Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea
试验速览
- 阶段
- 3 期
- 状态
- 撤回
- 试验地点
- 2
- 主要终点
- 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
研究概览
简要总结
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.
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Diagnostic
- 盲法
- None
入排标准
- 年龄范围
- 18 Years 至 75 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Must be an adult (≥18 years old)
- •Must have symptoms suggestive of OSA, and be considered for sleep study by the sleep specialist provider.
排除标准
- •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.
结局指标
主要结局
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
时间窗: 6 weeks
次要结局
未报告次要终点
研究者
Ali El Solh
Professor
State University of New York at Buffalo