Possibility of applying heart rate variability as a screening method to high-risk obstructive sleep apnea patients

Malekmohammad, Majid; Naghan, Parisa Adimi; Khoundabi, Batoul; Omidian, Shideh

Possibility of applying heart rate variability as a screening method to high-risk obstructive sleep apnea patients

Document Type : Original Article

Authors

¹ Tracheal Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Qazvin, Iran

² Chronic Respiratory Disease Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Qazvin, Iran

³ Iran Helal Institute of Applied-Science and Technology, Red Crescent Society of the Islamic Republic of Iran, Tehran Research Center for Health Management in Mass Gathering, Qazvin, Iran

⁴ Omidian Shideh, Qazvin University of Medical Sciences, Qazvin, Iran

Abstract

Background: Altered heart rate variability (HRV) has been associated with a number of disorders affecting autonomic tone, including recent myocardial infarction, congestive heart failure, and diabetic neuropathy. Furthermore, obstructive sleep apnea (OSA) has been shown to be associated with characteristic disturbances in heart rhythm. In this study, using HRV frequency analysis, an attempt has been made to diagnose or possibly diagnose OSA. Materials and Methods: Using Somnologica version 3.3.1 software (Medcare-Embla), polysomnographic recordings were done. Electrocardiographic signals were digitalized with a sampling rate of 250 Hz. Using the HRV analysis report of this software, low-frequency (LF) and high- frequency (HF) information and LF to HF ratio (LF/HF) were obtained at 5-min intervals, then at cutting points 30, 35, 40, 45, and 50, which indicate the intensity of the apnea and hypopnea index (AHI), were analyzed with mean and standard deviation of HRV frequencies. Results: According to the results reported in this study, comparison of mild, moderate, and severe cases led to no significant differences, while frequency-domain analysis displayed significant LF/HF increase in more severe AHI cases. This can probably be applied in screening high-risk patients, reducing the application of PSG in high probable cases, and providing an estimate of prognosis of potentials patients for the physicians. Conclusions: In the study of frequency-domain analysis, LF/HF increases in more severe AHI cases. These can probably be applied in screening high-risk patients, reducing the application of PSG in high probable cases.

Keywords

References

1.	Rundo JV. Obstructive sleep apnea basics. Cleve Clin J Med 2019;86:2-9.
2.	Buccelletti E, Gilardi E, Scaini E, Galiuto L, Persiani R, Biondi A, et al. Heart rate variability and myocardial infarction: Systematic literature review and metanalysis. Eur Rev Med Pharmacol Sci 2009;13:299-307.
3.	Bigger JT Jr., Fleiss JL, Rolnitzky LM, Steinman RC, Schneider WJ. Time course of recovery of heart period variability after myocardial infarction. J Am Coll Cardiol 1991;18:1643-9.
4.	Casolo G, Balli E, Taddei T, Amuhasi J, Gori C. Decreased spontaneous heart rate variability in congestive heart failure. Am J Cardiol 1989;64:1162-7.
5.	Besnier F, Labrunée M, Richard L, Faggianelli F, Kerros H, Soukarié L, et al. Short-term effects of a 3-week interval training program on heart rate variability in chronic heart failure. A randomised controlled trial. Ann Phys Rehabil Med 2019;62:321-8.
6.	Pagani M, Malfatto G, Pierini S, Casati R, Masu AM, Poli M, et al. Spectral analysis of heart rate variability in the assessment of autonomic diabetic neuropathy. J Auton Nerv Syst 1988;23:143-53.
7.	Benichou T, Pereira B, Mermillod M, Tauveron I, Pfabigan D, Maqdasy S, et al. Heart rate variability in type 2 diabetes mellitus: A systematic review and meta-analysis. PLoS One 2018;13:e0195166.
8.	Guilleminault C, Connolly SJ, Winkle RA. Cardiac arrhythmia and conduction disturbances during sleep in 400 patients with sleep apnea syndrome. Am J Cardiol 1983;52:490-4.
9.	Patel N, Donahue C, Shenoy A, Patel A, El-Sherif N. Obstructive sleep apnea and arrhythmia: A systemic review. Int J Cardiol 2017;228:967-70.
10.	Ferini-Strambi L, Oldani A, Zucconi M, Smirne S. Cardiac autonomic activity during wakefulness and sleep in REM sleep behavior disorder. Sleep 1996;19:367-9.
11.	Shiomi T, Guilleminault C, Sasanabe R, Hirota I, Maekawa M, Kobayashi T. Augmented very low frequency component of heart rate variability during obstructive sleep apnea. Sleep 1996;19:370-7.
12.	Narkiewicz K, Montano N, Cogliati C, van de Borne PJ, Dyken ME, Somers VK. Altered cardiovascular variability in obstructive sleep apnea. Circulation 1998;98:1071-7.
13.	Khoo MC, Kim TS, Berry RB. Spectral indices of cardiac autonomic function in obstructive sleep apnea. Sleep 1999;22:443-51.
14.	Roche F, Gaspoz JM, Court-Fortune I, Minini P, Pichot V, Duverney D, et al. Screening of obstructive sleep apnea syndrome by heart rate variability analysis. Circulation 1999;100:1411-5.
15.	Lombardi C, Pengo MF, Parati G. Obstructive sleep apnea syndrome and autonomic dysfunction. Autonomic neuroscience. Basic Clin 2019;221:102563.
16.	Vanninen E, Tuunainen A, Kansanen M, Uusitupa M, Länsimies E. Cardiac sympathovagal balance during sleep apnea episodes. Clin Physiol 1996;16:209-16.
17.	Berry RB, Albertario CL, Harding SM, Lloyd RM, Plante DT, Quan SF, et al. The AASM manual for the scoring of sleep and associated events: Rules, terminology and technical specifications: American Academy of Sleep Medicine; 2018.
18.	Mietus JE, Peng CK, Henry I, Goldsmith RL, Goldberger AL. The pNNx files: Re-examining a widely used heart rate variability measure. Heart 2002;88:378-80.
19.	Zinchuk AV, Gentry MJ, Concato J, Yaggi HK. Phenotypes in obstructive sleep apnea: A definition, examples and evolution of approaches. Sleep Med Rev 2017;35:113-23.

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