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Sleep Med ; 119: 229-233, 2024 Jul.
Article in English | MEDLINE | ID: mdl-38704870

ABSTRACT

OBJECTIVE: Although manual scoring has been classically considered the gold standard to identify periodic leg movements (PLM), it is a very time consuming and expensive process, also subject to variability in interpretation. In the last decades, different authors have observed reasonably good agreement between automated PSG scoring algorithms and manual scoring in adults, according to established criteria. We aim to compare the automatic software analysis of our polysomnogram with the manual staging in children with sleep-disordered breathing. METHODS: We performed a semiautomatic method, in which an experienced technician watched the video recording and removed from the automatic analysis those movements that did not correspond to true candidate leg movement (LM). RESULTS: A total of 131 PSGs were studied; applying the established criteria, 65 children were diagnosed of obstructive sleep apnea, and 66 presented snoring but with no sleep apnea. The mean age was 6.7 years (±1.7) and twenty-five children (19.08 %) had a PLMI >5/h. Statistical differences were found not only for PLMI (manual: 2.20 (0.7, 4.1) vs automatic (6.4 (3.85,9.5); p < 0.001), but for almost of all indexes assessed between the automatic and the manual scoring analysis. The level of concordance was only moderate for PLM index (0.63 [0.51-0.72]); showing that, unlike the articles published in the adult population, automatic analysis is not accurate in children and, manually or semi-automatically analysis as ours need to be done. CONCLUSION: It seems that PLM detection algorithm might work accurately but, the real need would be a true LM detection algorithm.


Subject(s)
Nocturnal Myoclonus Syndrome , Polysomnography , Humans , Polysomnography/methods , Child , Male , Female , Nocturnal Myoclonus Syndrome/diagnosis , Nocturnal Myoclonus Syndrome/physiopathology , Algorithms , Child, Preschool , Sleep Apnea, Obstructive/diagnosis , Sleep Apnea, Obstructive/physiopathology , Video Recording , Software
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