Pilot Study: Delirium in the Intensive Care Unit Utilizing the Z Machine sleep monitor for assessment


Karmen Gee, Ashley Gentry, Caroline Lewis


Holroyd-Leduc, J. M., Khandwala, F., & Sink, K. M. (2010) state that “Delirium is defined as an acute disturbance of consciousness accompanied by a change in cognition or by development of a perceptual disturbance” (p. 465). It can develop in a very short amount of time, and the course it runs is often different in the patients it affects. Delirium has been noted as an increased finding in the hospital with as high as seventy-four percent of surgical patients and eleven to forty-two percent of general in-patients suffering from it (Holroyd-Leduc, J. M., Khandwala, F., & Sink, K. M. 2010). The majority of the patients in the hospitals that suffer from delirium tend to be in the Intensive Care Unit (ICU). Many different factors predispose a patient to developing delirium. According to Girard et al. (2008), these factors can be broken down into two categories: issues that the patient had upon admission into the hospital and issues that the patient develops while being in the hospital. Older age, alcoholism, cognitive impairment, depression, hypertension, and smoking are all examples of patient characteristics that increase the risk of developing delirium. Immobilization while in the hospital, some medications, and sleep disturbances can also place a patient at increased risk for developing delirium.

Many studies have been done as to whether or not lack of sleep and delirium are related. It has long been a debate that, if related, does lack of sleep cause delirium, or does delirium lead to a lack of sleep? According to Helton and colleagues (as cited by Figueroa-Ramos, Arroyo-Novoa, Lee, Padilla, and Puntillo, 2009), patients experiencing sleep deprivation were at a much higher risk to develop delirium than were those patients who were not experiencing any problems with sleep. Whitcomb, et al (2012) also focused on lack of sleep and the development of delirium and identifying environmental factors that possibly contribute to the syndrome. The results showed that there is a relationship between sedation, lack of rapid eye movement sleep and delirium.


The purpose of this research is to monitor the sleep-wake cycle of patients in the Medical Intensive Care Unit using a Z-machine in an attempt to explore the relationship between sleep deprivation and delirium. Keywords such as delirium, intensive care unit (ICU), and sleep were used to locate articles. The question of the effect of abnormal sleep-wake cycles on ICU patient delirium is important because delirium hinders patient healing and is a cost absorbed by the hospital. The past year has yielded more articles discussing delirium related to sleep-wake cycles but there is still a lack of research that focuses solely on the effects of sleep. If this research proves significant, it can greatly affect how ICU’s are operated and potentially limit the number of delirious patients in the ICU.

Research Design

Subjects identified to meet inclusion criteria on admission age 18 years old or greater, data collected with the wireless system Z-Machine from 9pm-6am (2100-0600) for 7 consecutive nights and data collection sheet for time in room.

Data to be collected from the patient's charts and Z-Machine to correlate the Z score with the daily ICDSC score.

Data collection form for each subject

A staff nurse will be the user of the Z-machine device. They will obtain consent/informational sheet from the patient or appropriate proxy and will apply the device to the patient. A staff nurse will provide education to the ICU staff on this protocol who has been educated in the protocol process.

Sample - Medical/Pulmonary Intensive Care Unit patients on sedation drips and ventilation support age 18 years and older.

Subject Inclusion and Selection Criteria - Inclusion criteria will be adults 18 years of age and older who are admitted to the MICU who are on sedation and mechanical ventilation.

Subject Exclusion - Studies have demonstrated that age 65 and older have an increase in the incidence of delirium in the intensive care unit (Angus, Shorr, White et al 2006). In a previous pilot study we found that many other subjects could have been included less than 65 years of age who developed delirium, therefore we are reducing the age to 18 to capture all eligible subjects. Subjects who have a diagnose that prohibits the assessment of mental awareness.

Subject Recruiting Methods - New admission to MICU who meet the above selection criteria.

Justification of Subject Population - This has been identified in the literature as the most susceptible population to delirium in an ICU setting (Angus, Shorr, White et al 2006), however in this study we have reduced the age limit based on prior study conducted.

Data Analysis

Statistics used will be descriptive statistics in the data analysis. Frequency counts analyzed as percent sample characteristics and mean response times will be the major units of analysis. The Nurse Educator and a staff nurse, who previously did undergraduate work in a similar creative inquiry study have been identified to be the user of the Z-machine device. They will obtain consent from the patient or appropriate proxy and will apply the device to the patient. The Nurse Educator and staff nurse will provide education to the MICU staff on this protocol. The trained nurses on staff will be filling out the count sheet of times entered the room and the ICDSC.


The Z machine Insight (and Insight+) processes a single channel of spontaneous EEG data from the differential-mastoid (A1-A2) location to determine the sleep stage of the user as either wake, light sleep (N1 & N2), deep sleep (N3) or REM. The sleep staging output is updated every 30 seconds throughout the recording. The Z machine contains an integrated low-noise, wide-bandwidth EEG amplifier, high-speed impedance measurement circuitry, and an on-board processor running the sleep staging algorithms. The hardware and algorithms are all FDA cleared. Also the Intensive Care Delirium Screening Checklist (ICDSC) will be used, along with a count sheet which will record every time the room was entered and what was done.

Z Machine Insight Monitor - http://www.generalsleep.com/
A1-A2 location noted on each ear - http://www.autodidacts.io/binaural-beat-openbci-eeg-experiment/
Intensive Care Delirium Screening Checklist

Research Implications

This study is very important for our research team to explore, because there is not much literature on the topic yet. Many articles explore the types and significance of delirium in the ICU related to distractions (bright lights, care from nurses, noise, etc.) but there is little or no research done on the effects of sedation and failure to enter REM sleep causing delirium. If this research proves significant, it can greatly affect how ICU’s are operated and potentially limit the number of delirious patients in the ICU. Instead of using sedatives to help patients “sleep” health care workers could begin to consider other routes and hopefully limit sedation so that patients can reach REM sleep. This information has the potential to effect nurses, intensivists, doctors, as well as patients who are hospitalized in the ICU. There has been a lot of work done on the subject of delirium in the ICU including the types of delirium, tools used to assess delirium, and sedatives related to delirium, just to name a few. These topics have been studied mostly from the perspective of the doctors and nurses.


Dr. John Whitcomb, PhD, RN, CCRN, FCCM


Angus, D, Shorr, A., White. A. et al. (2006). Critical Care delivery in the United States: distribution of services and compliance with Leapfrog recommendations. Crit Care Med.34(4), 1016-1024.

Figueroa-Ramos, M.I., Arroyo-Novoa, C.M., Lee, K.A., Padilla, G., & Puntillo, K.A. (2009). Sleep and delirium in ICU patients: A review of mechanisms and manifestations. Journal of Intensive Care Medicine, 35, 781–795. doi:10.1007/s00134-009-1397-4

Holroyd-Leduc, J. M., Khandwala, F., & Sink, K. M. (2010). How can delirium best be prevented and managed in older patients in the hospital? CMAJ, 182, (465-470). doi:10.1503/cmaj.080519

Whitcomb, J., Morgan, M., Irvin, T., Spencer, K., Turman, S., Boynton, L., Rhodes, C. (2013) A Pilot Study: Delirium in the Intensive Care Unit: Utilizing the Zeo Wireless Sleep Monitor for assessment. A Creative Inquiry Project with Undergraduate Nursing Students. Dimensions of Critical Care Nursing (Sept/Oct 2013, 32(5):266-270)

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