study is to determine (before birth) the variables that will predict whether a newborn will experience these problems. Study participants will be pregnant women with a single fetus who are 18 years or older and who are scheduled to receive a standard prenatal ultrasound. Researchers will use the ultrasound to observe fetal motions associated with breathing, sucking, and swallowing on digital videotape. They will then review these tapes and take measurements that will help them document how breathing and swallowing develop.
Sleep-disordered breathing (SDB) in children may be responsible for disruptive daytime behaviors such as inattention and hyperactivity. Many children undergo tonsillectomy for SDB and disruptive daytime behaviors. However, the link between SDB and disruptive behavior is not clearly understood. This study will evaluate the relationship between SDB and disruptive behavior.
The diagnosis and treatment of sleep disordered breathing have come to the forefront of clinical medicine following recognition of the high prevalence and associated morbidity of sleep apnea. The effects on quality of life as well as societal costs have been well documented. The NYU Sleep Research Laboratory has spent the last several years working on the problem of improving the diagnosis of mild sleep disordered breathing which manifests as the upper airway resistance syndrome. Our approach has been to develop a non-invasive technique to detect increased upper airway resistance directly from analysis of the airflow signal. A characteristic intermittent change of the inspiratory flow contour, which is indicative of the occurrence of flow limitation, correlates well with increased airway resistance. Currently all respiratory events are identified manually and totaled. This is time consuming and subject to variability. The objective of the present project is to improve upon the manual approach by implementing an artificially intelligent system for the identification and quantification of sleep disordered breathing based solely on non-invasive cardiopulmonary signals collected during a routine sleep study. The utility of other reported indices of sleep disordered breathing obtained during a sleep study will be evaluated. Successful development of an automated system that can identify and classify upper airway resistance events will simplify, standardize and improve the diagnosis of sleep disordered breathing, and greatly facilitate research and clinical work in this area. Using a physiological based determination of disease should allow better assessment of treatment responses in mild disease.