Comparison of rapid eye movement without atonia quantification methods to diagnose rapid eye movement sleep behavior disorder: a systematic review

Jung-Ick Byun; Tae-Won Yang; Jun-Sang Sunwoo; Won Chul Shin; Oh-Young Kwon; Ki-Young Jung

doi:10.1093/sleep/zsac150

Comparison of rapid eye movement without atonia quantification methods to diagnose rapid eye movement sleep behavior disorder: a systematic review

Sleep. 2022 Sep 8;45(9):zsac150. doi: 10.1093/sleep/zsac150.

Authors

Jung-Ick Byun¹, Tae-Won Yang^{2

3

4}, Jun-Sang Sunwoo⁵, Won Chul Shin¹, Oh-Young Kwon^{2

4

6}, Ki-Young Jung⁷

Affiliations

¹ Department of Neurology, Kyung Hee University Hospital at Gangdong, Kyung Hee University School of Medicine, Seoul, Republic of Korea.
² Department of Neurology, Gyeongsang National University College of Medicine, Jinju, Korea.
³ Department of Neurology, Gyeongsang National University Changwon Hospital, Changwon, Korea.
⁴ Institute of Health Science, Gyeongsang National University College of Medicine, Jinju, Korea.
⁵ Department of Neurology, Kangbuk Samsung Hospital, Seoul, Korea.
⁶ Department of Neurology, Gyeongsang National University Hospital, Jinju, Korea.
⁷ Department of Neurology, Seoul National University College of Medicine, Seoul National University Hospital, Seoul, Republic of Korea.

PMID: 35881545
DOI: 10.1093/sleep/zsac150

Abstract

Study objectives: Rapid eye movement (REM) sleep without atonia (RWA) is essential for diagnosing REM sleep behavior disorder (RBD). Manual and automatic quantifications of RWA that use different criteria have been validated. This study compared the RWA quantification methods for diagnosing RBD.

Methods: The PubMed, EMBASE, Web of Science, and Cochrane Library databases were systemically searched for studies published from inception to December 2021. The inclusion criteria were cohort, cross-sectional, and case-control studies assessing the sensitivity and specificity of RWA quantification methods. Pooled estimates of the sensitivity, specificity, diagnostic odds ratio (DOR), and area under the curve (AUC) were determined. Risk of bias and certainty of evidence was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool and the Grading of Recommendations, Assessment, Development, and Evaluations framework, respectively.

Results: Fourteen articles including 402 patients with RBD met the inclusion criteria. Manual methods evaluating any chin and phasic flexor digitorum superficialis (FDS) activity had the highest DOR (138.8, 95% CI = 21.8% to 881.7%) and AUC (0.9686). The automatic REM atonia index (RAI) showed similar or higher sensitivity (89.1%, 95% CI = 84.6% to 92.7%) but a lower specificity (73.5%), DOR (43.1), and AUC (0.9369) than the manual techniques.

Conclusions: In this meta-analysis, manual RWA quantification that employed chin or phasic FDS activity had the best RBD diagnostic performance. The automatic RAI method may be useful for screening patients with RBD. The results should be interpreted carefully because of the high risk of bias in patient selection and significant heterogeneity among the studies.

Prospero registration number: CRD42021276445.

Keywords: REM atonia index; REM sleep behavior disorder; REM sleep without atonia; diagnostic accuracy; meta-analysis.

Publication types

Meta-Analysis
Systematic Review
Research Support, Non-U.S. Gov't

MeSH terms

Cross-Sectional Studies
Electromyography / methods
Humans
Muscle Hypotonia / diagnosis
Polysomnography
REM Sleep Behavior Disorder* / diagnosis
Sleep, REM