Sleep Assessment in Critically Ill Adults: Established Methods and Emerging Strategies

Abstract

OBJECTIVES:. Sleep is a biological mandate with an integral role in optimizing functions that maintain psychological and physical health. During critical illness, however, sleep may be disrupted at best and elusive at worst. Sleep improvement efforts and research endeavors evaluating interventions to improve sleep in critically ill adults are hampered by limited methods available to measure sleep in this setting. This narrative review summarizes available modalities for sleep assessment in the ICU, describes new ICU sleep assessment methods under development, and highlights features of the ideal ICU sleep measurement tool. DATA SOURCES:. The most relevant literature and author experiences were assessed for inclusion from PubMed and textbooks. STUDY SELECTION:. The authors selected studies for inclusion by consensus. DATA EXTRACTION:. The authors reviewed each study and selected appropriate data for inclusion by consensus. DATA SYNTHESIS:. Currently available tools to measure sleep in critically ill adults have important flaws. Subjective measurements are limited by recall bias, the inability of many patients to communicate, and poorly correlate with objective measures when completed by surrogates. Actigraphy does not consider the effects of sedating medications or myopathy leading to an over estimation of sleep time. Polysomnography, the gold standard for sleep assessment, is limited by interpretation issues and practical application concerns. Single and multiple channel electroencephalogram devices offer real-time physiologic data and are more practical to use than polysomnography but are limited by the scope of sleep-specific information they can measure and poorly characterize the circadian system. CONCLUSIONS:. A measurement tool that offers real-time sleep and circadian assessment and is practical for broad application in the ICU does not exist. Newer sleep assessment devices have shown promise in measuring physiologic data in real time; when used in combination with other assessment modalities, and analyzed by computational techniques, they may revolutionize sleep monitoring in the ICU.