<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/NCT02190682</url>
  </required_header>
  <id_info>
    <org_study_id>2062014</org_study_id>
    <nct_id>NCT02190682</nct_id>
  </id_info>
  <brief_title>Data Collection for Prediction of Postoperative Chronic Pain for a Software</brief_title>
  <official_title>Data Collection for Prediction of Postoperative Chronic Pain for Establishing a Software by Using Data Mining Technology</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Istanbul University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>The Scientific and Technological Research Council of Turkey</agency>
      <agency_class>Other</agency_class>
    </collaborator>
  </sponsors>
  <source>Istanbul University</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
  </oversight_info>
  <brief_summary>
    <textblock>
      Postoperative Persistent Pain (PPP) is reported with a high incidence in adults 11.5-47%.&#xD;
      This high incidence effects quality of life of patients causes social-economical problems and&#xD;
      arises medico-legal issues. This study will be undertaken for producing a database by the&#xD;
      evaluation of surgeries in 4 hospitals located in Istanbul. This database will be used in&#xD;
      establishing a software by using data mining technology in the prediction of PPP&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      All cases operated in 4 different hospitals in one month period will be included Exclusion&#xD;
      criteria: cases who could not be followed up to 2 months postoperatively by telephone call.&#xD;
&#xD;
      A questionnaire will be filled preoperatively for each case after obtaining informed case .&#xD;
      All cases will be anesthetized and pain therapy will be applied according to&#xD;
      anesthesiologist's own practice and pain relief will be evaluated and noted. All patients&#xD;
      will be telephoned postoperatively for the pain level at 15,30,45 and 60th day. All the&#xD;
      information will be uploaded to computer and a software will be prepared for prediction of&#xD;
      postoperative chronic pain.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">October 2014</start_date>
  <completion_date type="Actual">April 30, 2018</completion_date>
  <primary_completion_date type="Actual">April 2018</primary_completion_date>
  <study_type>Observational [Patient Registry]</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Only</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <target_duration>4 Months</target_duration>
  <primary_outcome>
    <measure>Incidence of postoperative chronic pain</measure>
    <time_frame>postoperative 3 months</time_frame>
    <description>Postoperative chronic pain is pain in the area of surgery lasting at least 2 months postoperatively regardless of infection, recurrence of disease and etc.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>preparation of software for the prediction of postoperative chronic pain</measure>
    <time_frame>8 months</time_frame>
    <description>the information from the questioners to the patients will be uploaded to an excel sheet and the IT group will prepare a software by using the data mining technology</description>
  </secondary_outcome>
  <enrollment type="Actual">733</enrollment>
  <condition>Chronic Postoperative Pain</condition>
  <eligibility>
    <study_pop>
      <textblock>
        all cases undergoing surgery&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  all cases operated in one month period&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  cases who cannot be followed for 2 months&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>N/A</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Pervin Bozkurt Sutaş, Prof. Dr</last_name>
    <role>Study Director</role>
    <affiliation>Istanbul University Cerrahpaşa Medical Faculty</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Istanbul University Cerrahpasa Medical Faculty</name>
      <address>
        <city>Istanbul</city>
        <zip>34303</zip>
        <country>Turkey</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Bezm-i Alem University</name>
      <address>
        <city>Istanbul</city>
        <country>Turkey</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Istanbul Research and Training Hospital</name>
      <address>
        <city>Istanbul</city>
        <country>Turkey</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Istanbul University Cardiology Institute</name>
      <address>
        <city>Istanbul</city>
        <country>Turkey</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Istanbul University Informatics Department</name>
      <address>
        <city>Istanbul</city>
        <country>Turkey</country>
      </address>
    </facility>
  </location>
  <location>
    <facility>
      <name>Tepecik Research and Training Hospital</name>
      <address>
        <city>Izmir</city>
        <country>Turkey</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>Turkey</country>
  </location_countries>
  <reference>
    <citation>Sutaş Bozkurt, A. P., Özen, Z., Kartal, E., Emre, İ. E., Selçukcan Erol, Ç., Koçoğlu, F. Ö., Güngör, G., Güneyli, H. C., Başaranoğlu, G., Ünlüsoy, E. Ö., Uğur, H. Ö., Buluç Bulğen, S., Çolakoğlu, N., Sayılgan, C., Pekel, A. F., Pişmişoğlu, H., Salihoğlu, Z., Yüceyar, L., Karaca, S., … Bakan, N. (2018). Analysis of the incidence and predictive factors of chronic postoperative pain in adult population. The Journal of Tepecik Education and Research, 28(2), 89-94. https://doi.org/10.5222/terh.2018.089</citation>
  </reference>
  <verification_date>January 2020</verification_date>
  <study_first_submitted>July 12, 2014</study_first_submitted>
  <study_first_submitted_qc>July 14, 2014</study_first_submitted_qc>
  <study_first_posted type="Estimate">July 15, 2014</study_first_posted>
  <last_update_submitted>January 23, 2020</last_update_submitted>
  <last_update_submitted_qc>January 23, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">January 27, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Istanbul University</investigator_affiliation>
    <investigator_full_name>Prof. Dr. A. Pervin SUTAS BOZKURT</investigator_full_name>
    <investigator_title>Professor Dr</investigator_title>
  </responsible_party>
  <keyword>postoperative</keyword>
  <keyword>chronic</keyword>
  <keyword>pain</keyword>
  <keyword>software</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Pain, Postoperative</mesh_term>
    <mesh_term>Chronic Pain</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>Yes</sharing_ipd>
    <ipd_description>Patient questioner</ipd_description>
    <ipd_info_type>Study Protocol</ipd_info_type>
    <ipd_info_type>Statistical Analysis Plan (SAP)</ipd_info_type>
    <ipd_info_type>Informed Consent Form (ICF)</ipd_info_type>
    <ipd_info_type>Clinical Study Report (CSR)</ipd_info_type>
    <ipd_time_frame>Jan 2020- Jan 2022</ipd_time_frame>
    <ipd_access_criteria>when it is published by a journal</ipd_access_criteria>
  </patient_data>
  <!-- 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/NCT02190682
org study id: 2062014
nct id: NCT02190682
lead sponsor: 
collaborator: 
has dmc: Yes
Postoperative Persistent Pain (PPP) is reported with a high incidence in adults 11.5-47%.
      This high incidence effects quality of life of patients causes social-economical problems and
      arises medico-legal issues. This study will be undertaken for producing a database by the
      evaluation of surgeries in 4 hospitals located in Istanbul. This database will be used in
      establishing a software by using data mining technology in the prediction of PPP
All cases operated in 4 different hospitals in one month period will be included Exclusion
      criteria: cases who could not be followed up to 2 months postoperatively by telephone call.

      A questionnaire will be filled preoperatively for each case after obtaining informed case .
      All cases will be anesthetized and pain therapy will be applied according to
      anesthesiologist's own practice and pain relief will be evaluated and noted. All patients
      will be telephoned postoperatively for the pain level at 15,30,45 and 60th day. All the
      information will be uploaded to computer and a software will be prepared for prediction of
      postoperative chronic pain.
observational model: Case-Only
time perspective: Prospective
measure: Incidence of postoperative chronic pain
time frame: postoperative 3 months
description: Postoperative chronic pain is pain in the area of surgery lasting at least 2 months postoperatively regardless of infection, recurrence of disease and etc.
measure: preparation of software for the prediction of postoperative chronic pain
time frame: 8 months
description: the information from the questioners to the patients will be uploaded to an excel sheet and the IT group will prepare a software by using the data mining technology
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: N/A
maximum age: N/A
healthy volunteers: No
last name: Pervin Bozkurt Sutaş, Prof. Dr
role: Study Director
affiliation: Istanbul University Cerrahpaşa Medical Faculty
facility: 
facility: 
facility: 
facility: 
facility: 
facility: 
country: Turkey
citation: Sutaş Bozkurt, A. P., Özen, Z., Kartal, E., Emre, İ. E., Selçukcan Erol, Ç., Koçoğlu, F. Ö., Güngör, G., Güneyli, H. C., Başaranoğlu, G., Ünlüsoy, E. Ö., Uğur, H. Ö., Buluç Bulğen, S., Çolakoğlu, N., Sayılgan, C., Pekel, A. F., Pişmişoğlu, H., Salihoğlu, Z., Yüceyar, L., Karaca, S., … Bakan, N. (2018). Analysis of the incidence and predictive factors of chronic postoperative pain in adult population. The Journal of Tepecik Education and Research, 28(2), 89-94. https://doi.org/10.5222/terh.2018.089
responsible party type: Principal Investigator
investigator affiliation: Istanbul University
investigator full name: Prof. Dr. A. Pervin SUTAS BOZKURT
investigator title: Professor Dr
mesh term: Pain, Postoperative
mesh term: Chronic Pain
sharing ipd: Yes
ipd description: Patient questioner
ipd info type: Study Protocol
ipd info type: Statistical Analysis Plan (SAP)
ipd info type: Informed Consent Form (ICF)
ipd info type: Clinical Study Report (CSR)
ipd time frame: Jan 2020- Jan 2022
ipd access criteria: when it is published by a journal