<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02258386</url>
  </required_header>
  <id_info>
    <org_study_id>IRB #1409472204</org_study_id>
    <nct_id>NCT02258386</nct_id>
  </id_info>
  <brief_title>Assessment of Delirium in Hospitalized Patients</brief_title>
  <official_title>Objective Assessment of Delirium in Hospitalized Patients</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Arizona</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Arizona</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      The aim of the present study is to implement a novel body-worn sensor, the ZephyrTM BioModule&#xD;
      (the registered name for the wearable sensor device used in our study), for assessing&#xD;
      physical activity and physiological measures in a clinical setting together with other&#xD;
      clinical routine assessments. Our specific aim is to explore whether and how specific&#xD;
      physical activity pattern and physiological measures are associated with delirium in hospital&#xD;
      inpatient. Our ultimate goal is early detection and intervention of delirium, and better&#xD;
      management through monitoring of activity pattern and physiological information. The ZephyrTM&#xD;
      a U.S. FDA-approved wireless, ambulatory physiological monitoring device that consists of a&#xD;
      data logger and transmitter unit which is attached at the location of the 5th intercostal&#xD;
      space using a specifically designed patch (BioPatchTM) and standard ECG electrodes. The&#xD;
      ZephyrTM is designed for long-term measurement of a patient's physical activity and&#xD;
      physiological measures. By using the physical activity parameters and physiological measures,&#xD;
      a specific delirium risk profile will be computed for each patient. Finally, the association&#xD;
      of this delirium risk profile with CAM-ICU questionnaire as a gold standard will be assessed.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      After obtaining written informed consent and Protected Health Information (PHI) consent,&#xD;
      CAM-ICU (Confusion Assessment Method for the ICU) will be measured routinely by unit nurses&#xD;
      each shift. Results will be available in the medical record. We will then measure physical&#xD;
      activity and physiological measures (e.g. ECG, heart rate, respiration rate, and body&#xD;
      temperature) using an unobtrusive body worn sensor. This sensor will be attached to the 5th&#xD;
      intercostal space using a specifically designed patch (BioPatchTM) to allow quantification of&#xD;
      physical activity such as walking, standing, sitting, lying, as well as measurement of other&#xD;
      physiological parameters. These measurements will only be available to the research team and&#xD;
      will not be available to the nurses on the inpatient study unit. Medical history (from clinic&#xD;
      chart) and demographic information will be obtained, such as age, gender, weight, and height&#xD;
      as well as details (e.g. injuries, fall score and number of falls) which happened during&#xD;
      hospital stay. The research tests consist of one core measurements and one ancillary&#xD;
      measurements (as required) as listed below (Note - ancillary measurement may not be required&#xD;
      for everyone).&#xD;
&#xD;
      Core measurements Assessment of physical activity and physiological measures: Patients will&#xD;
      be asked to wear the Zephyr BioModule for a period of 24 hours to maximum stay in the&#xD;
      hospital. The Zephyr BioModule will be attached to the patients to the 5th intercostal space&#xD;
      using a specifically designed patch (BioPatchTM).&#xD;
&#xD;
      Ancillary Measurements Upper Extremity Test: A validated body worn sensors (LEGSys™,&#xD;
      Biosensics LLC) will be used to evaluate upper extremity kinematics (angular velocities).&#xD;
      This is a simple test where the patient flexes and extends their arm for 20 seconds on each&#xD;
      arm.&#xD;
&#xD;
      Analysis plan:&#xD;
&#xD;
      To predict the risk of delirium using physical activity and physiological data, each patient&#xD;
      participating in the study will be categorized as to presence of delirium based on CAM-ICU&#xD;
      questionnaire. Logistic regression analysis will be used to examine the relation between each&#xD;
      physical activity variable (e.g. lying time) and physiological measures (e.g. heart rate)&#xD;
      with delirium risk. Firstly, univariate logistic regression, using presence of delirium as&#xD;
      the dependent variable, will be employed to investigate the relationship of the test&#xD;
      variables. The Odd Ratios (OR) and coefficient of determination (R2) will be calculated for&#xD;
      each explanatory variable. Then multivariate logistic regression using stepwise-automated&#xD;
      methods will be performed to investigate the independent effects of the physical activity&#xD;
      variables and physiological measures in predicting delirium. Sensitivities, specificities,&#xD;
      positive and negative predictive values of different cut-off values will be calculated for&#xD;
      any non-categorical variable shown to have an independent effect on predicting delirium. A&#xD;
      two-sided P-value ≤0.05 will be considered to be statistically significant. Statistical&#xD;
      analysis will be performed using SPSS (Statistical Package for the Social Sciences)&#xD;
      statistics 22.0 (IBM, Armonk (name of town), NY (New York), USA).&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Not yet recruiting</last_known_status>
  <start_date>October 2014</start_date>
  <completion_date type="Anticipated">September 2017</completion_date>
  <primary_completion_date type="Anticipated">September 2015</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Objective Assessment of Delirium in Hospitalized Patients</measure>
    <time_frame>3 years</time_frame>
    <description>To identify biodata (physiological measurement) patterns indicative of the 3 subtypes of delirium (hypoactive, hyperactive and mixed). To build an algorithm sensitive and specific to the diagnosis of each of the three subtypes of delirium for future integration into a delirium monitoring system capable of objective delirium diagnosis, concentrating on those patterns indicative of early identification.</description>
  </primary_outcome>
  <enrollment type="Anticipated">200</enrollment>
  <condition>Delirium</condition>
  <eligibility>
    <study_pop>
      <textblock>
        Age 70 and older; hospitalized in ICU at high-risk of delirium.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria: At least one of the following:&#xD;
&#xD;
          -  Cognitive impairment,&#xD;
&#xD;
          -  UTI (urinary tract infection)&#xD;
&#xD;
          -  Pneumonia,&#xD;
&#xD;
          -  Status post hip fracture or trauma,&#xD;
&#xD;
             -&gt;5 medications,&#xD;
&#xD;
          -  Previous hospitalization in past 6 months&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Refusal to participate&#xD;
&#xD;
          -  Terminally ill&#xD;
&#xD;
          -  On ventilator&#xD;
&#xD;
          -  Delirium based on CAM-ICU&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>70 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Jane Mohler, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Arizona</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Jane Mohler, PhD</last_name>
    <phone>520-626-5807</phone>
    <email>jmohler@aging.arizona.edu</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Marilyn E. Gilbert, MS</last_name>
    <phone>520-626-5806</phone>
    <email>mgilbert@aging.arizona.edu</email>
  </overall_contact_backup>
  <reference>
    <citation>Cole MG. Delirium in elderly patients. Am J Geriatr Psychiatry. 2004 Jan-Feb;12(1):7-21.</citation>
    <PMID>14729554</PMID>
  </reference>
  <reference>
    <citation>Gleason OC. Delirium. Am Fam Physician. 2003 Mar 1;67(5):1027-34.</citation>
    <PMID>12643363</PMID>
  </reference>
  <reference>
    <citation>Foreman MD, Wakefield B, Culp K, Milisen K. Delirium in elderly patients: an overview of the state of the science. J Gerontol Nurs. 2001 Apr;27(4):12-20. doi: 10.3928/0098-9134-20010401-06.</citation>
    <PMID>11915152</PMID>
  </reference>
  <reference>
    <citation>Inouye SK. The dilemma of delirium: clinical and research controversies regarding diagnosis and evaluation of delirium in hospitalized elderly medical patients. Am J Med. 1994 Sep;97(3):278-88. doi: 10.1016/0002-9343(94)90011-6.</citation>
    <PMID>8092177</PMID>
  </reference>
  <reference>
    <citation>Francis J. Delirium in older patients. J Am Geriatr Soc. 1992 Aug;40(8):829-38. doi: 10.1111/j.1532-5415.1992.tb01859.x. No abstract available.</citation>
    <PMID>1634729</PMID>
  </reference>
  <reference>
    <citation>Albert MS, Levkoff SE, Reilly C, Liptzin B, Pilgrim D, Cleary PD, Evans D, Rowe JW. The delirium symptom interview: an interview for the detection of delirium symptoms in hospitalized patients. J Geriatr Psychiatry Neurol. 1992 Jan-Mar;5(1):14-21. doi: 10.1177/002383099200500103.</citation>
    <PMID>1571069</PMID>
  </reference>
  <reference>
    <citation>Trzepacz PT, Baker RW, Greenhouse J. A symptom rating scale for delirium. Psychiatry Res. 1988 Jan;23(1):89-97. doi: 10.1016/0165-1781(88)90037-6.</citation>
    <PMID>3363018</PMID>
  </reference>
  <reference>
    <citation>Leslie DL, Zhang Y, Holford TR, Bogardus ST, Leo-Summers LS, Inouye SK. Premature death associated with delirium at 1-year follow-up. Arch Intern Med. 2005 Jul 25;165(14):1657-62. doi: 10.1001/archinte.165.14.1657.</citation>
    <PMID>16043686</PMID>
  </reference>
  <reference>
    <citation>McCusker J, Cole M, Dendukuri N, Belzile E, Primeau F. Delirium in older medical inpatients and subsequent cognitive and functional status: a prospective study. CMAJ. 2001 Sep 4;165(5):575-83.</citation>
    <PMID>11563209</PMID>
  </reference>
  <reference>
    <citation>O'Keeffe S, Lavan J. The prognostic significance of delirium in older hospital patients. J Am Geriatr Soc. 1997 Feb;45(2):174-8. doi: 10.1111/j.1532-5415.1997.tb04503.x.</citation>
    <PMID>9033515</PMID>
  </reference>
  <verification_date>October 2014</verification_date>
  <study_first_submitted>October 2, 2014</study_first_submitted>
  <study_first_submitted_qc>October 2, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">October 7, 2014</study_first_posted>
  <last_update_submitted>October 2, 2014</last_update_submitted>
  <last_update_submitted_qc>October 2, 2014</last_update_submitted_qc>
  <last_update_posted type="Estimate">October 7, 2014</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Arizona</investigator_affiliation>
    <investigator_full_name>Jane Mohler</investigator_full_name>
    <investigator_title>Professor, University of Arizona Colleges of Medicine; Assoc. Director, Arizona Center on Aging; Assoc. Dir. iCAMP</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Delirium</mesh_term>
  </condition_browse>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02258386
org study id: IRB #1409472204
nct id: NCT02258386
lead sponsor: 
has dmc: No
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).
time perspective: Prospective
measure: Objective Assessment of Delirium in Hospitalized Patients
time frame: 3 years
description: To identify biodata (physiological measurement) patterns indicative of the 3 subtypes of delirium (hypoactive, hyperactive and mixed). To build an algorithm sensitive and specific to the diagnosis of each of the three subtypes of delirium for future integration into a delirium monitoring system capable of objective delirium diagnosis, concentrating on those patterns indicative of early identification.
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 70 Years
maximum age: N/A
healthy volunteers: No
last name: Jane Mohler, PhD
role: Principal Investigator
affiliation: University of Arizona
last name: Jane Mohler, PhD
phone: 520-626-5807
email: jmohler@aging.arizona.edu
last name: Marilyn E. Gilbert, MS
phone: 520-626-5806
email: mgilbert@aging.arizona.edu
citation: Cole MG. Delirium in elderly patients. Am J Geriatr Psychiatry. 2004 Jan-Feb;12(1):7-21.
PMID: 14729554
citation: Gleason OC. Delirium. Am Fam Physician. 2003 Mar 1;67(5):1027-34.
PMID: 12643363
citation: Foreman MD, Wakefield B, Culp K, Milisen K. Delirium in elderly patients: an overview of the state of the science. J Gerontol Nurs. 2001 Apr;27(4):12-20. doi: 10.3928/0098-9134-20010401-06.
PMID: 11915152
citation: Inouye SK. The dilemma of delirium: clinical and research controversies regarding diagnosis and evaluation of delirium in hospitalized elderly medical patients. Am J Med. 1994 Sep;97(3):278-88. doi: 10.1016/0002-9343(94)90011-6.
PMID: 8092177
citation: Francis J. Delirium in older patients. J Am Geriatr Soc. 1992 Aug;40(8):829-38. doi: 10.1111/j.1532-5415.1992.tb01859.x. No abstract available.
PMID: 1634729
citation: Albert MS, Levkoff SE, Reilly C, Liptzin B, Pilgrim D, Cleary PD, Evans D, Rowe JW. The delirium symptom interview: an interview for the detection of delirium symptoms in hospitalized patients. J Geriatr Psychiatry Neurol. 1992 Jan-Mar;5(1):14-21. doi: 10.1177/002383099200500103.
PMID: 1571069
citation: Trzepacz PT, Baker RW, Greenhouse J. A symptom rating scale for delirium. Psychiatry Res. 1988 Jan;23(1):89-97. doi: 10.1016/0165-1781(88)90037-6.
PMID: 3363018
citation: Leslie DL, Zhang Y, Holford TR, Bogardus ST, Leo-Summers LS, Inouye SK. Premature death associated with delirium at 1-year follow-up. Arch Intern Med. 2005 Jul 25;165(14):1657-62. doi: 10.1001/archinte.165.14.1657.
PMID: 16043686
citation: McCusker J, Cole M, Dendukuri N, Belzile E, Primeau F. Delirium in older medical inpatients and subsequent cognitive and functional status: a prospective study. CMAJ. 2001 Sep 4;165(5):575-83.
PMID: 11563209
citation: O'Keeffe S, Lavan J. The prognostic significance of delirium in older hospital patients. J Am Geriatr Soc. 1997 Feb;45(2):174-8. doi: 10.1111/j.1532-5415.1997.tb04503.x.
PMID: 9033515
responsible party type: Principal Investigator
investigator affiliation: University of Arizona
investigator full name: Jane Mohler
investigator title: Professor, University of Arizona Colleges of Medicine; Assoc. Director, Arizona Center on Aging; Assoc. Dir. iCAMP
mesh term: Delirium