Evaluation Of Patients With Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) Based on Nonlinear Analysis Of Respiratory Signals

NCT01161381 | Completed

• 1 other identifier: EK1001
• Study Type: observational
• Target: 100
• Locations: 1 country
• Sites: 1

Brief Summary

Objective: Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) is a common sleep disorder requiring the time and money consuming full polysomnography to be diagnosed. Alternative methods for initial evaluation are sought. The investigators aim was the prediction of Apnea-Hypopnea Index (AHI) in patients suspected to suffer from OSAHS using two models based on nonlinear analysis of three biosignals during sleep. Methods: One hundred patients referred to a Sleep Unit underwent full polysomnography. Three nonlinear indices (Largest Lyapunov Exponent, Detrended Fluctuation Analysis and Approximate Entropy) were extracted from three biosignals (airflow from a nasal cannula, thoracic movement and Oxygen saturation) providing input to a data mining application for the creation of predictive models for AHI.

Conditions

Obstructive Sleep Apnea Syndrome (OSAS)

Keywords

OSAHS; nonlinear analysis; polysomnography; biosignal analysis; DFA; APEN; LLE

Outcome Measures

Primary Outcomes (1)

• nonlinear dynamics of respiratory signals

  calculation of nonlinear parameters (DFA, LLE, APEN) from recorded respiratory biosignals (nasal airflow, thoracic movement and SpO2) during sleep.

  One night

Study Arms (2)

Normal

Subjects that underwent night polysomnography with an observed Apnea-Hypopnea Index (AHI) \< 5.

Device: Estimation of nonlinear indices from Polysomnography

OSAHS patients

Subjects that underwent night polysomnography with an observed Apnea-Hypopnea Index (AHI) \> 5.

Device: Estimation of nonlinear indices from Polysomnography

Interventions

Estimation of nonlinear indices from Polysomnography DEVICE

All subjects underwent full night polysomnography. Three nonlinear indices (Largest Lyapunov Exponent, Detrended Fluctuation Analysis and Approximate Entropy) were extracted from three biosignals (airflow from a nasal cannula, thoracic movement and Oxygen saturation) providing input to a data mining application for the creation of predictive models for AHI.

Also known as: polysomnography device: Somnologica 7000, Flaga; Iceland

Normal; OSAHS patients

Eligibility Criteria

• Age: 18 Years - 75 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Patients referred to the Sleep Unit of a tertiary hospital in northern Greece during the years 2005-2008 and who accepted to sign the informed consent form were included in the study. One out of every five consecutive patients was selected in order to ensure randomization.

You may qualify if:

• symptoms compatible with OSAHS
• voluntary participation

You may not qualify if:

• presence of dementia
• neuromuscular disorders
• overlap syndrome
• severe cardiac problems

Sponsors & Collaborators

• Aristotle University Of Thessaloniki: lead
• Greek State Scholarship Foundation: collaborator

Study Sites (1)

Sleep Unit of "G. Papanikolaou" General Hospital

Exochi, GR57010, Greece

Location

Related Publications (2)

• Kaimakamis E, Bratsas C, Sichletidis L, Karvounis C, Maglaveras N. Screening of patients with Obstructive Sleep Apnea Syndrome using C4.5 algorithm based on non linear analysis of respiratory signals during sleep. Annu Int Conf IEEE Eng Med Biol Soc. 2009;2009:3465-9. doi: 10.1109/IEMBS.2009.5334605.

  PMID: 19964987 RESULT

• Kaimakamis E, Tsara V, Bratsas C, Sichletidis L, Karvounis C, Maglaveras N. Evaluation of a Decision Support System for Obstructive Sleep Apnea with Nonlinear Analysis of Respiratory Signals. PLoS One. 2016 Mar 3;11(3):e0150163. doi: 10.1371/journal.pone.0150163. eCollection 2016.

  PMID: 26937681 DERIVED

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

• Evangelos K Kaimakamis, MD, MSc

  Aristotle University Of Thessaloniki

  PRINCIPAL INVESTIGATOR

• Nikolaos Maglaveras, PhD

  Aristotle University Of Thessaloniki

  STUDY CHAIR

Study Design

• Study Type: observational
• Observational Model: CASE ONLY
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER

Study Record Dates

• First Submitted: July 12, 2010
• First Posted: July 13, 2010
• Study Start: November 1, 2005
• Primary Completion: December 1, 2009
• Study Completion: December 1, 2009
• Last Updated: July 13, 2010

Record last verified: 2005-12

Locations

GR (1)