<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/NCT04410848</url>
  </required_header>
  <id_info>
    <org_study_id>GA19-00003</org_study_id>
    <nct_id>NCT04410848</nct_id>
  </id_info>
  <brief_title>Symbolic Regression Model To Predict Choledocholithiasis</brief_title>
  <acronym>(SymChole)</acronym>
  <official_title>Symbolic Regression Model To Predict Choledocholithiasis: Prospective Validation</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Hospital Universitario Dr. Jose E. Gonzalez</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Hospital Universitario Dr. Jose E. Gonzalez</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>
      Choledocholithiasis refers to the presence of gallstones within the common bile duct. It is&#xD;
      proposed to look for markers that help in the diagnosis and in differentiating between&#xD;
      retained and migrated gallstones. The selection of patients is a very important aspect, due&#xD;
      to the economic aspects and possible complications. Taking advantage of the development of&#xD;
      technology, the improvement in computer systems, the use of artificial intelligence and a&#xD;
      symbolic regression model that works to predict the presence of choledocholithiasis and&#xD;
      provide evidence that clarifies the treatment of patients with this pathology, especially in&#xD;
      this group where there is a bigger controversy.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Choledocholithiasis refers to the presence of gallstones within the common bile duct. It is&#xD;
      proposed to look for markers that help in the diagnosis and in differentiating between&#xD;
      retained and migrated gallstones. The selection of patients to perform endoscopic retrograde&#xD;
      cholangiopancreatography (ERCP) is a very important aspect, due to the economic aspects and&#xD;
      possible complications. By making a proper patient selection for additional studies or&#xD;
      procedure, then the costs, complications and days of stay would be reduced. Avoiding the&#xD;
      unnecessary use of ERCP would avoid its complications. Taking advantage of the development of&#xD;
      technology, the improvement in computer systems, the use of artificial intelligence and a&#xD;
      Symbolic Regression Model that works to predict the presence of choledocholithiasis and&#xD;
      provide evidence that clarifies the treatment of patients with this pathology, especially in&#xD;
      this group where there is a bigger controversy.&#xD;
&#xD;
      Having the historical database of the University Hospital (HU), regarding clinical,&#xD;
      laboratory and image variables of patients with suspected choledocholithiasis, using a&#xD;
      symbolic regression method, several randomly formed equations are generated. Each equation&#xD;
      deducts its coefficient of linear correlation (Pearson's correlation).&#xD;
&#xD;
      For the following study we admitted to the emergency department of adults at the University&#xD;
      Hospital all patients with clinical suspicion of choledocholithiasis, who meet the inclusion&#xD;
      criterion. The study which is realized is a normal one based on the method of clinical&#xD;
      predictors, obtaining laboratory studies, image studies, and patient management will be&#xD;
      carried out based on the method of clinical predictors. The calculation is made with the&#xD;
      equation obtained, and the patient is monitored until discharge. The calculation obtained&#xD;
      from the equation will not be taken into account for the decisions in the management of the&#xD;
      patient. The variables studied as white blood cells, total bilirubin values, direct&#xD;
      bilirubin, indirect bilirubin, Serum alanine aminotransferase (ALT) and aspartate&#xD;
      aminotransferase (AST), alkaline phosphatase (AP), gamma-glutamyl transpeptidase (GGT) at&#xD;
      admission will be taken from the clinical record. Transabdominal ultrasonography will be&#xD;
      performed upon admission by the diagnostic radiology department of the HU and the size of the&#xD;
      bile duct in mm, presence of gallbladder gallstones and bile duct stones will be taken from&#xD;
      the report. ERCP, magnetic resonance cholangiopancreatography (MRCP) or intraoperative&#xD;
      cholangiography will be performed and one will be taken as a confirmation of&#xD;
      choledocolithiasis, and its absence would rule it out.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">June 7, 2019</start_date>
  <completion_date type="Anticipated">July 31, 2020</completion_date>
  <primary_completion_date type="Anticipated">May 30, 2020</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>1 Year</target_duration>
  <primary_outcome>
    <measure>To validate prospectively a symbolic regression model to predict choledocholithiasis</measure>
    <time_frame>72 horas</time_frame>
    <description>To validate a model to predict choledocholithiasis compared clinical predictors.</description>
  </primary_outcome>
  <number_of_groups>1</number_of_groups>
  <enrollment type="Anticipated">200</enrollment>
  <condition>Common Bile Duct Calculi</condition>
  <arm_group>
    <arm_group_label>All patient with suspicion of choledocholithiasis</arm_group_label>
    <description>Patient with the suspect of common biliary duct stone for pain type colic in the right upper quadrant abdomen, the elevation of bilirubin, alkaline phosphatase, pancreatitis, dilated common bile duct and cholangitis. According to the criteria to assign the risk of choledocholithiasis. We are going to validate a scale based on intelligence artificial compared to the clinical predictor.</description>
  </arm_group>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>To determine the diagnostic of Choledocholithiasis with symbolic regression model</intervention_name>
    <description>To determine the diagnostic of Choledocholithiasis with symbolic regression model</description>
    <arm_group_label>All patient with suspicion of choledocholithiasis</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Patients with clinical suspicion of choledocholithiasis.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Non-Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Patients above 18 with clinical suspicion of choledocholithiasis by biliary-type pain,&#xD;
             laboratory testing that reveals a cholestatic pattern of liver test abnormalities,&#xD;
             biliary pancreatitis or dilated common bile duct&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Patient with a history of cholecystectomy&#xD;
&#xD;
          -  History of previous ERCP or surgery involving bile duct&#xD;
&#xD;
          -  Patient who could not be followed&#xD;
&#xD;
          -  Patient with other pathology that causes alteration of liver function test.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>José A. González González, MD</last_name>
    <role>Study Director</role>
    <affiliation>José Eleuterio González University Hospital</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Carlos A. Herrera Figueroa, M.D</last_name>
    <phone>+52 8127319026</phone>
    <email>carale30@hotmail.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>José A. González González, MD</last_name>
    <email>jalbertogastro@gmail.com</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Hospital Universitario Dr. Jose E. Gonzalez, Universidad Autónoma de Nuevo León</name>
      <address>
        <city>Monterrey</city>
        <state>Nuevo Leon</state>
        <zip>64460</zip>
        <country>Mexico</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Carlos A. Herrera Figueroa, M.D</last_name>
      <phone>+51 8127319026</phone>
      <email>carale30@hotmail.com</email>
    </contact>
    <contact_backup>
      <last_name>José A. González Gonzáles, MD</last_name>
      <email>jalbertogastro@gmail.com</email>
    </contact_backup>
  </location>
  <location_countries>
    <country>Mexico</country>
  </location_countries>
  <verification_date>May 2020</verification_date>
  <study_first_submitted>January 20, 2020</study_first_submitted>
  <study_first_submitted_qc>May 29, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 1, 2020</study_first_posted>
  <last_update_submitted>May 29, 2020</last_update_submitted>
  <last_update_submitted_qc>May 29, 2020</last_update_submitted_qc>
  <last_update_posted type="Actual">June 1, 2020</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Hospital Universitario Dr. Jose E. Gonzalez</investigator_affiliation>
    <investigator_full_name>Dr. med. Hector Eloy Tamez Perez</investigator_full_name>
    <investigator_title>Clinical Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Choledocholithiasis</mesh_term>
    <mesh_term>Gallstones</mesh_term>
    <mesh_term>Calculi</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </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/NCT04410848
org study id: GA19-00003
nct id: NCT04410848
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
Choledocholithiasis refers to the presence of gallstones within the common bile duct. It is
      proposed to look for markers that help in the diagnosis and in differentiating between
      retained and migrated gallstones. The selection of patients is a very important aspect, due
      to the economic aspects and possible complications. Taking advantage of the development of
      technology, the improvement in computer systems, the use of artificial intelligence and a
      symbolic regression model that works to predict the presence of choledocholithiasis and
      provide evidence that clarifies the treatment of patients with this pathology, especially in
      this group where there is a bigger controversy.
Choledocholithiasis refers to the presence of gallstones within the common bile duct. It is
      proposed to look for markers that help in the diagnosis and in differentiating between
      retained and migrated gallstones. The selection of patients to perform endoscopic retrograde
      cholangiopancreatography (ERCP) is a very important aspect, due to the economic aspects and
      possible complications. By making a proper patient selection for additional studies or
      procedure, then the costs, complications and days of stay would be reduced. Avoiding the
      unnecessary use of ERCP would avoid its complications. Taking advantage of the development of
      technology, the improvement in computer systems, the use of artificial intelligence and a
      Symbolic Regression Model that works to predict the presence of choledocholithiasis and
      provide evidence that clarifies the treatment of patients with this pathology, especially in
      this group where there is a bigger controversy.

      Having the historical database of the University Hospital (HU), regarding clinical,
      laboratory and image variables of patients with suspected choledocholithiasis, using a
      symbolic regression method, several randomly formed equations are generated. Each equation
      deducts its coefficient of linear correlation (Pearson's correlation).

      For the following study we admitted to the emergency department of adults at the University
      Hospital all patients with clinical suspicion of choledocholithiasis, who meet the inclusion
      criterion. The study which is realized is a normal one based on the method of clinical
      predictors, obtaining laboratory studies, image studies, and patient management will be
      carried out based on the method of clinical predictors. The calculation is made with the
      equation obtained, and the patient is monitored until discharge. The calculation obtained
      from the equation will not be taken into account for the decisions in the management of the
      patient. The variables studied as white blood cells, total bilirubin values, direct
      bilirubin, indirect bilirubin, Serum alanine aminotransferase (ALT) and aspartate
      aminotransferase (AST), alkaline phosphatase (AP), gamma-glutamyl transpeptidase (GGT) at
      admission will be taken from the clinical record. Transabdominal ultrasonography will be
      performed upon admission by the diagnostic radiology department of the HU and the size of the
      bile duct in mm, presence of gallbladder gallstones and bile duct stones will be taken from
      the report. ERCP, magnetic resonance cholangiopancreatography (MRCP) or intraoperative
      cholangiography will be performed and one will be taken as a confirmation of
      choledocolithiasis, and its absence would rule it out.
observational model: Case-Only
time perspective: Prospective
measure: To validate prospectively a symbolic regression model to predict choledocholithiasis
time frame: 72 horas
description: To validate a model to predict choledocholithiasis compared clinical predictors.
arm group label: All patient with suspicion of choledocholithiasis
description: Patient with the suspect of common biliary duct stone for pain type colic in the right upper quadrant abdomen, the elevation of bilirubin, alkaline phosphatase, pancreatitis, dilated common bile duct and cholangitis. According to the criteria to assign the risk of choledocholithiasis. We are going to validate a scale based on intelligence artificial compared to the clinical predictor.
intervention type: Other
intervention name: To determine the diagnostic of Choledocholithiasis with symbolic regression model
description: To determine the diagnostic of Choledocholithiasis with symbolic regression model
arm group label: All patient with suspicion of choledocholithiasis
study pop: 
sampling method: Non-Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: José A. González González, MD
role: Study Director
affiliation: José Eleuterio González University Hospital
last name: Carlos A. Herrera Figueroa, M.D
phone: +52 8127319026
email: carale30@hotmail.com
last name: José A. González González, MD
email: jalbertogastro@gmail.com
facility: 
status: Recruiting
contact: 
contact backup: 
country: Mexico
responsible party type: Principal Investigator
investigator affiliation: Hospital Universitario Dr. Jose E. Gonzalez
investigator full name: Dr. med. Hector Eloy Tamez Perez
investigator title: Clinical Professor
mesh term: Choledocholithiasis
mesh term: Gallstones
mesh term: Calculi
sharing ipd: No