A 24% prevalence of excessive fragmentary myoclonus in 500 consecutive sleep laboratory patients.
Melanie BergmannAmbra StefaniAbubaker IbrahimVictoria AnselmiElisabeth BrandauerBirgit HöglMatteo CesariPublished in: Journal of sleep research (2023)
Excessive fragmentary myoclonus (EFM) is a frequent finding during routine video-polysomnography (VPSG). We aimed to automatically measure the prevalence of EFM according to current American Academy of Sleep Medicine (AASM) criteria, and the fragmentary myoclonus index (FMI) in sleep stage N1, N2, N3, rapid eye movement (REM) sleep and wake in a large patient population. A total of 500 VPSG recordings of patients admitted to the Sleep Laboratory, Department of Neurology, Medical University of Innsbruck, Austria, between May 1, 2022 and February 28, 2023, were included. EFM according to AASM criteria and FMI were computed by applying a previously validated algorithm. EFM was automatically detected in 121 of the 500 Sleep Laboratory patients (24.2%, 95% confidence interval 20.1%-28.9%). FMI increased with age, male gender, apnea-hypopnea-index (AHI), oxygen desaturation index (ODI), and periodic leg movements of sleep (PLMS) index. FMI was highest in REM sleep behaviour disorder (RBD), followed by neurodegenerative and internal medicine diseases, but the increase in the FMI was not explained by the disease itself but rather by the age and sex of the patients. Almost a quarter of our patient population had EFM. However, the prevalence of EFM does not allow the drawing of any conclusions about the pathophysiology of EFM or even the determination of a pathological FMI cut-off value. Associations of the FMI with age, sex, AHI, ODI and PLMS are in line with previous studies, but the FMI needs to be evaluated in different disease entities to learn more about its pathophysiology.
Keyphrases
- end stage renal disease
- sleep quality
- physical activity
- ejection fraction
- newly diagnosed
- chronic kidney disease
- obstructive sleep apnea
- peritoneal dialysis
- healthcare
- risk factors
- machine learning
- case report
- magnetic resonance imaging
- computed tomography
- magnetic resonance
- mass spectrometry
- depressive symptoms
- patient reported outcomes
- body mass index
- clinical practice
- tandem mass spectrometry