Defining morphology of periodic leg movements in sleep: an evidence-based definition of a minimum window of sustained activity

Reinventing polysomnography in the age of precision medicine

For almost 50 years, sleep laboratories around the world have been collecting massive amounts of polysomnographic (PSG) physiological data to diagnose sleep disorders, the majority of which are not utilized in the clinical setting. Only a small fraction of the information available within these signals is utilized to generate indices. For example, the apnea-hypopnea index (AHI) remains the primary tool for diagnostic and therapeutic decision-making for obstructive sleep apnea (OSA) despite repeated studies showing it to be inadequate in predicting clinical consequences. Today, there are many novel approaches to PSG signals, making it possible to extract more complex metrics and analyses that are potentially more clinically relevant for individual patients. However, the pathway to implement novel PSG metrics/analyses into routine clinical practice is unclear. Our goal with this review is to highlight some of the novel PSG metrics/analyses that are becoming available. We suggest that stronger academic-industry relationships would facilitate the development of state-of-the-art clinical research to establish the value of novel PSG metrics/analyses in clinical sleep medicine. Collectively, as a sleep community, it is time to reinvent how we utilize the polysomnography to move us towards Precision Sleep Medicine.

Effects of new PLM scoring rules on PLM rate in relation to sleep and resting wake for RLS and healthy controls

PURPOSE

This study evaluates the differences in periodic leg movement (PLM) rates for Restless Legs Syndrome (RLS) and healthy controls when using the updated PLM scoring criteria developed by IRLSSG in 2016 versus the prior PLM scoring criteria developed by IRLSSG in 2006. Four major problems with the prior standards had been objectively identified, i.e. minimum inter-movement interval should be 10 not 5 s, non-PLM leg movements should end any preceding PLM sequence, a leg movement (LM) can be any length > 0.5 s, and a PLM should be a persisting movement not a couple or a series of closely spaced, very brief events. Each of these led to including, erroneously, various random leg movements as PLM. Correcting these problems was expected to increase specificity, reducing the number of PLM detected, particularly in situations producing relatively more random leg movements, e.g. wake vs. sleep and controls without PLMD vs. RLS patients.

METHODS

This study evaluated the putative benefits of the updated, 2016-scoring criteria. The LMs from 42 RLS patients and 30 age- and gender-matched controls were scored for PLMS and PLMW from standard all-night PSG recordings using both 2006 and 2016 WASM criteria.

RESULTS/CONCLUSION

The results confirmed that that the 2016 compared to the 2006 criteria generally decreased the PLM rates with particularly large decreases for the conditions with more random non-PLM events, e.g. wake times and normal healthy controls. This supported the view that the new criteria succeeded in increasing the specificity of PLM detection. Moreover, the changes in PLM rates were generally small for the conditions with relatively few random LM, e.g. RLS and sleep. Thus the bulk of existing PLMS research does not require reconsideration of results, with possible exception of special situations with relatively more random leg movements than periodic leg movements, e.g. wake, healthy normals and children.