Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea

State University of New York at Buffalo

Overview

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.

Study Type

INTERVENTIONAL

Allocation

RANDOMIZED

Purpose

DIAGNOSTIC

Masking

NONE

Conditions

Sleep Apnea

Interventions

computer modelOTHER

Diagnosis of Sleep apnea and treatment guidance will rely on a computer model prediction.

PolysomnogramOTHER

Diagnosis of sleep apnea will rely on polysomnogram

Eligibility

Sex: ALLMin age: 18 YearsMax age: 75 Years

Medical Language ↔ Plain English

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.

Locations (1)

Veterans Affairs Medical Center in Buffalo

Buffalo, New York, United States

Outcomes

Primary Outcomes

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

Time frame: 6 weeks

Data from ClinicalTrials.gov

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