Sleep medicine · 2015
MATPLM1, A MATLAB script for scoring of periodic limb movements: preliminary validation with visual scoring.
Сравнительное исследованиеСтатьяВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Huang Andy S, Skeba Patrick, Yang Myung S, Sgambati Francis P, Earley Christopher J, Allen Richard P
Аннотация
BACKGROUND AND PURPOSE: A Matrix Laboratory (MATLAB) script (MATPLM1) was developed to rigorously apply World Associations of Sleep Medicine (WASM) scoring criteria for periodic limb movements in sleep (PLMS) from bilateral electromyographic (EMG) leg recordings. This study compares MATPLM1 with both standard technician and expert detailed visual PLMS scoring.
METHODS AND SUBJECTS: Validation was based on a 'macro' level by agreement for PLMS/h during a night recording and on a 'micro' level by agreement for the detection of each PLMS from a stratified random sample for each subject. Data available for these analyses were from 15 restless leg syndrome (RLS) (age: 61.5 ± 8.5, 60% female) and nine control subjects (age: 61.4 ± 7.1, 67% female) participating in another study.
RESULTS: In the 'micro' analysis, MATPLM1 and the visual detection of PLMS events agreed 87.7% for technician scoring and 94.4% for expert scoring. The technician and MATPLM1 scoring disagreements were checked for 36 randomly selected events, 97% involved clear technician-scoring error. In the 'macro' analysis, MATPLM1 rates of PMLS/h correlated highly with visual scoring by the technician (r(2) = 0.97) and the expert scorer (r(2) = 0.99), but the technician scoring was consistently less than MATPLM1: median (quartiles) difference: 10 (5, 23). There was little disagreement with expert scorer [median (quartile) difference: -0.3 (-2.4, 0.3)].
CONCLUSIONS: The MATPLM1 produces reliable scoring of PLMS that matches expert scoring. The standard visual scoring without careful measuring of events tends to significantly underscore PLMS. These preliminary results support the use of MATPLM1 as a preferred method of scoring PLMS for EMG recordings that are of a good quality and without significant sleep-disordered breathing events.
METHODS AND SUBJECTS: Validation was based on a 'macro' level by agreement for PLMS/h during a night recording and on a 'micro' level by agreement for the detection of each PLMS from a stratified random sample for each subject. Data available for these analyses were from 15 restless leg syndrome (RLS) (age: 61.5 ± 8.5, 60% female) and nine control subjects (age: 61.4 ± 7.1, 67% female) participating in another study.
RESULTS: In the 'micro' analysis, MATPLM1 and the visual detection of PLMS events agreed 87.7% for technician scoring and 94.4% for expert scoring. The technician and MATPLM1 scoring disagreements were checked for 36 randomly selected events, 97% involved clear technician-scoring error. In the 'macro' analysis, MATPLM1 rates of PMLS/h correlated highly with visual scoring by the technician (r(2) = 0.97) and the expert scorer (r(2) = 0.99), but the technician scoring was consistently less than MATPLM1: median (quartiles) difference: 10 (5, 23). There was little disagreement with expert scorer [median (quartile) difference: -0.3 (-2.4, 0.3)].
CONCLUSIONS: The MATPLM1 produces reliable scoring of PLMS that matches expert scoring. The standard visual scoring without careful measuring of events tends to significantly underscore PLMS. These preliminary results support the use of MATPLM1 as a preferred method of scoring PLMS for EMG recordings that are of a good quality and without significant sleep-disordered breathing events.