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The Evaluation of Autonomic Arousals in Scoring Sleep Respiratory Disturbances with Polysomnography and Portable Monitor Devices: A Proof of Concept Study

Authors Mayer P, Herrero Babiloni A, Beetz G, Marshansky S, Kaddaha Z, Rompré PH, Jobin V, Lavigne GJ

Received 22 April 2020

Accepted for publication 30 June 2020

Published 16 July 2020 Volume 2020:12 Pages 443—451


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Professor Ahmed S Bahammam

Pierre Mayer,1 Alberto Herrero Babiloni,1– 4 Gabrielle Beetz,2 Serguei Marshansky,1 Zeina Kaddaha,1 Pierre H Rompré,3 Vincent Jobin,1 Gilles J Lavigne1– 3

1Faculté de Médecine, Hôpital Hôtel-Dieu du Centre Hospitalier de l’Université de Montréal (CHUM), Université de Montréal, Montréal, Québec, Canada; 2Research Center, Hôpital du Sacré-Coeur de Montréal, CIUSSS du Nord-de-l’île-de-Montréal, Université de Montréal, Montréal, Québec, Canada; 3Department of Oral Health, Faculté de Médecine Dentaire, Université de Montréal, Montréal, Québec, Canada; 4Division of Experimental Medicine, McGill University, Montréal, Québec, Canada

Correspondence: Alberto Herrero Babiloni
Research Center, Hôpital du Sacré-Coeur de Montreal, CIUSSS du Nord-de-l’Île-de-Montréal, Université De Montréal, 5400 Boul Gouin O, Montréal, QC H4J 1C5, Canada
Tel +1 514-338-2222
Fax +1 514-238-2531

Background: Autonomic arousals can be considered as surrogates of electroencephalography (EEG) arousals when calculating respiratory disturbance index (RDI). The main objective of this proof of concept study was to evaluate the use of heart rate acceleration (HRa) arousals associated with sleep respiratory events in a population undergoing full polysomnography (type 1) and in another undergoing portable monitor study (type 3). Our hypothesis is that when compared to other commonly used indexes, RDI based on HRa will capture more events in both types of recording.
Materials and Methods: A retrospective analysis was performed in two different populations of patients with suspected OSA: a) 72 patients undergoing one night of type 1 recording and b) 79 patients undergoing one night of type 3 recording. Variables for type 1 were 4% oxygen desaturation index (ODI), apnea/hypopnea index (AHI), RDI based on EEG arousals (RDIe), and RDI based on HRa with threshold of 5bpm (RDIa5). For type 3, variables were 4% ODI, AHI, and RDIa5 (it is not possible to calculate RDIe due to the absence of EEG). Calculated data were 1) Mean values for each sleep disturbance index in type 1 and 3 recordings; 2) Frequency of migration from lower to higher OSA severity categories using RDIa5 in comparison to AHI (thresholds: ≥ 5/h mild, ≥ 15/h moderate, ≥ 30/h severe); and 3) Bland–Altman plots to assess agreement between AHI vs RDIe and RDIa5 in type 1 population, and AHI vs RDIa5 in type 3 populations.
Results: More respiratory disturbance events were captured with RDIa5 index in both type 1 and type 3 recordings when compared to the other indexes. In type 1 recording, when using RDIa5 37% of patients classified as not having OSA with AHI were now identified as having OSA, and a total of 59% migrated to higher severity categories. In type 3 recording, similar results were obtained, as 37% of patients classified as not having OSA with AHI were now identified as having OSA using RDIa5, and a total of 55% patients migrated to higher severity categories. Mean differences for RDIa5 and AHI in type 1 and 3 populations were similar.
Conclusion: The use of autonomic arousals such as HRa can help to detect more respiratory disturbance events when compared to other indexes, being a variable that may help to capture borderline mild cases. This becomes especially relevant in type 3 recordings. Future research is needed to determine its validity, optimization, and its clinical significance.

Keywords: sleep apnea, autonomic arousals, apnea-hypopnea index, respiratory disturbance index, polysomnography, portable monitor devices

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