Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Diagnostic Accuracy of a Portable Electromyography and Electrocardiography Device to Measure Sleep Bruxism in a Sleep Apnea Population: A Comparative Study

Version 1 : Received: 30 June 2023 / Approved: 3 July 2023 / Online: 4 July 2023 (08:05:40 CEST)
Version 2 : Received: 12 September 2023 / Approved: 12 September 2023 / Online: 13 September 2023 (10:20:40 CEST)
Version 3 : Received: 12 November 2023 / Approved: 13 November 2023 / Online: 14 November 2023 (07:55:30 CET)

A peer-reviewed article of this Preprint also exists.

Cid-Verdejo, R.; Domínguez Gordillo, A.A.; Sánchez-Romero, E.A.; Ardizone García, I.; Martínez Orozco, F.J. Diagnostic Accuracy of a Portable Electromyography and Electrocardiography Device to Measure Sleep Bruxism in a Sleep Apnea Population: A Comparative Study. Clocks & Sleep 2023, 5, 717-733. https://doi.org/10.3390/clockssleep5040047 Cid-Verdejo, R.; Domínguez Gordillo, A.A.; Sánchez-Romero, E.A.; Ardizone García, I.; Martínez Orozco, F.J. Diagnostic Accuracy of a Portable Electromyography and Electrocardiography Device to Measure Sleep Bruxism in a Sleep Apnea Population: A Comparative Study. Clocks & Sleep 2023, 5, 717-733. https://doi.org/10.3390/clockssleep5040047

Abstract

Background: The gold standard for the diagnosis of sleep bruxism (SB) and obstructive sleep apnea (OSA) is Polysmnography (PSG). At the end of the apnea episodes there is frequently a final hy-permotor muscle activity that could act as a confusion factor in the diagnosis of SB with the elec-tromyography portable devices. The aim of this study was to compare the concordance on the number of episodes of SB in a population with OSA, between the diagnosis obtained by PSG, an-alyzed manually by a neurophysiologist and that obtained manually and automatically by a portable electromyography (EMG) and electrocardiography (EKG) device. Methods: Twenty-three subjects underwent one night of polysomnographic study with simulta-neous recording with the EMG-EKG device. The variables referring to the number of episodes and the SB index measured with both tools and analyzed in the manual and automatic modes were compared. Masticatory muscle activity was scored according to published criteria. The sample was segmented by severity of OSA according to AASM criteria. ANOVA, correlations, and the Bland–Altman plot were used to quantify the agreement between both methods. The concordance was calculated through the ICC. Results: The total events of SB per night in the PSG study were on average (8.17), lower than the one obtained with EMG-EKG manual analysis (14.13) and automatic (29.26). Both the SB PSG and Manual EMG-EKG episodes decrease from non-OSA (PSG = 16 ± 13,55, EMG-EKG = 16,83 ±11,58) to severe OSA (PSG = 3,14 ± 4,26, EMG-EKG = 9,86 ± 8,09). However, in the case of automatic EMG-EKG mode: the number of SB episodes in severe OSA doubled (41,23 ± 12,50) with respect to non OSA (24,50 ± 12,19). On average: the EMG-EKG device Automatic analysis measures 21.08 units more than PSG. The results with the manual EMG-EKG analysis improved. Conclusion: There is no concordance between the results obtained in the PSG neurophysiologic analysis and those obtained by means of the EMG-EKG device automatic and manual analysis for the diagnosis of SB in a population mostly with OSA. The OSA could act as a confusion factor in the diagnosis of SB with the electromyography portable devices, but further study is needed.

Keywords

bruxism; electromyography; sleep apnea; polysomnography; sleep bruxism; sleep wake disorders

Subject

Medicine and Pharmacology, Clinical Medicine

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