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Completed Not applicable Interventional

Incorporating Flow Limitation Into the Diagnosis and Quantification of Sleep Disordered Breathing

ClinicalTrials.gov ID: NCT00004569

Public ClinicalTrials.gov record NCT00004569. Field values are reproduced from the official study page; the official ClinicalTrials.gov record remains the source of truth for eligibility, enrollment, and contact information.

ClinicalTrials.gov public records Last synced Sep 9, 2026, 12:35 AM EDT

Data is sourced from official ClinicalTrials.gov public API records. Always review the official ClinicalTrials.gov record for the latest information.

Brief summary

Reproduced verbatim from the official ClinicalTrials.gov record. Not medical advice.

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.

Study identification

NCT ID
NCT00004569
Recruitment status
Completed
Study type
Interventional
Phase
Not applicable
Enrollment
Not listed

Conditions and interventions

Eligibility (public fields only)

Age range
18 Years and older
Sex
All
Healthy volunteers
Healthy volunteers not accepted

This page does not interpret eligibility. Detailed inclusion and exclusion criteria are on the official ClinicalTrials.gov record.

Study timeline

Start date
Not listed
Primary completion
Not listed
Completion
Not listed
Last update posted
Jun 23, 2005

United States locations

U.S. sites
1
U.S. states
1
U.S. cities
1
Facility City State ZIP Site status
NYU Sleep Disorders Center New York New York 10016

Site contact phone numbers, emails, and investigator names are intentionally not displayed here. Open the official ClinicalTrials.gov record for site contact information.

About this trial record page

What this page shows
Public field values for ClinicalTrials.gov record NCT00004569, including study identification, conditions, interventions, eligibility (age, sex, healthy volunteer), timeline, and U.S. site list.
What this page does not do
No medical advice, eligibility judgments, treatment recommendations, study quality scoring, or AI-generated medical summaries. No site contact phone numbers, emails, or investigator names.
Where the data comes from
Sourced from the official ClinicalTrials.gov public API. The official record is the source of truth.
Last refresh
Last update posted Jun 23, 2005 · Synced Sep 9, 2026

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Open the official record

The complete protocol, eligibility criteria, and contact information for NCT00004569 live on ClinicalTrials.gov.

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