Factors that may influence the classification of sleep-wake by wrist actigraphy: the MrOS Sleep Study

影响腕部活动记录仪睡眠-觉醒分类的因素:MrOS睡眠研究

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Abstract

STUDY OBJECTIVES: Total sleep time (TST), sleep efficiency (SE), sleep latency (SOL) and wake after sleep onset (WASO) assessed by actigraphy gathered in 3 different modes were compared to polysomnography (PSG) measurements to determine which mode corresponded highest to PSG. Associations of measurement error for TST (PSG-actigraphy) with demographics, medical history, exam data, and sleep characteristics were examined. METHODS: Participants underwent in-home 12-channel PSG. Actigraphy data were collected in 3 modes: proportional integration mode (PIM), time above threshold (TAT) and zero crossings mode (ZCM). The analysis cohort was a subgroup of 889 men (mean age 76.4 years) from the MrOS Sleep Study with concurrently measured PSG and actigraphy. Intraclass correlation coefficients (ICCs) were used to compare the association between PSG and actigraphy. RESULTS: The PIM mode of actigraphy corresponded moderately to PSG for all measures (ICCs 0.32 to 0.57), TAT a little lower (ICCs 0.17 to 0.47), and ZCM lower still (ICCs 0.16 to 0.33). The PIM mode corresponded best to PSG (ICCs TST 0.57; SE 0.46; SOL 0.23; WASO 0.54), though the estimations from PSG and PIM mode differed significantly (p < 0.01). The PIM mode overestimated TST by 13.2 min on average, but underestimated TST for those in certain subgroups: those with excessive daytime sleepiness, less sleep fragmentation, or more sleep disordered breathing (p < 0.05). CONCLUSIONS: Sleep parameters from the PIM and TAT modes of actigraphy corresponded reasonably well to PSG in this population, with the PIM mode correlating highest. Systematic measurement error was observed within subgroups with different sleep characteristics.

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