Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea

Sleep Apnea Clinical Trial

Official title:

Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea

Clinical Trial Details — Status: Withdrawn

Administrative data

• NCT number: NCT01286636
• Other study ID #: ANN02
• Status: Withdrawn
• Phase: Phase 3
• First received: January 27, 2011
• Last updated: January 12, 2016
• Start date: January 2011
• Est. completion date: June 2015

Study information

• Verified date: January 2016
• Source: State University of New York at Buffalo
• Contact: n/a
• Is FDA regulated: No
• Health authority: United States: Institutional Review Board
• Study type: Interventional

Clinical Trial Summary

The investigators have developed a simple, accurate, and a point-of-care, computer-based clinical decision support system (CDSS) not only to detect the presence of sleep apnea but also to predict its severity. The CDSS is based on deploying an artificial neural network (ANN) derived from anthropomorphic and clinical characteristics.

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.

Recruitment information / eligibility

• Status: Withdrawn
• Enrollment: 0
• Est. completion date: June 2015
• Est. primary completion date: March 2015
• Accepts healthy volunteers: No
• Gender: Both
• Age group: 18 Years to 75 Years

Eligibility

Inclusion Criteria:

• Must be an adult (=18 years old)

• Must have symptoms suggestive of OSA, and be considered for sleep study by the sleep specialist provider.

Exclusion Criteria:

• Pregnancy or breast feeding

• 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.

Study Design

Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Parallel Assignment, Masking: Open Label, Primary Purpose: Diagnostic

Related Conditions & MeSH terms

• Apnea
• Sleep Apnea
• Sleep Apnea Syndromes
• Sleep Apnea, Obstructive

Intervention

Other:
• 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

Locations

Country	Name	City	State
United States	Veterans Affairs Medical Center in Buffalo	Buffalo	New York

Sponsors (2)

Lead Sponsor	Collaborator
State University of New York at Buffalo	VA Office of Research and Development

Country where clinical trial is conducted

United States, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	To demonstrate that using an ANN directed management of OSA is not inferior to PSG directed management of OSA in terms of sleepiness related functional outcome		6 weeks	No