Delirium Clinical Trial
Official title:
Objective Assessment of Delirium in Hospitalized Patients
The aim of the present study is to implement a novel body-worn sensor, the ZephyrTM BioModule (the registered name for the wearable sensor device used in our study), for assessing physical activity and physiological measures in a clinical setting together with other clinical routine assessments. Our specific aim is to explore whether and how specific physical activity pattern and physiological measures are associated with delirium in hospital inpatient. Our ultimate goal is early detection and intervention of delirium, and better management through monitoring of activity pattern and physiological information. The ZephyrTM a U.S. FDA-approved wireless, ambulatory physiological monitoring device that consists of a data logger and transmitter unit which is attached at the location of the 5th intercostal space using a specifically designed patch (BioPatchTM) and standard ECG electrodes. The ZephyrTM is designed for long-term measurement of a patient's physical activity and physiological measures. By using the physical activity parameters and physiological measures, a specific delirium risk profile will be computed for each patient. Finally, the association of this delirium risk profile with CAM-ICU questionnaire as a gold standard will be assessed.
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).
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Time Perspective: Prospective
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