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Journal Article
Validation Studies
Validation of a leg movements count and periodic leg movements analysis in a custom polysomnography system.
BMC Neurology 2017 Februrary 24
BACKGROUND: Periodic leg movements (PLM) during sleep (PLMS) are considered strongly related to restless legs syndrome (RLS), and are associated with polymorphisms in RLS risk genes. Various software for automatic analysis of PLMS are available, but only few of them have been validated. Aim of this study was to validate a leg movements count and analysis integrated in a commercially available polysomnography (PSG) system against manual scoring.
METHODS: Twenty RLS patients with a PLMS index > 20/h and 20 controls with a PLMS index < 5/h were included. Manual and computerized scoring of leg movements (LM) and PLM was performed according to the standard American Academy of Sleep Medicine (AASM) criteria. LM and PLM indices during sleep and wakefulness, the rate of PLMS associated with respiratory events, intermovement interval and periodicity indices were manually and automatically scored.
RESULTS: The correlation between manual and computerized scoring was high for all investigated parameters (Spearman correlation coefficients 0.751-0.996, p < 0.001; intraclass correlation coefficients 0.775-0.999, p < 0.001). Bland-Altman plots showed high agreement between manual and automatic analysis.
CONCLUSIONS: This study validated an automatic LM count and PLM analysis against the gold standard manual scoring according to AASM criteria. The data demonstrate that the software used in this study has an outstanding performance for computerized LM and PLM scoring, and LM and PLM indices generated with this software can be reliably integrated in the routine PSG report. This automatic analysis is also an excellent tool for research purposes.
METHODS: Twenty RLS patients with a PLMS index > 20/h and 20 controls with a PLMS index < 5/h were included. Manual and computerized scoring of leg movements (LM) and PLM was performed according to the standard American Academy of Sleep Medicine (AASM) criteria. LM and PLM indices during sleep and wakefulness, the rate of PLMS associated with respiratory events, intermovement interval and periodicity indices were manually and automatically scored.
RESULTS: The correlation between manual and computerized scoring was high for all investigated parameters (Spearman correlation coefficients 0.751-0.996, p < 0.001; intraclass correlation coefficients 0.775-0.999, p < 0.001). Bland-Altman plots showed high agreement between manual and automatic analysis.
CONCLUSIONS: This study validated an automatic LM count and PLM analysis against the gold standard manual scoring according to AASM criteria. The data demonstrate that the software used in this study has an outstanding performance for computerized LM and PLM scoring, and LM and PLM indices generated with this software can be reliably integrated in the routine PSG report. This automatic analysis is also an excellent tool for research purposes.
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