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| ID | Type | Description | Link |
|---|---|---|---|
| 1750192 | Other Grant/Funding Number | National Science Foundation | |
| 1R21EB027344-01 | U.S. NIH Grant/Contract | View source | |
| R01NS120924-01 | U.S. NIH Grant/Contract | View source |
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| Name | Class |
|---|---|
| U.S. National Science Foundation | FED |
| National Institute for Biomedical Imaging and Bioengineering (NIBIB) | NIH |
| National Institute of Neurological Disorders and Stroke (NINDS) | NIH |
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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Delirium group | ICU patients with a positive Confusion Assessment Method (CAM) score; observational using accelerometers, commercially available camera, and Internet Pod (iPod). |
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| Control group | ICU patients with a negative Confusion Assessment Method (CAM) score; observational using accelerometers, commercially available camera, and Internet Pod (iPod). |
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| Healthy control group | Healthy subjects that sleep in their home environment; observational using accelerometers, cortisol swabs, and Internet Pod (iPod) |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Confusion Assessment Method | Behavioral | Confusion Assessment Method (CAM) score |
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| Measure | Description | Time Frame |
|---|---|---|
| CAM/CAM-ICU | Confusion Assessment Method for detection of delirium | Changes from Baseline up to 7 Days |
| Memorial Delirium Assessment Scale (MDAS) will be used for changes from baseline up to 7 days between the groups. | 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. | Changes from Baseline up to 7 Days |
| Delirium Motor Subtyping Scale (DMSS-4) will be used for changes from baseline up to 7 days between the groups. | 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. | Changes from Baseline up to 7 Days |
| Freedman Sleep Scale | To determine sleep quality of patient for given day. | Changes from Baseline up to 7 Days |
| Measure | Description | Time Frame |
|---|---|---|
| Number of subjects who died | Death at any time during admission | Baseline up to 7 Days |
| Number of subjects on mechanical ventilation | Number of subjects requiring mechanical ventilation greater than 48 hours. |
| Measure | Description | Time Frame |
|---|---|---|
| Facial amimia versus non-amimia expressions between the groups | Frequency of presence of facial amimia versus non-amimia expressions between the groups. | Changes from Baseline up to 7 Days |
| Dynamic activity versus static position |
Inclusion Criteria (ICU Patients):
Exclusion Criteria (ICU Patients):
Inclusion Criteria (Healthy Controls):
Exclusion Criteria (Healthy Controls):
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ICU Patients: Patients who been hospitalized in an intensive care unit and have risk factors to develop delirium or delirium has been suspected by their medical provider.
Healthy Controls: People who are healthy and sleep in their home environment.
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| Name | Affiliation | Role |
|---|---|---|
| Azra Bihorac, MD | University of Florida | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| UF Health | Gainesville | Florida | 32610 | United States |
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| ID | Term |
|---|---|
| D003693 | Delirium |
| D003221 | Confusion |
| D005149 | Facial Expression |
| ID | Term |
|---|---|
| D019954 | Neurobehavioral Manifestations |
| D009461 | Neurologic Manifestations |
| D009422 | Nervous System Diseases |
| D012816 | Signs and Symptoms |
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| ID | Term |
|---|---|
| D003952 | Diagnostic Imaging |
| ID | Term |
|---|---|
| D019937 | Diagnostic Techniques and Procedures |
| D003933 | Diagnosis |
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| Accelerometer | Device | 3 accelerometers (placed on upper arm, wrist and ankle) and 1 placed on wall as ambient light sensor |
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| Commercially available camera | Device | As part of facial recognition video system |
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| Internet Pod (iPod) | Device | Monitors noise levels in the room |
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| Cortisol Swab | Diagnostic Test | Cortisol level collected through self administered salivary swab |
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| greater than 48 hours |
Percentage of time spent moving versus static position
| Changes from Baseline up to 7 Days |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D009633 | Nonverbal Communication |
| D003142 | Communication |
| D001519 | Behavior |