Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea
NCT ID: NCT01286636
Last Updated: 2016-01-13
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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WITHDRAWN
PHASE3
INTERVENTIONAL
2011-01-31
2015-06-30
Brief Summary
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The investigators hypothesize that patients with severe OSA defined as AHI≥30 can be diagnosed with the use of ANN without undergoing a sleep study, and that empiric management with auto-CPAP has similar outcomes to those who undergo a formal sleep study.
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Detailed Description
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Conditions
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
NONE
Study Groups
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artificial neural network
computer model
Diagnosis of Sleep apnea and treatment guidance will rely on a computer model prediction.
Polysomnogram
Polysomnogram
Diagnosis of sleep apnea will rely on polysomnogram
Interventions
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computer model
Diagnosis of Sleep apnea and treatment guidance will rely on a computer model prediction.
Polysomnogram
Diagnosis of sleep apnea will rely on polysomnogram
Eligibility Criteria
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Inclusion Criteria
* Must have symptoms suggestive of OSA, and be considered for sleep study by the sleep specialist provider.
Exclusion Criteria
* Patients with severe congestive heart failure (eg, NYHA Class IV, ejection fraction \< 35%).
* Patients with end-stage renal disease on hemodialysis
* Patients with CVA, Parkinson, neuromuscular degenerative disease.
* Patient on narcotics.
* Patients with severe lung disease requiring oxygen at night and/or during the day.
* Patient with predominant insomnia or sleep hygiene problems, and who are not considered for PSG by the sleep specialist.
18 Years
75 Years
ALL
No
Sponsors
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VA Office of Research and Development
FED
State University of New York at Buffalo
OTHER
Responsible Party
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Ali El Solh
Professor
Principal Investigators
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Ali El-Solh, MD, MPH
Role: PRINCIPAL_INVESTIGATOR
State University of New York at Buffalo
Locations
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Veterans Affairs Medical Center in Buffalo
Buffalo, New York, United States
Countries
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Other Identifiers
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ANN02
Identifier Type: -
Identifier Source: org_study_id
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