Assessment of Delirium in Hospitalized Patients

After obtaining written informed consent and Protected Health Information (PHI) consent, CAM-ICU (Confusion Assessment Method for the ICU) will be measured routinely by unit nurses each shift. Results will be available in the medical record. We will then measure physical activity and physiological measures (e.g. ECG, heart rate, respiration rate, and body temperature) using an unobtrusive body worn sensor. This sensor will be attached to the 5th intercostal space using a specifically designed patch (BioPatchTM) to allow quantification of physical activity such as walking, standing, sitting, lying, as well as measurement of other physiological parameters. These measurements will only be available to the research team and will not be available to the nurses on the inpatient study unit. Medical history (from clinic chart) and demographic information will be obtained, such as age, gender, weight, and height as well as details (e.g. injuries, fall score and number of falls) which happened during hospital stay. The research tests consist of one core measurements and one ancillary measurements (as required) as listed below (Note - ancillary measurement may not be required for everyone).

Core measurements Assessment of physical activity and physiological measures: Patients will be asked to wear the Zephyr BioModule for a period of 24 hours to maximum stay in the hospital. The Zephyr BioModule will be attached to the patients to the 5th intercostal space using a specifically designed patch (BioPatchTM).

Ancillary Measurements Upper Extremity Test: A validated body worn sensors (LEGSys™, Biosensics LLC) will be used to evaluate upper extremity kinematics (angular velocities). This is a simple test where the patient flexes and extends their arm for 20 seconds on each arm.

Analysis plan:

To predict the risk of delirium using physical activity and physiological data, each patient participating in the study will be categorized as to presence of delirium based on CAM-ICU questionnaire. Logistic regression analysis will be used to examine the relation between each physical activity variable (e.g. lying time) and physiological measures (e.g. heart rate) with delirium risk. Firstly, univariate logistic regression, using presence of delirium as the dependent variable, will be employed to investigate the relationship of the test variables. The Odd Ratios (OR) and coefficient of determination (R2) will be calculated for each explanatory variable. Then multivariate logistic regression using stepwise-automated methods will be performed to investigate the independent effects of the physical activity variables and physiological measures in predicting delirium. Sensitivities, specificities, positive and negative predictive values of different cut-off values will be calculated for any non-categorical variable shown to have an independent effect on predicting delirium. A two-sided P-value ≤0.05 will be considered to be statistically significant. Statistical analysis will be performed using SPSS (Statistical Package for the Social Sciences) statistics 22.0 (IBM, Armonk (name of town), NY (New York), USA).