<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/NCT03794674</url>
  </required_header>
  <id_info>
    <org_study_id>MPIRECVALID</org_study_id>
    <nct_id>NCT03794674</nct_id>
  </id_info>
  <brief_title>Validation of a Record-based Frailty Assessment According to the Multidimensional Prognostic Index</brief_title>
  <official_title>Validation of a Record-based Frailty Assessment According to the Multidimensional Prognostic Index</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Aarhus</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>University of Aarhus</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      Background Various phenotype and cumulative frailty assessment tools have been developed and&#xD;
      compared in research. For use in an in-hospital setting, a cumulative and graded frailty&#xD;
      assessment method is preferred in order to identify subgroups of patients at risk of adverse&#xD;
      events during discharge and transition to primary care. Comprehensive Geriatric Assessment&#xD;
      (CGA) is the gold standard to assess frailty. Most medical wards have limited access to&#xD;
      specialized geriatric team support capable of performing CGA. Thus in these wards there is a&#xD;
      need for a CGA based instrument to identify the frail patients and to quantify the level of&#xD;
      frailty. The Multidimensional Prognostic Index (MPI) is based on CGA and is a comprehensive&#xD;
      cumulative deficit frailty assessment tool validated in a Danish geriatric department. MPI is&#xD;
      fully applicable in the everyday clinical work and supplies useful information to clinicians.&#xD;
      It can predict readmission and death, and it is well-suited to assess the degree of frailty.&#xD;
      Enabling identification of patients at risk of adverse events facilitates targeting of the&#xD;
      interventions in order to improve patient outcomes. The MPI is a bedside assessment. However,&#xD;
      in observational record-based research the patient is not accessible for the researcher. To&#xD;
      assess and identify hospitalized frail patients retrospectively for clinical research, a&#xD;
      valid record-based frailty assessment method is needed. The aim of this study is to compare&#xD;
      the accuracy of a record-based MPI assessment with a bedside performed MPI assessment in&#xD;
      order to use the record-based MPI when access to bedside MPI is impossible.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">December 4, 2018</start_date>
  <completion_date type="Actual">February 22, 2019</completion_date>
  <primary_completion_date type="Actual">February 21, 2019</primary_completion_date>
  <study_type>Observational [Patient Registry]</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Other</time_perspective>
  </study_design_info>
  <target_duration>1 Day</target_duration>
  <primary_outcome>
    <measure>Sumscore</measure>
    <time_frame>1 day</time_frame>
    <description>The relative difference between the two measurements' sumscores calculated as an Intraclass Correlation Coefficient (ICC)</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Actual">92</enrollment>
  <condition>Frail Elderly Syndrome</condition>
  <arm_group>
    <arm_group_label>MPI test group</arm_group_label>
    <description>50 eligible patients. Frailty level independently assessed by two reviewers based on the medical records and assessed by one research assistant based on bedside testing.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>No intervention.</intervention_name>
    <description>No intervention, since this is a validation study</description>
    <arm_group_label>MPI test group</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        The study group comprises medical patients acutely admitted to the Department of Cardiology&#xD;
        and the Department of Infectious Diseases, Aarhus University Hospital.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Acutely admitted to one of the two medical departments listed below&#xD;
&#xD;
          -  Aged 75 years or older&#xD;
&#xD;
          -  Living within the municipality of Aarhus&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Included in any other kind of follow-up schemes&#xD;
&#xD;
          -  Already included in this study&#xD;
&#xD;
          -  Declared terminally ill or undergoing palliative care at admission&#xD;
&#xD;
          -  Admitted from one specific temporary nursing home with geriatric medical assistance&#xD;
             (Vikærgården)&#xD;
&#xD;
          -  Discharge or transfer to another department, including hospice&#xD;
&#xD;
          -  The patient does not want to participate in the MPI-screening process&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>75 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Troels Hansen, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Aarhus University Hospital and Aarhus University</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Aarhus University</name>
      <address>
        <city>Aarhus</city>
        <country>Denmark</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Denmark</country>
  </location_countries>
  <reference>
    <citation>Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: A review. Eur J Intern Med. 2016 Jun;31:3-10. doi: 10.1016/j.ejim.2016.03.007. Epub 2016 Mar 31.</citation>
    <PMID>27039014</PMID>
  </reference>
  <reference>
    <citation>Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013 Mar 2;381(9868):752-62. doi: 10.1016/S0140-6736(12)62167-9. Epub 2013 Feb 8. Erratum In: Lancet. 2013 Oct 19;382(9901):1328.</citation>
    <PMID>23395245</PMID>
  </reference>
  <reference>
    <citation>Volpato S, Bazzano S, Fontana A, Ferrucci L, Pilotto A; MPI-TriVeneto Study Group. Multidimensional Prognostic Index predicts mortality and length of stay during hospitalization in the older patients: a multicenter prospective study. J Gerontol A Biol Sci Med Sci. 2015 Mar;70(3):325-31. doi: 10.1093/gerona/glu167. Epub 2014 Sep 9.</citation>
    <PMID>25209253</PMID>
  </reference>
  <reference>
    <citation>Pilotto A, Ferrucci L, Franceschi M, D'Ambrosio LP, Scarcelli C, Cascavilla L, Paris F, Placentino G, Seripa D, Dallapiccola B, Leandro G. Development and validation of a multidimensional prognostic index for one-year mortality from comprehensive geriatric assessment in hospitalized older patients. Rejuvenation Res. 2008 Feb;11(1):151-61. doi: 10.1089/rej.2007.0569.</citation>
    <PMID>18173367</PMID>
  </reference>
  <reference>
    <citation>Gregersen M, Hansen TK, Jørgensen BB, Damsgaard EM. Validation of a modified Multidimensional Prognostic Index obtained at discharge in older Danish geriatric patients to predict acute readmission and mortality. 2018 Unpublished data.</citation>
  </reference>
  <reference>
    <citation>Warnier RM, van Rossum E, van Velthuijsen E, Mulder WJ, Schols JM, Kempen GI. Validity, Reliability and Feasibility of Tools to Identify Frail Older Patients in Inpatient Hospital Care: A Systematic Review. J Nutr Health Aging. 2016 Feb;20(2):218-30. doi: 10.1007/s12603-015-0567-z.</citation>
    <PMID>26812520</PMID>
  </reference>
  <reference>
    <citation>Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000 Jul;30(1):1-15. doi: 10.2165/00007256-200030010-00001.</citation>
    <PMID>10907753</PMID>
  </reference>
  <reference>
    <citation>de Vet HC, Terwee CB, Knol DL, Bouter LM. When to use agreement versus reliability measures. J Clin Epidemiol. 2006 Oct;59(10):1033-9. doi: 10.1016/j.jclinepi.2005.10.015. Epub 2006 Aug 10.</citation>
    <PMID>16980142</PMID>
  </reference>
  <reference>
    <citation>Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, Bouter LM, de Vet HC. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007 Jan;60(1):34-42. doi: 10.1016/j.jclinepi.2006.03.012. Epub 2006 Aug 24.</citation>
    <PMID>17161752</PMID>
  </reference>
  <verification_date>December 2018</verification_date>
  <study_first_submitted>December 21, 2018</study_first_submitted>
  <study_first_submitted_qc>January 2, 2019</study_first_submitted_qc>
  <study_first_posted type="Actual">January 7, 2019</study_first_posted>
  <last_update_submitted>October 7, 2019</last_update_submitted>
  <last_update_submitted_qc>October 7, 2019</last_update_submitted_qc>
  <last_update_posted type="Actual">October 8, 2019</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <keyword>Multidimensional Prognostic Index</keyword>
  <keyword>Frailty</keyword>
  <keyword>Geriatric</keyword>
  <keyword>Elderly</keyword>
  <keyword>Aged</keyword>
  <keyword>+75</keyword>
  <keyword>Comprehensive Geriatric Assessment</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Frailty</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Undecided</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>January 30, 2019</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/74/NCT03794674/Prot_SAP_001.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- 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/NCT03794674
org study id: MPIRECVALID
nct id: NCT03794674
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Background Various phenotype and cumulative frailty assessment tools have been developed and
      compared in research. For use in an in-hospital setting, a cumulative and graded frailty
      assessment method is preferred in order to identify subgroups of patients at risk of adverse
      events during discharge and transition to primary care. Comprehensive Geriatric Assessment
      (CGA) is the gold standard to assess frailty. Most medical wards have limited access to
      specialized geriatric team support capable of performing CGA. Thus in these wards there is a
      need for a CGA based instrument to identify the frail patients and to quantify the level of
      frailty. The Multidimensional Prognostic Index (MPI) is based on CGA and is a comprehensive
      cumulative deficit frailty assessment tool validated in a Danish geriatric department. MPI is
      fully applicable in the everyday clinical work and supplies useful information to clinicians.
      It can predict readmission and death, and it is well-suited to assess the degree of frailty.
      Enabling identification of patients at risk of adverse events facilitates targeting of the
      interventions in order to improve patient outcomes. The MPI is a bedside assessment. However,
      in observational record-based research the patient is not accessible for the researcher. To
      assess and identify hospitalized frail patients retrospectively for clinical research, a
      valid record-based frailty assessment method is needed. The aim of this study is to compare
      the accuracy of a record-based MPI assessment with a bedside performed MPI assessment in
      order to use the record-based MPI when access to bedside MPI is impossible.
observational model: Cohort
time perspective: Other
measure: Sumscore
time frame: 1 day
description: The relative difference between the two measurements' sumscores calculated as an Intraclass Correlation Coefficient (ICC)
arm group label: MPI test group
description: 50 eligible patients. Frailty level independently assessed by two reviewers based on the medical records and assessed by one research assistant based on bedside testing.
intervention type: Other
intervention name: No intervention.
description: No intervention, since this is a validation study
arm group label: MPI test group
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 75 Years
maximum age: N/A
healthy volunteers: No
last name: Troels Hansen, MD
role: Principal Investigator
affiliation: Aarhus University Hospital and Aarhus University
facility: 
country: Denmark
citation: Dent E, Kowal P, Hoogendijk EO. Frailty measurement in research and clinical practice: A review. Eur J Intern Med. 2016 Jun;31:3-10. doi: 10.1016/j.ejim.2016.03.007. Epub 2016 Mar 31.
PMID: 27039014
citation: Clegg A, Young J, Iliffe S, Rikkert MO, Rockwood K. Frailty in elderly people. Lancet. 2013 Mar 2;381(9868):752-62. doi: 10.1016/S0140-6736(12)62167-9. Epub 2013 Feb 8. Erratum In: Lancet. 2013 Oct 19;382(9901):1328.
PMID: 23395245
citation: Volpato S, Bazzano S, Fontana A, Ferrucci L, Pilotto A; MPI-TriVeneto Study Group. Multidimensional Prognostic Index predicts mortality and length of stay during hospitalization in the older patients: a multicenter prospective study. J Gerontol A Biol Sci Med Sci. 2015 Mar;70(3):325-31. doi: 10.1093/gerona/glu167. Epub 2014 Sep 9.
PMID: 25209253
citation: Pilotto A, Ferrucci L, Franceschi M, D'Ambrosio LP, Scarcelli C, Cascavilla L, Paris F, Placentino G, Seripa D, Dallapiccola B, Leandro G. Development and validation of a multidimensional prognostic index for one-year mortality from comprehensive geriatric assessment in hospitalized older patients. Rejuvenation Res. 2008 Feb;11(1):151-61. doi: 10.1089/rej.2007.0569.
PMID: 18173367
citation: Gregersen M, Hansen TK, Jørgensen BB, Damsgaard EM. Validation of a modified Multidimensional Prognostic Index obtained at discharge in older Danish geriatric patients to predict acute readmission and mortality. 2018 Unpublished data.
citation: Warnier RM, van Rossum E, van Velthuijsen E, Mulder WJ, Schols JM, Kempen GI. Validity, Reliability and Feasibility of Tools to Identify Frail Older Patients in Inpatient Hospital Care: A Systematic Review. J Nutr Health Aging. 2016 Feb;20(2):218-30. doi: 10.1007/s12603-015-0567-z.
PMID: 26812520
citation: Hopkins WG. Measures of reliability in sports medicine and science. Sports Med. 2000 Jul;30(1):1-15. doi: 10.2165/00007256-200030010-00001.
PMID: 10907753
citation: de Vet HC, Terwee CB, Knol DL, Bouter LM. When to use agreement versus reliability measures. J Clin Epidemiol. 2006 Oct;59(10):1033-9. doi: 10.1016/j.jclinepi.2005.10.015. Epub 2006 Aug 10.
PMID: 16980142
citation: Terwee CB, Bot SD, de Boer MR, van der Windt DA, Knol DL, Dekker J, Bouter LM, de Vet HC. Quality criteria were proposed for measurement properties of health status questionnaires. J Clin Epidemiol. 2007 Jan;60(1):34-42. doi: 10.1016/j.jclinepi.2006.03.012. Epub 2006 Aug 24.
PMID: 17161752
responsible party type: Sponsor
mesh term: Frailty
sharing ipd: Undecided
provided document: 