Artificial Neural Network Directed Therapy of Severe Obstructive Sleep Apnea
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.
研究概览
研究类型
阶段
- 第三阶段
联系人和位置
学习地点
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New York
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Buffalo、New York、美国、14215
- Veterans Affairs Medical Center in Buffalo
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参与标准
资格标准
适合学习的年龄
接受健康志愿者
有资格学习的性别
描述
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.
学习计划
研究是如何设计的？
设计细节
- 主要用途：诊断
- 分配：随机化
- 介入模型：并行分配
- 屏蔽：无（打开标签）
武器和干预
参与者组/臂 |
干预/治疗 |
|---|---|
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实验性的：artificial neural network
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Diagnosis of Sleep apnea and treatment guidance will rely on a computer model prediction.
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有源比较器：Polysomnogram
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Diagnosis of sleep apnea will rely on polysomnogram
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研究衡量的是什么？
主要结果指标
结果测量 |
大体时间 |
|---|---|
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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
大体时间：6 weeks
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6 weeks
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合作者和调查者
调查人员
- 首席研究员：Ali El-Solh, MD, MPH、State University of New York at Buffalo
研究记录日期
研究主要日期
学习开始
初级完成 (实际的)
研究完成 (实际的)
研究注册日期
首次提交
首先提交符合 QC 标准的
首次发布 (估计)
研究记录更新
最后更新发布 (估计)
上次提交的符合 QC 标准的更新
最后验证
更多信息
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