Incorporating Flow Limitation Into the Diagnosis and Quantification of Sleep Disordered Breathing
NCT ID: NCT00004569
Last Updated: 2005-06-24
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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COMPLETED
NA
INTERVENTIONAL
Brief Summary
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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.
Detailed Description
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Conditions
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Study Design
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DIAGNOSTIC
Interventions
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Non-invasive technique to diagnose and quantitate sleep-disordered breathing
Eligibility Criteria
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Inclusion Criteria
18 Years
ALL
No
Sponsors
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National Center for Research Resources (NCRR)
NIH
Locations
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NYU Sleep Disorders Center
New York, New York, United States
Countries
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Other Identifiers
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NCRR-M01RR00096-0938
Identifier Type: -
Identifier Source: org_study_id