Obstructive Sleep Apnea Syndrome (OSAS)NCT01161381
Evaluation Of Patients With Obstructive Sleep Apnea-Hypopnea Syndrome (OSAHS) Based on Nonlinear Analysis Of Respiratory Signals
An observational study of Obstructive Sleep Apnea Syndrome (OSAS), run by Aristotle University Of Thessaloniki at 1 site in Greece.
Trial 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. Read more about this study
- Who is it for?
- Ages 18 to 75 yearsHealthy volunteers can take part
- Conditions the study is for
- Obstructive Sleep Apnea Syndrome (OSAS)
- What is being tested?
- Estimation of nonlinear indices from Polysomnography
- Type of treatment
- Medical device
- How many people
- 100 participants
- Where
- 1 siteGreece
- Study dates
- Nov 2005to Dec 2009
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 75 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
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.
Who may be able to join
- symptoms compatible with OSAHS
- voluntary participation
Who cannot join
- presence of dementia
- neuromuscular disorders
- overlap syndrome
- severe cardiac problems
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Evaluation Of Patients With Suspected Obstructive Sleep Apnea - Hypopnea Syndrome Using Two Models Based on Nonlinear Analysis Of Respiratory Signals
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.
Read the detailed description
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. The study protocol was approved by the ethics committee of the hospital. All the subjects reported symptoms consistent with OSAHS and had no significant comorbidities. The presence of dementia, neuromuscular disorders, overlap syndrome or severe cardiac problems was an exclusion criterion for the participants. The subjects underwent full overnight attended polysomnography (Somnologica 7000, Flaga; Iceland) according to standard criteria including respiratory recordings of thoracic and abdominal movements, nasal flow by pressure cannula, snoring, and arterial oxygen saturation using pulse oximetry. Apnea and hypopnea were defined in accordance with standard used criteria. All the recordings were manually scored by the same experienced medical doctor.
Three nonlinear indices (Largest Lyapunov Exponent-LLE, Detrended Fluctuation Analysis-DFA and Approximate Entropy-APEN) were extracted from two respiratory signals (nasal cannula flow-F and thoracic belt movement-T). The oxygen saturation signal (SpO2) from pulse oximetry was also selected. The above signals had a mean duration of 317.5 minutes and were first exported in European Data Format (EDF) to be further processed with the use of signal processing software (Matlab by Mathworks Inc.) in personal computers. The LLE calculation required the use of a command line application by Rosenstein et al as well as a spreadsheet program (Microsoft Excel).
The basic statistical analysis was performed with the use of SPSS for Windows, Version 15.0 (SPSS Inc, Chicago, Illinois). Correlations between the studied or derived parameters were explored with the Pearson's correlation test and differences in the mean observed values between the various OSAHS severity groups were analyzed using the Student's t-test. The statistical significance level was set at p<0.05. The predictive model was created by utilizing the linear regression tool.
- Conditions
- Obstructive Sleep Apnea Syndrome (OSAS)
- Being tested
- Estimation of nonlinear indices from Polysomnography
- Keywords
- OSAHS, nonlinear analysis, polysomnography, biosignal analysis, DFA, APEN, LLE
- Medical subject headings
- Sleep Apnea, Obstructive
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Estimation of nonlinear indices from PolysomnographyDevice
Also called polysomnography device: Somnologica 7000, Flaga; Iceland
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.
| Study group | Role | What they receive |
|---|---|---|
| Normal | Subjects that underwent night polysomnography with an observed Apnea-Hypopnea Index (AHI) < 5. Receives: Device: Estimation of nonlinear indices from Polysomnography | |
| OSAHS patients | Subjects that underwent night polysomnography with an observed Apnea-Hypopnea Index (AHI) > 5. Receives: Device: Estimation of nonlinear indices from Polysomnography |
What is being measured
The primary outcome is the main question the study is designed to answer.
nonlinear dynamics of respiratory signals
calculation of nonlinear parameters (DFA, LLE, APEN) from recorded respiratory biosignals (nasal airflow, thoracic movement and SpO2) during sleep.
Measured: One night
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Jul 2010 (estimated)
- Study startNov 2005
- Primary completionDec 2009
- Study completionDec 2009
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (2)Papers the sponsor has linked to this study.
- Other trials for Obstructive Sleep Apnea Syndrome (OSAS)Studies of the same condition, open and under way.
- More trials run by Aristotle University Of ThessalonikiThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Case only
- Time perspective
- Prospective
- Enrolment
- 100 participants (actual)
Sponsor and investigators
- Lead sponsor
- Aristotle University Of Thessaloniki
- Sponsor type
- University, hospital or other
- Collaborators
- Greek State Scholarship Foundation
- Investigators
- Evangelos K Kaimakamis, MD, MSc, Principal investigator, Aristotle University Of ThessalonikiNikolaos Maglaveras, PhD, Study chair, Aristotle University Of Thessaloniki
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT01161381
- Sponsor's protocol ID
- EK1001
- Status last verified
- Dec 2005
- First submitted
- 12 Jul 2010
- Last updated
- 13 Jul 2010
- Results posted
- No
- Data monitoring committee
- No
Publications
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.
PubMed 19964987Kaimakamis 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.
PubMed 26937681
Study at a glance
From the registry record, last updated by the sponsor on 13 Jul 2010. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluation Of Patients With Suspected Obstructive Sleep Apnea - Hypopnea Syndrome Using Two Models Based on Nonlinear Analysis Of Respiratory Signals
- ClinicalTrials.gov ID
- NCT01161381
- Acronym / sponsor ID
- EK1001
- Conditions
- Obstructive Sleep Apnea Syndrome (OSAS)
- Keywords
- OSAHS, nonlinear analysis, polysomnography, biosignal analysis, DFA, APEN, LLE
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 100 participants (actual)
- Lead sponsor
- Aristotle University Of ThessalonikiUniversity, hospital or other
- Collaborators
- Greek State Scholarship Foundation
- Study start
- Nov 2005
- Primary completion
- Dec 2009 (actual)
- Study completion
- Dec 2009 (actual)
- First posted
- 13 Jul 2010 (estimated)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
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. The study protocol was approved by the ethics committee of the hospital. All the subjects reported symptoms consistent with OSAHS and had no significant comorbidities. The presence of dementia, neuromuscular disorders, overlap syndrome or severe cardiac problems was an exclusion criterion for the participants. The subjects underwent full overnight attended polysomnography (Somnologica 7000, Flaga; Iceland) according to standard criteria including respiratory recordings of thoracic and abdominal movements, nasal flow by pressure cannula, snoring, and arterial oxygen saturation using pulse oximetry. Apnea and hypopnea were defined in accordance with standard used criteria. All the recordings were manually scored by the same experienced medical doctor.
Three nonlinear indices (Largest Lyapunov Exponent-LLE, Detrended Fluctuation Analysis-DFA and Approximate Entropy-APEN) were extracted from two respiratory signals (nasal cannula flow-F and thoracic belt movement-T). The oxygen saturation signal (SpO2) from pulse oximetry was also selected. The above signals had a mean duration of 317.5 minutes and were first exported in European Data Format (EDF) to be further processed with the use of signal processing software (Matlab by Mathworks Inc.) in personal computers. The LLE calculation required the use of a command line application by Rosenstein et al as well as a spreadsheet program (Microsoft Excel).
The basic statistical analysis was performed with the use of SPSS for Windows, Version 15.0 (SPSS Inc, Chicago, Illinois). Correlations between the studied or derived parameters were explored with the Pearson's correlation test and differences in the mean observed values between the various OSAHS severity groups were analyzed using the Student's t-test. The statistical significance level was set at p<0.05. The predictive model was created by utilizing the linear regression tool.
Study design
- Observational model
- Case only
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Normal | – | Device: Estimation of nonlinear indices from PolysomnographySubjects that underwent night polysomnography with an observed Apnea-Hypopnea Index (AHI) < 5. |
| OSAHS patients | – | Device: Estimation of nonlinear indices from PolysomnographySubjects that underwent night polysomnography with an observed Apnea-Hypopnea Index (AHI) > 5. |
Who may qualify
- Ages
- 18 to 75 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- 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.
Key inclusion criteria (2 listed)
- symptoms compatible with OSAHS
- voluntary participation
Key exclusion criteria (4 listed)
- presence of dementia
- neuromuscular disorders
- overlap syndrome
- severe cardiac problems
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Estimation of nonlinear indices from PolysomnographyAlso: polysomnography device: Somnologica 7000, Flaga; IcelandAll 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. | Device | Normal, OSAHS patients |
Primary outcome
nonlinear dynamics of respiratory signals
Time frame: One night
calculation of nonlinear parameters (DFA, LLE, APEN) from recorded respiratory biosignals (nasal airflow, thoracic movement and SpO2) during sleep.
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Jul 2010.
- Results publication: PubMed 19964987Kaimakamis 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.
- Derived from this study: PubMed 26937681Kaimakamis 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.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Evangelos K Kaimakamis, MD, MSc principal investigator
Aristotle University Of Thessaloniki
Nikolaos Maglaveras, PhD study chair
Aristotle University Of Thessaloniki
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Obstructive Sleep Apnea Syndrome (OSAS), run by Aristotle University Of Thessaloniki at 1 site in Greece.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 2 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 13 Jul 2010. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Greece. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
nonlinear dynamics of respiratory signals (time frame: One night). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT01161381, which also lists 2 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 13 Jul 2010.