Automatic Estimation of the Apnea-hypopnea Index Using Neural Networks to Detect Sleep Apnea

NCT02143297 | Unknown DMC

• 1 other identifier: SEPAR-265/2012
• Study Type: observational
• Target: 322
• Locations: 1 country
• Sites: 1

Brief Summary

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.

Conditions

Sleep Apnea/Hypopnea Syndrome

Keywords

Sleep Apnea/Hypopnea Syndrome; Pulse Oximetry; Nonlinear Dynamics; Fourier Analysis; Neural Networks (Computer)

Outcome Measures

Primary Outcomes (2)

• Correlation between our estimated AHI from oximetry and real AHI from gold standard PSG

  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.

  12 months after the inclusion of the last patient

• Percentage of patients correctly classified

  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.

  12 months after the inclusion of the last patient

Secondary Outcomes (10)

• Prevalence of SAHS

  12 months (inclusion period)

• Severity of SAHS

  12 months (inclusion period)

• Demographic and anthropometric characteristics

  12 months (inclusion period)

• Clinical characteristics of the study population

  12 months (inclusion period)

• Patients' lifestyle

  12 months (inclusion period)

Study Arms (2)

SAHS negative

Subjects derived to the sleep unit due to suspicion of suffering from sleep apnea which finally do not have the disease according to standard PSG

SAHS positive

Subjects derived to the sleep unit due to suspicion of suffering from sleep apnea which finally have the disease according to standard PSG

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

Subjects derived to the reference sleep unit from primary care with suspicion of suffering from SAHS due to daytime hypersomnolence, loud snoring, nocturnal choking and awakenings, and/or apnoeic events

You may qualify if:

• Men and women over 18 years old
• Subjects submitted to the sleep unit due to previous symptoms of sleep apnea (daytime hypersomnolence, loud snoring, nocturnal choking and awakenings, and/or apnoeic events)
• Written informed consent signed

You may not qualify if:

• 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

Sponsors & Collaborators

• Sociedad Española de Neumología y Cirugía Torácica: lead

Study Sites (1)

Hospital Universitario Río Hortega

Valladolid, Valladolid, 47012, Spain

Location

Related Links

• Biomedical Engineering Group (GIB) Website

MeSH Terms

Conditions

Sleep Apnea, Obstructive

Condition Hierarchy (Ancestors)

Sleep Apnea Syndromes; Apnea; Respiration Disorders; Respiratory Tract Diseases; Sleep Disorders, Intrinsic; Dyssomnias; Sleep Wake Disorders; Nervous System Diseases

Study Officials

• Felix Del Campo, PhD, MD

  Hospital Universitario Río Hortega, University of Valladolid

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD, MD

Study Record Dates

• First Submitted: May 15, 2014
• First Posted: May 21, 2014
• Study Start: July 1, 2013
• Primary Completion: March 1, 2014
• Study Completion: July 1, 2014
• Last Updated: May 21, 2014

Record last verified: 2014-05

Locations

ES (1)