Probabilistic sleep architecture models in patients with and without sleep apnea

摘要: Sleep fragmentation of any cause is disruptive to the rejuvenating value sleep. However, methods quantify sleep architecture remain limited. We have previously shown that human sleep–wake stage distributions exhibit multi-exponential dynamics, which are fragmented by obstructive apnea (OSA), suggesting Markov models may be a useful method in health and disease. data were obtained from two subsets Heart Health Study database: control subjects with no medications, OSA, medical co-morbidities sleepiness (n = 374); severe OSA 338). was simplified into three stages: wake after onset (WASO); non-rapid eye movement (NREM) sleep; rapid (REM) The connectivity transition rates among eight ‘generator’ states first-order continuous-time model inferred observed (‘phenotypic’) distributions: exponentials each NREM WASO; REM Ultradian cycling accomplished imposing time-variation state entry rates. Fragmentation involved faster probabilities as well additional paths within model. important features architecture: dynamics (accounting for bout distributions); probabilistic transitions (an inherent source variability). In addition, quantifies associated OSA. prove quantifying disruption provide objective metrics correlate endpoints ranging cardiovascular morbidity.