Polysomnographic versus video scoring of large muscle group movements during sleep in children with restless sleep

Giuliano De Meo1, Melania Martucci1, Maria Ausilia Musumeci1

  • 1Department of Social and Developmental Psychology, Sapienza University, Rome, Italy.

Sleep Medicine
|December 3, 2022
PubMed

Insights

Polysomnography (PSG) scoring of large muscle movements (LMM) without video is more sensitive for detecting restless sleep disorder (RSD) than video-PSG. This method identifies over 95% of movements, suggesting updated diagnostic criteria may be needed.

Area of Science:

  • Pediatric Sleep Medicine
  • Neurophysiology
  • Sleep Disorders

Background:

  • Restless sleep is a common pediatric complaint, potentially indicating Restless Sleep Disorder (RSD).
  • Diagnosing RSD traditionally relies on video-polysomnography (vPSG) to count large muscle movements (LMM).
  • New scoring criteria for LMM on PSG alone exist, but their correlation with vPSG needs evaluation.

Purpose of the Study:

  • To compare the scoring of LMM using vPSG versus PSG signals alone in children with restless sleep.
  • To assess the sensitivity and correlation of PSG-only LMM scoring with vPSG-based scoring.

Main Methods:

  • A blinded scorer reviewed vPSG studies from 20 children with restless sleep.
  • LMM were scored first using video analysis (video-LMM) and then using PSG criteria without video (PSG-LMM).

Main Results:

  • PSG-LMM scoring detected significantly more movements per hour (8.6 ± 2.95 SD) than video-LMM (6.9 ± 2.40 SD).
  • Movement duration was similar between methods; 95.4% of video-LMM were also detected by PSG.
  • A PSG-LMM index of 6.24/hour was equivalent to 5 LMM/hour by video-LMM.

Conclusions:

  • PSG-LMM scoring criteria demonstrate high sensitivity, detecting over 95% of movements identified by vPSG.
  • The higher sensitivity of PSG-LMM suggests potential for improved RSD diagnosis.
  • Consideration of these criteria for inclusion in sleep scoring manuals is recommended, possibly with an adjusted index for RSD diagnosis.
Abstract

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