Automatic Estimation of Apnea-hypopnea Index (AHI) Using Neural Networks to Assist in the Diagnosis of Sleep Apnea-hypopnea Syndrome (SAHS)
试验速览
- 阶段
- 不适用
- 发起方
- 入组人数
- 322
- 试验地点
- 1
- 主要终点
- Correlation between our estimated AHI from oximetry and real AHI from gold standard PSG
研究概览
简要总结
The sleep apnea hypopnea syndrome (SAHS) is a respiratory disorder characterized by frequent breathing cessations (apneas) or partial collapses (hypopneas) during sleep. These respiratory events lead to deep oxygen desaturations, blood pressure and heart rate acute changes, increased sympathetic activity and cortical arousals. The gold standard method for SAHS diagnosis is in-hospital, technician-attended overnight polysomnography (PSG). However, this methodology is labor-intensive, expensive and time-consuming, which has led to large waiting lists, delaying diagnosis and treatment. Blood oxygen saturation (SpO2) from nocturnal pulse oximetry (NPO) provides relevant information to detect apneas, it can be easily recorded ambulatory and it is less expensive and highly reliable. The investigators hypothesize that an automatic analysis of single oximetric recordings at home could provide essential information on the diagnosis of SAHS. The aim of this study is two-fold: firstly, the research focuses on assessing the reliability and usefulness of NPO carried out at patient's home in the context of SAHS detection and, secondly, the study aims at assessing the performance of an automatic regression model of the AHI by means of neural networks using information from NPO recordings. To achieve this goal, both PSG and NPO studies are carried out. A polysomnography equipment (E-Series, Compumedics) is used for standard in-hospital PSG studies, whereas a portable pulseoximeter (WristOX2 3150, Nonin) is used for ambulatory NPO. NPO is carried out the day immediately before or after the PSG at patient's home. Patients are assigned to carry out the NPO study before or after the in-hospital PSG randomly. In addition, in-hospital attended oximetry is also performed simultaneously to the PSG using the portable pulseoximeter.
详细描述
Subjects under study are recruited from the sleep unit of the "Hospital Universitario Río Hortega" (HURH) from Valladolid (Spain). All subjects are derived to the sleep unit due to suspicion of suffering from SAHS. The whole population set is subsequently divided into training set and test set. The training set is used to compose the regression model, whereas the test set is used to further assess its performance.
The standard apnea-hypopnea index (AHI) from PSG is used to diagnose SAHS. According to the American Academy of Sleep Medicine (AASM) rules, apnea is defined as a drop in the airflow signal greater than or equal to 90% from baseline lasting at least 10s, whereas hypopnea is defined as a drop greater than or equal to 50% during at least 10 s accompanied by a desaturation greater than or equal to 3% and/or an arousal. Subjects with an AHI >= 10 events per hour (e/h) are diagnosed as suffering from SAHS.
A portable pulseoximeter (WristOX2 3150, Nonin) is used for ambulatory NPO. NPO is carried out the day immediately before or after the PSG at patient's home. Patients are assigned to carry out the NPO study before or after in-hospital PSG randomly. In addition, oximetry is also performed simultaneously to the PSG by means of the portable pulseoximeter. Therefore, every patient has 3 oximetric recordings: (i) SpO2 from unattended portable monitoring at home, (ii) SpO2 from attended in-hospital portable monitoring and (iii) SpO2 from attended in-hospital standard PSG.
SpO2 is recorded at a sampling rate of 1 Hz. All SpO2 recordings are saved to separate files and process offline. An automatic signal pre-processing stage is carried out to remove artifacts.
Our methodology is divided into two stages: feature extraction and pattern recognition. Oximetric recordings are parameterized by means of 16 features from four feature subsets to compose the initial feature set from oximetry: time domain statistics, frequency domain statistics, conventional spectral measures and nonlinear features. All features are computed for each whole overnight recording.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Control
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- 未提供
排除标准
- •Subjects under 18 years old
- •Subjects not signing the informed consent
- •Presence of any previously diagnosed sleep disorders: narcolepsy, insomnia, chronic sleep deprivation, regular use of hypnotic or sedative medications and restless leg syndrome
- •Patients with chronic diseases: congestive heart failure, renal failure, neuromuscular diseases, chronic respiratory failure
- •Patients with > 50% of central apneas or the presence of Cheyne-Stokes respiration
- •Previous CPAP treatment for SAHS diagnosis
- •A medical history that may interfere with the study objectives or, in the opinion of the investigator, compromise the conclusions
结局指标
主要结局
Correlation between our estimated AHI from oximetry and real AHI from gold standard PSG
时间窗: 12 months after the inclusion of the last patient
A measure of correlation between our estimation of the AHI and the real AHI derived from conventional in-hospital PSG will be measured by means of the intra-class correlation coefficient (ICC). This measure shows how similar are both indexes (estimated AHI and real AHI) in order to assess the severity of SAHS using our estimated AHI. In addition, Bland and Altman plots of agreement between NPO-based estimated AHI and PSG-based standard AHI will be drawn in order to assess under/over-estimation along the whole range of AHI values.
Percentage of patients correctly classified
时间窗: 12 months after the inclusion of the last patient
Percentage of patients correctly classified by the optimum portable NPO-based algorithm using the NPO-based estimated AHI. PSG is used as the reference gold standard method. Subjects with an AHI \>= 10 event per hour (e/h) are considered as suffering from SAHS.
次要结局
- Prevalence of SAHS(12 months (inclusion period))
- Severity of SAHS(12 months (inclusion period))
- Clinical characteristics of the study population(12 months (inclusion period))
- Patients' lifestyle(12 months (inclusion period))
- PSG-derived variables(12 months (inclusion period))
- Demographic and anthropometric characteristics(12 months (inclusion period))
- Compliance with portable device(12 months (inclusion period))
- Physiological interpretation(24 months)
- Portable NPO-derived variables(12 months (inclusion period))
- Cost-effectiveness(24 months)
研究者
Dr. Félix del Campo
PhD, MD
University of Valladolid