0169 Misaligned Core Body Temperature Rhythms Impact Cognitive Performance of Hospital Shift Work Nurses

Introduction Circadian rhythms greatly influence 24-h variation in cognition in nearly all organisms, including humans. Circadian clock impairment and sleep disruption are detrimental to cognition and negatively influence the acquisition and recall of learned behaviors. The circadian clock can become out of sync with the environment during circadian misalignment. Shift work represents a real-world model of circadian misalignment that can be studied for its physiological implications. The present study aimed to test the hypothesis that circadian misalignment disrupts vigilance and cognitive performance on occupationally relevant tasks using shift work as a model. As such, we sought to 1) explore the general effects of night- and day-shift worker schedules on sleep-wake parameters and core body temperature (CBT) phase, and 2) determine whether shift-type and CBT phase impact cognitive performance and vigilance at the end of a 12-hour shift. Methods We observed a sample of day-shift and night-shift hospital nurses over a 10-day period. At the end of three, consecutive, 12-hour shifts (7pm-7am or 7am-7pm), participants completed a cognitive battery assessing vigilance, cognitive throughput, and medication calculation fluency (via an investigator developed and tested metric). Results Night-shift nurses exhibited significantly greater sleep fragmentation as well as a greater disparity between their wake-time and time of CBT minimum compared to day-shift nurses. Nightshift nurses exhibited significantly slower cognitive proficiency at the end of their shifts, even after adjustment for CBT phase. Conclusion These results suggest that circadian disruption and reduced sleep quality both contribute to cognitive functioning and performance. Support (If Any) This work was supported by an intramural Dean’s Scholar Award from the School of Nursing, University of Alabama at Birmingham, the National Center for Advancing Translational Sciences of the National Institutes of Health (NIH) under award number UL1TR001417 and the UAB Vision Science Research Core grant VSRC core NIH grant P30 EY003039.