<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/NCT04413370</url>
  </required_header>
  <id_info>
    <org_study_id>Dry eye screening system</org_study_id>
    <nct_id>NCT04413370</nct_id>
  </id_info>
  <brief_title>Dry Eye Screening and Referral System</brief_title>
  <official_title>The Development of Artificial Intelligence Dry Eye Screening and Referral System</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Sun Yat-sen University</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Sun Yat-sen University</source>
  <oversight_info>
    <has_dmc>Yes</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>
      Dry eye is one of the most common ocular surface diseases. Its pathogenic factors are related&#xD;
      to multiple etiology. Because of the complexity of the pathogenesis of dry eye, the diversity&#xD;
      of related examinations, and the inconsistency of symptoms and signs of dry eye patients, the&#xD;
      diagnosis of dry eye has higher requirements on the professional technology and examination&#xD;
      equipment of ophthalmologists.&#xD;
&#xD;
      The purpose of this study is to establish a case-control cohort of dry eye patients.&#xD;
      Multimodal data will be collected from participants, including medical history information,&#xD;
      ocular surface disease index scale (OSDI), anterior segment photography, and treatment&#xD;
      outcome of dry eye patients. The correlation between the characteristics of anterior segment&#xD;
      images and dry eye diagnosis will be explored by artificial intelligence algorithms. The&#xD;
      purpose of this study was to develop an artificial intelligence dry eye screening and&#xD;
      referral system.&#xD;
    </textblock>
  </brief_summary>
  <overall_status>Active, not recruiting</overall_status>
  <start_date type="Actual">January 6, 2020</start_date>
  <completion_date type="Anticipated">August 1, 2022</completion_date>
  <primary_completion_date type="Actual">April 19, 2022</primary_completion_date>
  <study_type>Observational [Patient Registry]</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>
  <target_duration>1 Day</target_duration>
  <primary_outcome>
    <measure>Area under the curve (severe)</measure>
    <time_frame>up to 1 month</time_frame>
    <description>AUC values for predicting whether subject need to be referral or not.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Area under the curve (each group)</measure>
    <time_frame>up to 1 month</time_frame>
    <description>AUC values for predicting whether subject can be accurately grouped into each of the four groups.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Accuracy, true positive rate, and true negative rate</measure>
    <time_frame>up to 1 month</time_frame>
    <description>The performance of this artificial platform.</description>
  </secondary_outcome>
  <number_of_groups>3</number_of_groups>
  <enrollment type="Actual">518</enrollment>
  <condition>Dry Eye</condition>
  <arm_group>
    <arm_group_label>Severe Group</arm_group_label>
    <description>This group of subjects needed a referral to the hospital for further treatments.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Mild group</arm_group_label>
    <description>This group of subjects was diagnosed with dry eye but can use artificial tears instead of further treatment.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Follow-up group</arm_group_label>
    <description>This group of subjects had no dry eye symptoms and signs and belonged to the normal control group.</description>
  </arm_group>
  <intervention>
    <intervention_type>Diagnostic Test</intervention_type>
    <intervention_name>Dry eye diagnostic test</intervention_name>
    <description>The artificial intelligent dry eye screening platform</description>
    <arm_group_label>Follow-up group</arm_group_label>
    <arm_group_label>Mild group</arm_group_label>
    <arm_group_label>Severe Group</arm_group_label>
  </intervention>
  <eligibility>
    <study_pop>
      <textblock>
        Subjects who are equal or over 18 years old with or without dry eye symptoms and signs.&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. Subjects whose age are greater than or equal to 18 years old;&#xD;
&#xD;
          2. Subjects who can cooperate with the inspection;&#xD;
&#xD;
          3. Subjects who agree to participate in the study and sign the consent form.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Subjects who cannot do the inspection.&#xD;
&#xD;
          2. Subjects who suffer from diseases that compromise the inspection.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <location>
    <facility>
      <name>Zhongshan Ophthalmic Center</name>
      <address>
        <city>Guangzhou</city>
        <state>Guangdong</state>
        <zip>510632</zip>
        <country>China</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>China</country>
  </location_countries>
  <verification_date>April 2022</verification_date>
  <study_first_submitted>May 28, 2020</study_first_submitted>
  <study_first_submitted_qc>May 28, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 2, 2020</study_first_posted>
  <last_update_submitted>April 18, 2022</last_update_submitted>
  <last_update_submitted_qc>April 18, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">April 25, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Sun Yat-sen University</investigator_affiliation>
    <investigator_full_name>Haotian Lin</investigator_full_name>
    <investigator_title>Professor</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Dry Eye Syndromes</mesh_term>
    <mesh_term>Keratoconjunctivitis Sicca</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/NCT04413370
org study id: Dry eye screening system
nct id: NCT04413370
lead sponsor: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
Dry eye is one of the most common ocular surface diseases. Its pathogenic factors are related
      to multiple etiology. Because of the complexity of the pathogenesis of dry eye, the diversity
      of related examinations, and the inconsistency of symptoms and signs of dry eye patients, the
      diagnosis of dry eye has higher requirements on the professional technology and examination
      equipment of ophthalmologists.

      The purpose of this study is to establish a case-control cohort of dry eye patients.
      Multimodal data will be collected from participants, including medical history information,
      ocular surface disease index scale (OSDI), anterior segment photography, and treatment
      outcome of dry eye patients. The correlation between the characteristics of anterior segment
      images and dry eye diagnosis will be explored by artificial intelligence algorithms. The
      purpose of this study was to develop an artificial intelligence dry eye screening and
      referral system.
observational model: Case-Control
time perspective: Prospective
measure: Area under the curve (severe)
time frame: up to 1 month
description: AUC values for predicting whether subject need to be referral or not.
measure: Area under the curve (each group)
time frame: up to 1 month
description: AUC values for predicting whether subject can be accurately grouped into each of the four groups.
measure: Accuracy, true positive rate, and true negative rate
time frame: up to 1 month
description: The performance of this artificial platform.
arm group label: Severe Group
description: This group of subjects needed a referral to the hospital for further treatments.
arm group label: Mild group
description: This group of subjects was diagnosed with dry eye but can use artificial tears instead of further treatment.
arm group label: Follow-up group
description: This group of subjects had no dry eye symptoms and signs and belonged to the normal control group.
intervention type: Diagnostic Test
intervention name: Dry eye diagnostic test
description: The artificial intelligent dry eye screening platform
arm group label: Follow-up group
arm group label: Mild group
arm group label: Severe Group
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: Accepts Healthy Volunteers
facility: 
country: China
responsible party type: Principal Investigator
investigator affiliation: Sun Yat-sen University
investigator full name: Haotian Lin
investigator title: Professor
mesh term: Dry Eye Syndromes
mesh term: Keratoconjunctivitis Sicca
sharing ipd: No