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Association between early stage N2 sleep spindle burst characteristics and vigilance groups: an observational study on patients from a tertiary sleep centre

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Objective. Obstructive sleep apnoea (OSA) is associated with impaired vigilance. This paper examines the hypothesis that sleep spindle (Sp) characteristics during nocturnal sleep can be mapped to vigilance deficits measured… Click to show full abstract

Objective. Obstructive sleep apnoea (OSA) is associated with impaired vigilance. This paper examines the hypothesis that sleep spindle (Sp) characteristics during nocturnal sleep can be mapped to vigilance deficits measured by the psychomotor vigilance task (PVT) in patients with OSA. Approach. The PVT was performed prior to In-laboratory Polysomnography for 250 patients. PVT outcomes were clustered into three vigilance groups (VGs). Spindles were scored manually for a Training Cohort of 55 patients, (9491 Sps) across different blocks of NREM sleep (SBs) and validated in a Test Cohort (25 patients, 4867 Sps). We proposed a novel set of Sp features including a spindle burst index (SBI), which quantifies the burst characteristics of spindles and constructed models mapping them to VGs. We also explored the performance of conventional Sp features (such as Sp number and density) in our modelling approach. Main results. In the Training Cohort, we observed statistically significant differences in the SBI across VGs and SBs independent of OSA severity (1st stage N2 SBI; p = <0.001 across VGs). In the Test Cohort, a Model based on the proposed SBI predicted VG membership with 88% accuracy. A model based on conventional Sp features mapped to VGs with 80% accuracy, and a model using mixed burst and conventional features reached an accuracy of 88%. Significance. Spindle features measured during diagnostic In-laboratory polysomnography measurements can be mapped to PVT outcomes. The novel SBI proved useful for exploring the relationship between PVT outcomes and sleep. Further studies in larger populations are needed to verify these conclusions.

Keywords: burst characteristics; spindle burst; vigilance groups; cohort; sleep spindle; vigilance

Journal Title: Physiological Measurement
Year Published: 2022

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