New Approach in the Study of the Autonomic Nervous System Through Cardiac Variability in Sleep Apnea Syndrome.

Summary

The main objective of this study is to compare the different variations of the cardiac variability index measured thanks to the technique developed by the CIC-IT between subjects with severe SAS and healthy subjects with sleep pathology. In a first step, these two groups will be compared in REM sleep phase because it is the period during which the risk of sleep apnea syndrome is the highest. In a second step, the same methodology will be applied for the other sleep phases and correlations will be established with the other markers of cardiac variability (HRV) already known. This will allow to validate a reliable method of screening for SAS that is more accessible in ambulatory settings by means of a machine learning system based on artificial intelligence

Eligibility

Inclusion Criteria:

* Group healthy subjects - 1): absence of sleep disorder referenced in the ICSD-3.

  * Epworth Sleep Scale \< 11
  * Pittsburgh Quality Sleep Index \< 6
  * Berlin Questionnaire: \< 2 positive categories
  * STOP BANG \<3
  * HADS normal
  * No RLS
* Group 2 (subjects with severe SAS - 2): AHI \> 30/h obstructive

Exclusion Criteria:

Non-inclusion criteria:

* Cardiac rhythm disorder
* Neurological or psychiatric pathology impacting on ANS
* Control group (healthy subjects - 1)

  * Complaint of sleep disorder
  * Known sleep disorder
* Experimental group (subjects with severe SAS - 2):

  o Associated sleep pathology at diagnosis of severe SAS
* Administrative reasons:

  * Unable to receive informed information,
  * Unable to participate in the entire study
  * Lack of social security coverage
  * Refusal to sign consent Exclusion criteria
* Control group (healthy subjects - 1):

  * Sleep pathology detected by polysomnography
  * Total sleep time less than 4 hours
  * Recording technically not usable

Conditions2

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