<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/NCT04482387</url>
  </required_header>
  <id_info>
    <org_study_id>IRAS196573</org_study_id>
    <nct_id>NCT04482387</nct_id>
  </id_info>
  <brief_title>DigiVis: Self-testing Vision App for Telephone Consultations</brief_title>
  <official_title>DigiVis: Validation of Self-testing Visual Acuity Web-based App to Aid Ophthalmic Telephone Consultations During Covid19 Lockdown and Subsequent Social Distancing Crisis</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Cambridge University Hospitals NHS Foundation Trust</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Cambridge University Hospitals NHS Foundation Trust</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>
      This trial aims to assess the accuracy and test-retest variability of a new digital app which&#xD;
      enables community visual acuity testing without requirement of an trained examiner.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Eye problems like macular degeneration and amblyopia (lazy eye) require regular monitoring to&#xD;
      prevent permanent visual impairment. Over 2000 patients a month are seen in Cambridge&#xD;
      University Hospitals NHS Trust (CUH) eye clinics; concern about Covid-19 infection has led to&#xD;
      over 80% of consultations being conducted by telephone with few clinical clues to inform&#xD;
      decision making. Patients will face long delays even when routine clinics restart: there is&#xD;
      no doubt that some will suffer preventable visual loss.&#xD;
&#xD;
      DigiVis is a web-based vision testing app enabling self-testing of vision at home. Early&#xD;
      testing and patient feedback is positive: 80% of children prefer DigiVis to regular testing.&#xD;
      The investigators wish to test how accurately the app works for home use, by asking older&#xD;
      children and adults to self-test their vision prior to their planned face to face clinic&#xD;
      appointment. Once tested, DigiVis will be available free of charge to patients, not only&#xD;
      during the Covid-19 crisis, but also to support telephonic consultations in the future.&#xD;
&#xD;
      Visual acuity (VA) is a fundamental measure of vision required for all ophthalmic&#xD;
      assessments. It is measured by health professionals using vision charts. DigiVis is a new app&#xD;
      which enables self-testing of VA using two wirelessly connected digital devices. By matching&#xD;
      letters on a handheld device to those displayed on the second device a distance away,&#xD;
      threshold VA can be measured using a staircase algorithm. The distance and scaling of the&#xD;
      test is vital to its accuracy and a concept (patent filed by Cambridge Enterprise) in DigiVis&#xD;
      enables this without the need for manual distance measurement or an observer.&#xD;
&#xD;
      Early validation using two tablet computers in 150 clinic patients has given positive&#xD;
      results, both in testing accuracy and patient feedback. With the current Covid-19 crisis&#xD;
      limiting face to face appointments, there is an urgent need for accurate home VA assessment.&#xD;
      The DigiVis app has been re-coded for free website delivery for this purpose.&#xD;
&#xD;
      The investigators wish to formally validate DigiVis home testing following Conformitè&#xD;
      Europëenne (CE class I) marking so that it can be recommended for clinical use. 250 patients&#xD;
      will be invited to self-test their VA twice using DigiVis prior to a planned face to face&#xD;
      clinic appointment. The test-retest variability and comparison of DigiVis VA to chart based&#xD;
      assessment will be compared.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Unknown status</overall_status>
  <last_known_status>Recruiting</last_known_status>
  <start_date type="Actual">July 24, 2020</start_date>
  <completion_date type="Anticipated">July 1, 2021</completion_date>
  <primary_completion_date type="Anticipated">July 1, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>N/A</allocation>
    <intervention_model>Sequential Assignment</intervention_model>
    <intervention_model_description>Patients will test their own vision twice using the DigiVis app twice, subsequently they will have visual acuity assessment in eye clinic by a trained examiner. The results of visual acuity will be compared using Bland Altman statistical analysis.</intervention_model_description>
    <primary_purpose>Diagnostic</primary_purpose>
    <masking>None (Open Label)</masking>
    <masking_description>The eye clinic visual acuity examiner will be masked to the result of the DigiVis tests.</masking_description>
  </study_design_info>
  <primary_outcome>
    <measure>Comparison of visual acuity measurement using DigiVis testing and standard visual acuity testing</measure>
    <time_frame>within 30 days</time_frame>
    <description>Measurement bias in logMAR units between DigiVis testing and standard visual acuity testing score compared to</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Levels of Agreement between DigiVis testing and standard visual acuity testing</measure>
    <time_frame>within 30 days</time_frame>
    <description>Upper and lower levels of agreement measured in logMAR units</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>DigiVis test repeatability</measure>
    <time_frame>within 30 days</time_frame>
    <description>Measurement of test-retest variability</description>
  </secondary_outcome>
  <number_of_arms>1</number_of_arms>
  <enrollment type="Anticipated">250</enrollment>
  <condition>Visual Impairment</condition>
  <condition>Amblyopia Suspect</condition>
  <arm_group>
    <arm_group_label>subjects recruited to visual acuity testing</arm_group_label>
    <arm_group_type>Other</arm_group_type>
    <description>All recruited subjects will have the intervention (Digivis visual acuity self-testing) and the standard clinical visual acuity assessment in clinic.</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>DigiVis visual acuity app</intervention_name>
    <description>Self-testing of visual acuity app on two occasions</description>
    <arm_group_label>subjects recruited to visual acuity testing</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Age between 5 and 85 years&#xD;
&#xD;
          -  Previous recorded visual acuity of at least +0.8 logMAR in or both eyes&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Individuals with poor conversant English&#xD;
&#xD;
          -  Individuals with cognitive impairment&#xD;
&#xD;
          -  Subjects unable to access the internet on two digital devices&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>5 Years</minimum_age>
    <maximum_age>85 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Stephen E Kelleher</last_name>
    <role>Study Director</role>
    <affiliation>Cambridge University Hospitals NHS Foundation Trust</affiliation>
  </overall_official>
  <overall_contact>
    <last_name>Louise E Allen, MBBS MD</last_name>
    <phone>07941666981</phone>
    <email>louise@louiseallen.com</email>
  </overall_contact>
  <overall_contact_backup>
    <last_name>Nabil Uddin</last_name>
    <email>nabil.uddin@addenbrookes.nhs.uk</email>
  </overall_contact_backup>
  <location>
    <facility>
      <name>Cambridge University Hospitals NHS Trust</name>
      <address>
        <city>Cambridge</city>
        <state>Cambs</state>
        <zip>CB2 0QQ</zip>
        <country>United Kingdom</country>
      </address>
    </facility>
    <status>Recruiting</status>
    <contact>
      <last_name>Louise Allen</last_name>
      <phone>07941666981</phone>
      <email>louise@louiseallen.com</email>
    </contact>
    <contact_backup>
      <last_name>Nabil Uddin</last_name>
      <email>nabil.uddin@addenbrookes.nhs.uk</email>
    </contact_backup>
  </location>
  <location_countries>
    <country>United Kingdom</country>
  </location_countries>
  <reference>
    <citation>Rono HK, Bastawrous A, Macleod D, Wanjala E, Di Tanna GL, Weiss HA, Burton MJ. Smartphone-based screening for visual impairment in Kenyan school children: a cluster randomised controlled trial. Lancet Glob Health. 2018 Aug;6(8):e924-e932. doi: 10.1016/S2214-109X(18)30244-4. Erratum In: Lancet Glob Health. 2018 Oct;6(10):e1072.</citation>
    <PMID>30012273</PMID>
  </reference>
  <reference>
    <citation>Bastawrous A, Rono HK, Livingstone IA, Weiss HA, Jordan S, Kuper H, Burton MJ. Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork. JAMA Ophthalmol. 2015 Aug;133(8):930-7. doi: 10.1001/jamaophthalmol.2015.1468. Erratum In: JAMA Ophthalmol. 2015 Sep;133(9):1096.</citation>
    <PMID>26022921</PMID>
  </reference>
  <verification_date>January 2021</verification_date>
  <study_first_submitted>July 17, 2020</study_first_submitted>
  <study_first_submitted_qc>July 21, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">July 22, 2020</study_first_posted>
  <last_update_submitted>January 12, 2021</last_update_submitted>
  <last_update_submitted_qc>January 12, 2021</last_update_submitted_qc>
  <last_update_posted type="Actual">January 14, 2021</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>Cambridge University Hospitals NHS Foundation Trust</investigator_affiliation>
    <investigator_full_name>Louise Allen</investigator_full_name>
    <investigator_title>Principal investigator</investigator_title>
  </responsible_party>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Amblyopia</mesh_term>
    <mesh_term>Vision Disorders</mesh_term>
    <mesh_term>Vision, Low</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <pending_results>
    <submitted>November 27, 2022</submitted>
  </pending_results>
  <!-- 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/NCT04482387
org study id: IRAS196573
nct id: NCT04482387
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
This trial aims to assess the accuracy and test-retest variability of a new digital app which
      enables community visual acuity testing without requirement of an trained examiner.
Eye problems like macular degeneration and amblyopia (lazy eye) require regular monitoring to
      prevent permanent visual impairment. Over 2000 patients a month are seen in Cambridge
      University Hospitals NHS Trust (CUH) eye clinics; concern about Covid-19 infection has led to
      over 80% of consultations being conducted by telephone with few clinical clues to inform
      decision making. Patients will face long delays even when routine clinics restart: there is
      no doubt that some will suffer preventable visual loss.

      DigiVis is a web-based vision testing app enabling self-testing of vision at home. Early
      testing and patient feedback is positive: 80% of children prefer DigiVis to regular testing.
      The investigators wish to test how accurately the app works for home use, by asking older
      children and adults to self-test their vision prior to their planned face to face clinic
      appointment. Once tested, DigiVis will be available free of charge to patients, not only
      during the Covid-19 crisis, but also to support telephonic consultations in the future.

      Visual acuity (VA) is a fundamental measure of vision required for all ophthalmic
      assessments. It is measured by health professionals using vision charts. DigiVis is a new app
      which enables self-testing of VA using two wirelessly connected digital devices. By matching
      letters on a handheld device to those displayed on the second device a distance away,
      threshold VA can be measured using a staircase algorithm. The distance and scaling of the
      test is vital to its accuracy and a concept (patent filed by Cambridge Enterprise) in DigiVis
      enables this without the need for manual distance measurement or an observer.

      Early validation using two tablet computers in 150 clinic patients has given positive
      results, both in testing accuracy and patient feedback. With the current Covid-19 crisis
      limiting face to face appointments, there is an urgent need for accurate home VA assessment.
      The DigiVis app has been re-coded for free website delivery for this purpose.

      The investigators wish to formally validate DigiVis home testing following Conformitè
      Europëenne (CE class I) marking so that it can be recommended for clinical use. 250 patients
      will be invited to self-test their VA twice using DigiVis prior to a planned face to face
      clinic appointment. The test-retest variability and comparison of DigiVis VA to chart based
      assessment will be compared.
allocation: N/A
intervention model: Sequential Assignment
intervention model description: Patients will test their own vision twice using the DigiVis app twice, subsequently they will have visual acuity assessment in eye clinic by a trained examiner. The results of visual acuity will be compared using Bland Altman statistical analysis.
primary purpose: Diagnostic
masking: None (Open Label)
masking description: The eye clinic visual acuity examiner will be masked to the result of the DigiVis tests.
measure: Comparison of visual acuity measurement using DigiVis testing and standard visual acuity testing
time frame: within 30 days
description: Measurement bias in logMAR units between DigiVis testing and standard visual acuity testing score compared to
measure: Levels of Agreement between DigiVis testing and standard visual acuity testing
time frame: within 30 days
description: Upper and lower levels of agreement measured in logMAR units
measure: DigiVis test repeatability
time frame: within 30 days
description: Measurement of test-retest variability
arm group label: subjects recruited to visual acuity testing
arm group type: Other
description: All recruited subjects will have the intervention (Digivis visual acuity self-testing) and the standard clinical visual acuity assessment in clinic.
intervention type: Device
intervention name: DigiVis visual acuity app
description: Self-testing of visual acuity app on two occasions
arm group label: subjects recruited to visual acuity testing
criteria: 
gender: All
minimum age: 5 Years
maximum age: 85 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Stephen E Kelleher
role: Study Director
affiliation: Cambridge University Hospitals NHS Foundation Trust
last name: Louise E Allen, MBBS MD
phone: 07941666981
email: louise@louiseallen.com
last name: Nabil Uddin
email: nabil.uddin@addenbrookes.nhs.uk
facility: 
status: Recruiting
contact: 
contact backup: 
country: United Kingdom
citation: Rono HK, Bastawrous A, Macleod D, Wanjala E, Di Tanna GL, Weiss HA, Burton MJ. Smartphone-based screening for visual impairment in Kenyan school children: a cluster randomised controlled trial. Lancet Glob Health. 2018 Aug;6(8):e924-e932. doi: 10.1016/S2214-109X(18)30244-4. Erratum In: Lancet Glob Health. 2018 Oct;6(10):e1072.
PMID: 30012273
citation: Bastawrous A, Rono HK, Livingstone IA, Weiss HA, Jordan S, Kuper H, Burton MJ. Development and Validation of a Smartphone-Based Visual Acuity Test (Peek Acuity) for Clinical Practice and Community-Based Fieldwork. JAMA Ophthalmol. 2015 Aug;133(8):930-7. doi: 10.1001/jamaophthalmol.2015.1468. Erratum In: JAMA Ophthalmol. 2015 Sep;133(9):1096.
PMID: 26022921
responsible party type: Principal Investigator
investigator affiliation: Cambridge University Hospitals NHS Foundation Trust
investigator full name: Louise Allen
investigator title: Principal investigator
mesh term: Amblyopia
mesh term: Vision Disorders
mesh term: Vision, Low
sharing ipd: No
submitted: November 27, 2022