ICU_Delirium: Intelligent Intensive Care Unit
Study Details
Study Description
Brief Summary
Delirium, as a common complication of hospitalization, poses significant health problems in hospitalized patients. Though about a third of delirium cases can benefit from intervention, detecting and predicting delirium is still very limited in practice. A common characterization of delirium is change in activity level, causing patients to become hyperactive or hypoactive which is manifested in facial expressions and total body movements. This pilot study is designed to test the feasibility of a delirium detection system using movement data obtained from 3-axis wearable accelerometers and commercially available camera with facial recognition video system in conjunction with electronics medical record (EMR) data to analyze the relation of whole-body movement and facial expressions with delirium.
| Condition or Disease | Intervention/Treatment | Phase |
|---|---|---|
|
Detailed Description
The aim of the study is to assess the potential of using motion and facial expression data to detect delirium in ICU patients by comparing motion and facial expression patterns in delirium and control groups. In this study, the investigators will use ActiGraph accelerometers to record each subject's movement patterns. Also, a processed video using a commercially available camera interfaces with a specialized program to identify patient facial expressions and movement patterns. A total of 60 participants will be enrolled with delirium, and 30 patients without delirium will be used as control group. Motion profiles will be compared in the motorically defined subgroups (hyperactive, hypoactive, normal) based on accelerometer and facial recognition data. Then, differences in facial expression, number of changes in postures, and percentage of time spent moving will be compared between motorically defined subgroups and in delirium and control groups. EMR data will also be used to assess the feasibility of detecting delirium by including additional information on related risk factors.
Study Design
Arms and Interventions
| Arm | Intervention/Treatment |
|---|---|
| Delirium group ICU patients with a positive Confusion Assessment Method (CAM) score; observational using accelerometers, commercially available camera, and Internet Pod (iPod). |
Behavioral: Confusion Assessment Method
Confusion Assessment Method (CAM) score
Device: Accelerometer
3 accelerometers (placed on upper arm, wrist and ankle) and 1 placed on wall as ambient light sensor
Device: Commercially available camera
As part of facial recognition video system
Other Names:
Device: Internet Pod (iPod)
Monitors noise levels in the room
Other Names:
|
| Control group ICU patients with a negative Confusion Assessment Method (CAM) score; observational using accelerometers, commercially available camera, and Internet Pod (iPod). |
Behavioral: Confusion Assessment Method
Confusion Assessment Method (CAM) score
Device: Accelerometer
3 accelerometers (placed on upper arm, wrist and ankle) and 1 placed on wall as ambient light sensor
Device: Commercially available camera
As part of facial recognition video system
Other Names:
Device: Internet Pod (iPod)
Monitors noise levels in the room
Other Names:
|
| Healthy control group Healthy subjects that sleep in their home environment; observational using accelerometers, cortisol swabs, and Internet Pod (iPod) |
Device: Accelerometer
3 accelerometers (placed on upper arm, wrist and ankle) and 1 placed on wall as ambient light sensor
Device: Internet Pod (iPod)
Monitors noise levels in the room
Other Names:
Diagnostic Test: Cortisol Swab
Cortisol level collected through self administered salivary swab
|
Outcome Measures
Primary Outcome Measures
- CAM/CAM-ICU [Changes from Baseline up to 7 Days]
Confusion Assessment Method for detection of delirium
- Memorial Delirium Assessment Scale (MDAS) will be used for changes from baseline up to 7 days between the groups. [Changes from Baseline up to 7 Days]
MDAS denotes motor profile and defines motor subtyping. It has 10 items which assesses several areas of cognitive functioning (memory, attention, orientation and disturbances in thinking) and psychomotor activity. The items are rated on a four point scale (0-3) based on the current interaction with the patient or by assessment of behavior. A score of 13 shows the diagnosis of delirium.
- Delirium Motor Subtyping Scale (DMSS-4) will be used for changes from baseline up to 7 days between the groups. [Changes from Baseline up to 7 Days]
Scoring from DMSS-4 which has 5 hyperactive and 8 hypoactive symptoms requires at least two symptoms to be present from either the hyperactive or hypoactive list to meet subtype criteria. The higher the score the higher the delirium.
- Freedman Sleep Scale [Changes from Baseline up to 7 Days]
To determine sleep quality of patient for given day.
Secondary Outcome Measures
- Number of subjects who died [Baseline up to 7 Days]
Death at any time during admission
- Number of subjects on mechanical ventilation [greater than 48 hours]
Number of subjects requiring mechanical ventilation greater than 48 hours.
Other Outcome Measures
- Facial amimia versus non-amimia expressions between the groups [Changes from Baseline up to 7 Days]
Frequency of presence of facial amimia versus non-amimia expressions between the groups.
- Dynamic activity versus static position [Changes from Baseline up to 7 Days]
Percentage of time spent moving versus static position
Eligibility Criteria
Criteria
Inclusion Criteria (ICU Patients):
-
Intensive care unit patient
-
18 years of age or older
Exclusion Criteria (ICU Patients):
-
Anticipated intensive care unit stay less than one day
-
Less than 18 years of age
-
Inability to wear a motion sensor watch (ActiGraph)
Inclusion Criteria (Healthy Controls):
-
18 years of age or older.
-
sleeps in home environment
Exclusion Criteria (Healthy Controls):
-
does not sleep in home environment
-
Less than 18 years of age
-
Inability to wear a motion sensor watch (ActiGraph)
Contacts and Locations
Locations
| Site | City | State | Country | Postal Code | |
|---|---|---|---|---|---|
| 1 | UF Health | Gainesville | Florida | United States | 32610 |
Sponsors and Collaborators
- University of Florida
- U.S. National Science Foundation
- National Institute for Biomedical Imaging and Bioengineering (NIBIB)
- National Institute of Neurological Disorders and Stroke (NINDS)
Investigators
- Principal Investigator: Azra Bihorac, MD, University of Florida
Study Documents (Full-Text)
None provided.More Information
Publications
None provided.- IRB201400546 -N
- 1750192
- 1R21EB027344-01
- R01NS120924-01