Trial document




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  DRKS00014857

Trial Description

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Title

Predicting the rehabilitation outcome after trauma based on the ICF - icfPROreha - prediction of work ability and quality of life in persons with musculoskeletal injuries

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Trial Acronym

icfPROreha

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URL of the Trial

http://ihrs.ibe.med.uni-muenchen.de/biopsychosocial/laufende-projekte/icf_pro_reha/index.html

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Brief Summary in Lay Language

Following traumatic injuries, people often suffer from limitations in activities of daily living, restrictions in work and employment and quality of life. To improve rehabilitation for patients with traumatic musculoskeletal injuries, the project icfPROreha was initiated. With this study, we would like to answer the following question: Which factors are important to predict work ability, time off work and quality of life in patients with severe musculoskeletal injuries? To answer this question, we collect and analyse questionnaire data in 11 inpatient rehabilitation clinics in Germany: sociodemographic data, data on injury, health status, living conditions, work ability, time off work and quality of life. Data are collected at admission to and discharge from the clinic as well as 12, 26, 52 and 78 weeks after discharge. No additional examinations or treatments are carried out.

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Brief Summary in Scientific Language

Aim of this study is to identify determinants (aspects of functioning as well as contextual factors) of a successful rehabilitation – especially return to work, time off work and quality of life - in persons with severe musculoskeletal injuries after inpatient rehabilitation. Besides, an outcome prognosis and guidelines including recommendations how to cope with the identified determinants in rehabilitation management will be established to considerably shorten time off work and ensure return to work. Aspects of functioning and contextual factors, which have to be considered to assess rehabilitation outcome, have already been determined in expert surveys, systematic literature reviews and consensus conferences. Data of 1.200 patients will be collected in eleven inpatient rehabilitation centres using the outcome measures determined beforehand. Clinically gathered data will be complemented by data (e.g. time off work) from insurance providers. Based on these data, predictive modelling will be applied to predict rehabilitation outcome such as time off work and quality of life. These models allow for establishing an outcome prognosis at admission to inpatient rehabilitation that is built on functioning status and contextual factors.

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Organizational Data

  •   DRKS00014857
  •   2018/07/04
  •   [---]*
  •   yes
  •   Approved
  •   18-329, Ethik-Kommission der Medizinischen Fakultät der Ludwig-Maximilians-Universität München
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Secondary IDs

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Health Condition or Problem studied

  •   Musculoskeletal injuries
  •   S00-T98 -  Injury, poisoning and certain other consequences of external causes
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Interventions/Observational Groups

  •   Patients with severe musculoskeletal injuries are surveyed at admission to and discharge from rehabilitation clinic and over a period of 78 weeks after discharge. No intervention is conducted.
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Characteristics

  •   Non-interventional
  •   Observational study
  •   Single arm study
  •   Open (masking not used)
  •   [---]*
  •   Uncontrolled/Single arm
  •   Prognosis
  •   Single (group)
  •   N/A
  •   N/A
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Primary Outcome

Work ability 78 weeks (t6) after discharge from inpatient rehabilitation treatment; assessed with telephone interviews and data of insurance companies

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Secondary Outcome

Time off work in a 78-weeks time period after discharge form inpatient rehabilitation treatment; assessed with telephone interviews and data of insurance companies;

Quality of life after discharge; assessed with the EQ-5D

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Countries of Recruitment

  •   Germany
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Locations of Recruitment

  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • Medical Center 
  • University Medical Center 
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Recruitment

  •   Actual
  •   2018/08/28
  •   1200
  •   Multicenter trial
  •   National
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Inclusion Criteria

  •   Both, male and female
  •   18   Years
  •   65   Years
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Additional Inclusion Criteria

(1) Diagnosis in accordance with the Verletzungsartenverzeichnis (VAV) der Deutschen Gesetzlichen Unfallversicherung (DGUV) und der Sozialversicherung für Landwirtschaft, Forsten und Gartenbau (SVLFG), combination possible, (2) admission to first inpatient rehabilitationa following the injury/accident, (3) time frame between injury/accident and admission to inpatient rehabilitation not longer than 16 weeks; (4) informed consent provided

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Exclusion Criteria

Persons with injuries of major nerves including injuries of the spine with neurologic symptoms and open or covered moderately severe or severe traumatic brain injuries

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Addresses

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    • Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie – IBE, Lehrstuhl für Public Health und Versorgungsforschung, Ludwig-Maximilians-Universität (LMU) München
    • Ms.  Dr.  Michaela  Coenen 
    • Marchioninistr. 17
    • 81377  München
    • Germany
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    • Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie – IBE, Lehrstuhl für Public Health und Versorgungsforschung, Ludwig-Maximilians-Universität (LMU) München
    • Ms.  Dr.  Michaela  Coenen 
    • Marchioninistr. 17
    • 81377  München
    • Germany
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    • Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie – IBE, Lehrstuhl für Public Health und Versorgungsforschung, Ludwig-Maximilians-Universität (LMU) München
    • Ms.  Dr.  Michaela  Coenen 
    • Marchioninistr. 17
    • 81377  München
    • Germany
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Sources of Monetary or Material Support

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    • Deutsche Gesetzliche Unfallversicherung (DGUV)
    • 10117  Berlin
    • Germany
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Status

  •   Recruiting ongoing
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Trial Publications, Results and other Documents

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* This entry means the parameter is not applicable or has not been set.