<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/NCT03236272</url>
  </required_header>
  <id_info>
    <org_study_id>TMMUHMD76</org_study_id>
    <nct_id>NCT03236272</nct_id>
  </id_info>
  <brief_title>Establishment of a Biomarkers-based Early Warning System of Acute Respiratory Distress Syndrome (ARDS)</brief_title>
  <official_title>Establishment of a Biomarkers-based Early Warning System of Acute Respiratory Distress Syndrome (ARDS)</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Mingdong Hu</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Third Military Medical University</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>
      The aim of the investigators 'study is to investigate the relationship between the biomarkers&#xD;
      (e.g. protein markers, genetic polymorphisms and epigenetic markers) and the onset of ARDS.&#xD;
      In this study, the participants were divided into case group (with ARDS) and control group&#xD;
      (without ARDS), based on a nested case-control study method. During the diagnosis and&#xD;
      treatment, the clinical data of subjects are collected at the given time point. And the&#xD;
      clinical data are extracted from plasma, blood and bronchoalveolar lavage fluid of&#xD;
      participants. These data will be analyzed based on statistical methods. In the end ,the&#xD;
      investigators can build a multi index early warning model based on the biomarkers,which is&#xD;
      meaningful for the early diagnosis of the patient with high-risk for ARDS and provide&#xD;
      evidence for the early treatment.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The investigators studied patients at high risk of acute respiratory distress syndrome (ARDS)&#xD;
      and ARDS patients. The patients with ARDS were the case group, and the patients without ARDS&#xD;
      were the control group .Sample size estimate :set alpha =0.05,1- beta =0.8, estimated cases&#xD;
      exposure rate was 50%, the control group estimated exposure rate was 35%, according to a&#xD;
      case-control study of sample size estimation formula for sample size calculation, and&#xD;
      considering the loss rate is 10%, the sample size for each group of 188 cases, two groups of&#xD;
      376 cases. The plasma, blood and bronchoalveolar lavage fluid will be collected during the&#xD;
      diagnosis and treatment，to study biomarkers related to the onset of ARDS, such as protein&#xD;
      markers,genetic polymorphisms and epigenetic markers.The observation data of two groups will&#xD;
      be compared .The clinical data are collected at the given time point. The stepwise regression&#xD;
      (forward-conditional) will be used for establishing a multivariate unconditional logistic&#xD;
      regression model that will contribute to screened the main risk factor and protective factors&#xD;
      that affect the ARDS. And these factor will help to established the early warning model and&#xD;
      the risk function of ARDS in high-risk patients, which will contribute to predict the risk of&#xD;
      ARDS in high-risk patients.All information about the subjects is strictly confidential, and&#xD;
      the results of the study may be reported at medical conferences and published in scientific&#xD;
      journals, but any individual who can identify subjects will not be able to use.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">September 15, 2017</start_date>
  <completion_date type="Anticipated">December 31, 2020</completion_date>
  <primary_completion_date type="Anticipated">December 31, 2020</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Case-Control</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>the change of protein biomarkers expression</measure>
    <time_frame>Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.</time_frame>
    <description>The protein biomarkers include surfactant protein(SP-D)，Clara Cell Protein 16(CC-16)，Angiopoietin-2(Ang-2)，von Willebrand factor(vWF)，Lipopolysaccharide-Binding Protein(LBP) and plasminogen activator inhibitor-1(PAI-1).The subjects will be observed for the content and expression changes of the items mentioned above at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point,day14 will be added.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>the change of microRNA-126(miR-126) expression</measure>
    <time_frame>Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.</time_frame>
    <description>The subjects will be observed for the content and expression changes of the miR-126 at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point,day14 will be added.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>the change of microRNA-146a(miR-146a) expression</measure>
    <time_frame>Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.</time_frame>
    <description>The subjects will be observed for the content and expression changes of the miR-146a at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point,day14 will be added.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Detection of methylation of occludin (OCLN) gene</measure>
    <time_frame>Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.</time_frame>
    <description>Detecting the OCLN gene methylation is based on microarray methylation pattern analysis.The subjects will be detected OCLN gene methylation at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point day14 will be added.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Analysis of gene polymorphism</measure>
    <time_frame>Day 0</time_frame>
    <description>Detecting the genetic polymorphisms,it include mannose binding lectin-2 gene (The Single Nucleotide Polymorphism database (dbSNP) identification number (ID): rs1800450) and lipopolysaccharide-binding peptide (LBP) gene（The Single Nucleotide Polymorphism database (dbSNP) ID: rs2232618）</description>
  </primary_outcome>
  <number_of_groups>2</number_of_groups>
  <enrollment type="Anticipated">376</enrollment>
  <condition>Respiratory Distress Syndrome, Adult</condition>
  <arm_group>
    <arm_group_label>case group</arm_group_label>
    <description>patients with ARDS</description>
  </arm_group>
  <arm_group>
    <arm_group_label>control group</arm_group_label>
    <description>patients Without ARDS</description>
  </arm_group>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      whole blood ,plasma,bronchoalveolar lavage fluid&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        The subjects were selected from the Department of respiration, Xinqiao Hospital of&#xD;
        Chongqing city&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. High-risk cases ARDS inclusion criteria:&#xD;
&#xD;
               -  Acute onset (within 1 weeks)&#xD;
&#xD;
               -  Pneumonia,Aspiration,Sepsis,Acute pancreatitis,Shock,High-risk trauma and other&#xD;
                  unexpected severe diseases.&#xD;
&#xD;
               -  Pao2/Fio2&gt;300mmhg&#xD;
&#xD;
               -  18 to 80 years old&#xD;
&#xD;
               -  The subjects agreed to sign the informed consent&#xD;
&#xD;
          2. ARDS Inclusion criteria:&#xD;
&#xD;
               -  Acute onset (within 1 weeks)&#xD;
&#xD;
               -  Pneumonia,Aspiration,Sepsis,Acute pancreatitis,Shock,High-risk trauma and other&#xD;
                  unexpected severe diseases.&#xD;
&#xD;
               -  Pao2/Fio2&lt;300mmhg&#xD;
&#xD;
               -  18 to 80 years old&#xD;
&#xD;
               -  The subjects agreed to sign the informed consent&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  patients who developed ARDS before initial evaluation or blood collection&#xD;
&#xD;
          -  patients who were rehospitalized&#xD;
&#xD;
          -  the hospital stay was shorter than 7 days, and it was unfeasible to determine the&#xD;
             clinical outcome&#xD;
&#xD;
          -  patients who died within 6h of admission&#xD;
&#xD;
          -  patients had a history of chronic interstitial lung disease&#xD;
&#xD;
          -  patients with an age of less than 18 years old&#xD;
&#xD;
          -  Patients were immunodeficiency (eg, eukaemia) or treated with cytotoxic drugs&#xD;
&#xD;
          -  patients who were pregnant&#xD;
&#xD;
          -  patients who were refused to join.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>80 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_contact>
    <last_name>Hu Mingdong, MD</last_name>
    <phone>13500362524</phone>
    <email>huhanshandd@163.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Wang dan</last_name>
    <phone>18581290211</phone>
    <email>wada211@163.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Center of Respiratory and Critical Care Medicine，Department Of Gerontology and Secret Service Medicine, Xinqiao Hospital, Third Military Medical University</name>
      <address>
        <city>Chongqing</city>
        <country>China</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>HU MINGDONG, MD</last_name>
    </contact>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>March 2020</verification_date>
  <study_first_submitted>July 24, 2017</study_first_submitted>
  <study_first_submitted_qc>July 27, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">August 1, 2017</study_first_posted>
  <last_update_submitted>March 23, 2020</last_update_submitted>
  <last_update_submitted_qc>March 23, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">March 25, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor-Investigator</responsible_party_type>
    <investigator_affiliation>Third Military Medical University</investigator_affiliation>
    <investigator_full_name>Mingdong Hu</investigator_full_name>
    <investigator_title>associate chief physician</investigator_title>
  </responsible_party>
  <keyword>Biomarkers</keyword>
  <keyword>High-Throughput Screening Assays</keyword>
  <keyword>Respiratory Distress Syndrome, Adult</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Respiratory Distress Syndrome</mesh_term>
    <mesh_term>Respiratory Distress Syndrome, Newborn</mesh_term>
    <mesh_term>Acute Lung Injury</mesh_term>
    <mesh_term>Syndrome</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/NCT03236272
org study id: TMMUHMD76
nct id: NCT03236272
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
The aim of the investigators 'study is to investigate the relationship between the biomarkers
      (e.g. protein markers, genetic polymorphisms and epigenetic markers) and the onset of ARDS.
      In this study, the participants were divided into case group (with ARDS) and control group
      (without ARDS), based on a nested case-control study method. During the diagnosis and
      treatment, the clinical data of subjects are collected at the given time point. And the
      clinical data are extracted from plasma, blood and bronchoalveolar lavage fluid of
      participants. These data will be analyzed based on statistical methods. In the end ,the
      investigators can build a multi index early warning model based on the biomarkers,which is
      meaningful for the early diagnosis of the patient with high-risk for ARDS and provide
      evidence for the early treatment.
The investigators studied patients at high risk of acute respiratory distress syndrome (ARDS)
      and ARDS patients. The patients with ARDS were the case group, and the patients without ARDS
      were the control group .Sample size estimate :set alpha =0.05,1- beta =0.8, estimated cases
      exposure rate was 50%, the control group estimated exposure rate was 35%, according to a
      case-control study of sample size estimation formula for sample size calculation, and
      considering the loss rate is 10%, the sample size for each group of 188 cases, two groups of
      376 cases. The plasma, blood and bronchoalveolar lavage fluid will be collected during the
      diagnosis and treatment，to study biomarkers related to the onset of ARDS, such as protein
      markers,genetic polymorphisms and epigenetic markers.The observation data of two groups will
      be compared .The clinical data are collected at the given time point. The stepwise regression
      (forward-conditional) will be used for establishing a multivariate unconditional logistic
      regression model that will contribute to screened the main risk factor and protective factors
      that affect the ARDS. And these factor will help to established the early warning model and
      the risk function of ARDS in high-risk patients, which will contribute to predict the risk of
      ARDS in high-risk patients.All information about the subjects is strictly confidential, and
      the results of the study may be reported at medical conferences and published in scientific
      journals, but any individual who can identify subjects will not be able to use.
observational model: Case-Control
time perspective: Prospective
measure: the change of protein biomarkers expression
time frame: Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.
description: The protein biomarkers include surfactant protein(SP-D)，Clara Cell Protein 16(CC-16)，Angiopoietin-2(Ang-2)，von Willebrand factor(vWF)，Lipopolysaccharide-Binding Protein(LBP) and plasminogen activator inhibitor-1(PAI-1).The subjects will be observed for the content and expression changes of the items mentioned above at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point,day14 will be added.
measure: the change of microRNA-126(miR-126) expression
time frame: Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.
description: The subjects will be observed for the content and expression changes of the miR-126 at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point,day14 will be added.
measure: the change of microRNA-146a(miR-146a) expression
time frame: Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.
description: The subjects will be observed for the content and expression changes of the miR-146a at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point,day14 will be added.
measure: Detection of methylation of occludin (OCLN) gene
time frame: Day 0,Day 1,Day 2,Day 3,Day 4,Day 7 and Day 14 post-enrollment.
description: Detecting the OCLN gene methylation is based on microarray methylation pattern analysis.The subjects will be detected OCLN gene methylation at day0,1,2,3,4,7. Among participants, for case group patients ,the observation time point day14 will be added.
measure: Analysis of gene polymorphism
time frame: Day 0
description: Detecting the genetic polymorphisms,it include mannose binding lectin-2 gene (The Single Nucleotide Polymorphism database (dbSNP) identification number (ID): rs1800450) and lipopolysaccharide-binding peptide (LBP) gene（The Single Nucleotide Polymorphism database (dbSNP) ID: rs2232618）
arm group label: case group
description: patients with ARDS
arm group label: control group
description: patients Without ARDS
whole blood ,plasma,bronchoalveolar lavage fluid
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: 80 Years
healthy volunteers: No
last name: Hu Mingdong, MD
phone: 13500362524
email: huhanshandd@163.com
last name: Wang dan
phone: 18581290211
email: wada211@163.com
facility: 
status: Recruiting
contact: 
country: China
responsible party type: Sponsor-Investigator
investigator affiliation: Third Military Medical University
investigator full name: Mingdong Hu
investigator title: associate chief physician
mesh term: Respiratory Distress Syndrome
mesh term: Respiratory Distress Syndrome, Newborn
mesh term: Acute Lung Injury
mesh term: Syndrome