xml: <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/NCT05989802</url>
    </required_header>
    <id_info>
      <org_study_id>R01HL169449</org_study_id>
      <secondary_id>U01AI152087</secondary_id>
      <secondary_id>7200AA22RFA00004</secondary_id>
      <nct_id>NCT05989802</nct_id>
    </id_info>
    <brief_title>Rapid Research in Diagnostics Development for TB Network (R2D2 Kids) and Assessing Diagnostics At POC for TB in Children (ADAPT for Kids)</brief_title>
    <official_title>Rapid Research in Diagnostics Development for Tuberculosis Network (R2D2 Kids) and Assessing Diagnostics At Point-of-care for Tuberculosis in Children (ADAPT for Kids)</official_title>
    <sponsors>
      <lead_sponsor>
        <agency>University of California, San Francisco</agency>
        <agency_class>Other</agency_class>
      </lead_sponsor>
      <collaborator>
        <agency>Instituto Nacional de Saúde, Mozambique</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>National Referral Hospital</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>University of Cape Town</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Johns Hopkins University</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>Elizabeth Glaser Pediatric AIDS Foundation</agency>
        <agency_class>Other</agency_class>
      </collaborator>
      <collaborator>
        <agency>National Institute of Allergy and Infectious Diseases (NIAID)</agency>
        <agency_class>NIH</agency_class>
      </collaborator>
      <collaborator>
        <agency>University of California, Irvine</agency>
        <agency_class>Other</agency_class>
      </collaborator>
    </sponsors>
    <source>University of California, San Francisco</source>
    <oversight_info>
      <has_dmc>No</has_dmc>
      <is_fda_regulated_drug>No</is_fda_regulated_drug>
      <is_fda_regulated_device>Yes</is_fda_regulated_device>
      <is_unapproved_device>Yes</is_unapproved_device>
      <is_us_export>Yes</is_us_export>
    </oversight_info>
    <brief_summary>
      <textblock>
        Every year there are an estimated 230,000 childhood deaths from TB. There is an urgent need&#xD;
        for novel tests for TB diagnosis in children under 15 years. The Rapid Research in&#xD;
        Diagnostics Development for TB Network (R2D2 Kids) and the Assessing Diagnostics at&#xD;
        Point-of-care for Tuberculosis in children (ADAPT for Kids) studies seek to reduce the burden&#xD;
        of TB worldwide by evaluating faster, simpler, and less expensive TB triage and diagnostic&#xD;
        tests for use in children.&#xD;
      </textblock>
    </brief_summary>
    <detailed_description>
      <textblock>
        The Rapid Research in Diagnostics Development for TB Network (R2D2 Kids) and the Assessing&#xD;
        Diagnostics at Point-of-care for Tuberculosis in children (ADAPT for Kids) studies will&#xD;
        rigorously assess promising, point-of-care (POC) TB diagnostic tests in clinical studies&#xD;
        conducted among children at settings of intended use. There is an urgent need for novel tests&#xD;
        for TB diagnosis in children under 15 years because of the challenge of obtaining sputum&#xD;
        samples from children and the low sputum bacillary burden among children with TB even when a&#xD;
        sample is obtained. This creates delays in diagnosis and treatment initiation, and is a major&#xD;
        contributor to the 230,000 childhood deaths from TB each year. Therefore, a non-sputum&#xD;
        biomarker-based test has been ranked among the highest priority target product profiles for&#xD;
        new TB diagnostics. If inexpensive and simple to perform, such a diagnostic tool could have&#xD;
        significant impact by facilitating rapid diagnosis and TB treatment in children. The studies&#xD;
        will evaluate the sensitivity and specificity of novel diagnostic tests in children in&#xD;
        reference to NIH consensus definitions for childhood TB. In addition, the usability and&#xD;
        acceptability of the novel TB diagnostic tests will be assessed through direct observations&#xD;
        and surveys of routine health workers.&#xD;
      </textblock>
    </detailed_description>
    <overall_status>Not yet recruiting</overall_status>
    <start_date type="Anticipated">September 1, 2023</start_date>
    <completion_date type="Anticipated">September 1, 2026</completion_date>
    <primary_completion_date type="Anticipated">September 1, 2026</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>Single Group Assignment</intervention_model>
      <primary_purpose>Diagnostic</primary_purpose>
      <masking>None (Open Label)</masking>
    </study_design_info>
    <primary_outcome>
      <measure>Proportion with positive index test result among participants with tuberculosis (TB)</measure>
      <time_frame>2 years</time_frame>
      <description>Sensitivity - Number with positive index test result/(Number with positive or negative index t test result) among participants with TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)</description>
    </primary_outcome>
    <primary_outcome>
      <measure>Proportion with negative index test result among participants without tuberculosis (TB)</measure>
      <time_frame>2 years</time_frame>
      <description>Specificity - Number with negative index test results/(Number with positive or negative index t test result) among participants without TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)</description>
    </primary_outcome>
    <number_of_arms>1</number_of_arms>
    <enrollment type="Anticipated">2100</enrollment>
    <condition>Tuberculosis</condition>
    <condition>Diagnostics</condition>
    <condition>Global Health</condition>
    <arm_group>
      <arm_group_label>Evaluation of various novel TB triage and diagnostic tests</arm_group_label>
      <arm_group_type>Experimental</arm_group_type>
      <description>The investigators will conduct evaluation of novel TB triage and diagnostic tests in a cohort of children with presumed TB. The investigators aim to enroll 250 participants per year at each of three enrollment sites for evaluation of various novel TB triage and diagnostic tests and 30 health workers to assess test usability. Novel test evaluations will be conducted on a rolling basis as new tests ready for field evaluation are identified.</description>
    </arm_group>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Oral swab molecular testing</intervention_name>
      <description>Swab-based testing provides a non-invasive approach to collect respiratory specimens for TB testing. Data in adults suggests that swab-based testing could be valuable when sputum collection is not feasible or available.</description>
      <arm_group_label>Evaluation of various novel TB triage and diagnostic tests</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Automated Cough Sound Analysis</intervention_name>
      <description>Cough sounds can be collected through a mobile phone and tablet, and then analyzed with machine learning algorithms to predict TB.</description>
      <arm_group_label>Evaluation of various novel TB triage and diagnostic tests</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Diagnostic Test</intervention_type>
      <intervention_name>Automated Lung Sound Analysis</intervention_name>
      <description>Lung sounds can be collected with a non-invasive digital stethoscope, and then saved on a tablet or phone and analyzed by machine learning algorithms to predict TB.</description>
      <arm_group_label>Evaluation of various novel TB triage and diagnostic tests</arm_group_label>
    </intervention>
    <intervention>
      <intervention_type>Other</intervention_type>
      <intervention_name>Chest X Ray Computer Aided Detection</intervention_name>
      <description>Several artificial intelligence algorithms have been developed to predict TB, though this has not yet been validated in children.</description>
      <arm_group_label>Evaluation of various novel TB triage and diagnostic tests</arm_group_label>
      <other_name>Artificial Intelligence algorithm</other_name>
    </intervention>
    <eligibility>
      <criteria>
        <textblock>
          Participant eligibility criteria:&#xD;
  &#xD;
          Participants will include children (age &lt;15 years) who present to care with:&#xD;
  &#xD;
          A. 2 or more of the following:&#xD;
  &#xD;
            -  Unexplained cough for any duration&#xD;
  &#xD;
            -  TB contact or tuberculin skin test or interferon gamma release assay positive&#xD;
  &#xD;
            -  Abnormal chest X-ray (any abnormality) OR&#xD;
  &#xD;
          B. Any one of criteria A AND any one of the following:&#xD;
  &#xD;
            -  Unexplained weight loss OR unexplained failure to thrive OR Severe Acute Malnutrition&#xD;
  &#xD;
            -  Unexplained fever ≥2 weeks&#xD;
  &#xD;
            -  Unexplained lethargy or reduced playfulness ≥2 weeks&#xD;
  &#xD;
          The study will exclude participants who:&#xD;
  &#xD;
            1. Completed preventive or active TB treatment within the past 12 months (to increase TB&#xD;
               prevalence and reduce false-positive results, respectively);&#xD;
  &#xD;
            2. Have taken any medication with anti-mycobacterial activity for any reason for greater&#xD;
               than 3 days at the time of enrollment (to reduce false-negatives);&#xD;
  &#xD;
            3. Are unable to return for follow-up visits; or&#xD;
  &#xD;
            4. Whose parents/guardians are unwilling to provide informed consent or who are unwilling&#xD;
               to provide assent if applicable (age determined by local IRB)&#xD;
  &#xD;
          Assessment of the usability of novel TB tests:&#xD;
  &#xD;
          The study will also include health workers at each clinical site who are 1) aged ≥18 years&#xD;
          and 2) involved in routine TB testing (collecting specimens for or performing TB tests).&#xD;
          Personnel who are unwilling to provide informed consent will be excluded.&#xD;
        </textblock>
      </criteria>
      <gender>All</gender>
      <minimum_age>N/A</minimum_age>
      <maximum_age>65 Years</maximum_age>
      <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
    </eligibility>
    <overall_official>
      <last_name>Adithya Cattamanchi, MD, MAS</last_name>
      <role>Principal Investigator</role>
      <affiliation>University of California, Irvine</affiliation>
    </overall_official>
    <overall_official>
      <last_name>Nilesh Bhatt</last_name>
      <role>Principal Investigator</role>
      <affiliation>Elizabeth Glazer Pediatric AIDS Foundation</affiliation>
    </overall_official>
    <overall_contact>
      <last_name>Devan Jaganath, MD</last_name>
      <phone>415-514-4692</phone>
      <email>devan.jaganath@ucsf.edu</email>
    </overall_contact>
    <overall_contact_backup>
      <last_name>Brittney Sweetser, MPH</last_name>
      <email>bsweetse@hs.uci.edu</email>
    </overall_contact_backup>
    <location>
      <facility>
        <name>Instituto Nacional de Saúde</name>
        <address>
          <city>Maputo</city>
          <country>Mozambique</country>
        </address>
      </facility>
      <contact>
        <last_name>Celso Khosa</last_name>
        <email>celso.khosa@ins.gov.mz</email>
      </contact>
    </location>
    <location>
      <facility>
        <name>Dora Nginza Hospital</name>
        <address>
          <city>Cape Town</city>
          <country>South Africa</country>
        </address>
      </facility>
      <contact>
        <last_name>Heather Zar</last_name>
        <email>heather.zar@uct.ac.za</email>
      </contact>
    </location>
    <location>
      <facility>
        <name>Mulago National Referral Hospital</name>
        <address>
          <city>Kampala</city>
          <country>Uganda</country>
        </address>
      </facility>
      <contact>
        <last_name>Eric Wobudeya</last_name>
        <email>ewobudeya@mujhu.org</email>
      </contact>
    </location>
    <location_countries>
      <country>Mozambique</country>
      <country>South Africa</country>
      <country>Uganda</country>
    </location_countries>
    <reference>
      <citation>Perez-Velez CM, Marais BJ. Tuberculosis in children. N Engl J Med. 2012 Jul 26;367(4):348-61. doi: 10.1056/NEJMra1008049. No abstract available.</citation>
      <PMID>22830465</PMID>
    </reference>
    <reference>
      <citation>World Health Organization. Roadmap towards ending TB in children and adolescents. Geneva: World Health Organization, 2018. Available at: https://www.who.int/tb/publications/2018/tb-childhoodroadmap/en/. Last accessed 1 June 2022.</citation>
    </reference>
    <reference>
      <citation>WHO. High-priority target product profiles for new tuberculosis diagnostics: Report of a consensus meeting. Geneva, Switzerland. Available at: http://www.who.int/tb/publications/tpp_report/en/, 2014.</citation>
    </reference>
    <reference>
      <citation>Graham SM, Cuevas LE, Jean-Philippe P, Browning R, Casenghi M, Detjen AK, Gnanashanmugam D, Hesseling AC, Kampmann B, Mandalakas A, Marais BJ, Schito M, Spiegel HM, Starke JR, Worrell C, Zar HJ. Clinical Case Definitions for Classification of Intrathoracic Tuberculosis in Children: An Update. Clin Infect Dis. 2015 Oct 15;61Suppl 3(Suppl 3):S179-87. doi: 10.1093/cid/civ581.</citation>
      <PMID>26409281</PMID>
    </reference>
    <reference>
      <citation>World Health Organization. Global Tuberculosis Report 2021. Geneva: World Health Organization, 2021.</citation>
    </reference>
    <reference>
      <citation>World Health Organization. Roadmap towards ending TB in children and adolescents. Geneva: World Health Organization, 2018.</citation>
    </reference>
    <reference>
      <citation>Lewinsohn DM, Leonard MK, LoBue PA, Cohn DL, Daley CL, Desmond E, Keane J, Lewinsohn DA, Loeffler AM, Mazurek GH, O'Brien RJ, Pai M, Richeldi L, Salfinger M, Shinnick TM, Sterling TR, Warshauer DM, Woods GL. Official American Thoracic Society/Infectious Diseases Society of America/Centers for Disease Control and Prevention Clinical Practice Guidelines: Diagnosis of Tuberculosis in Adults and Children. Clin Infect Dis. 2017 Jan 15;64(2):111-115. doi: 10.1093/cid/ciw778.</citation>
      <PMID>28052967</PMID>
    </reference>
    <reference>
      <citation>WHO consolidated guidelines on tuberculosis: Module 5: Management of tuberculosis in children and adolescents [Internet]. Geneva: World Health Organization; 2022. Available from http://www.ncbi.nlm.nih.gov/books/NBK579387/</citation>
      <PMID>35404556</PMID>
    </reference>
    <reference>
      <citation>Jaganath D, Beaudry J, Salazar-Austin N. Tuberculosis in Children. Infect Dis Clin North Am. 2022 Mar;36(1):49-71. doi: 10.1016/j.idc.2021.11.008.</citation>
      <PMID>35168714</PMID>
    </reference>
    <reference>
      <citation>Zawedde-Muyanja S, Reuter A, Tovar MA, Hussain H, Loando Mboyo A, Detjen AK, Yuen CM. Provision of Decentralized TB Care Services: A Detect-Treat-Prevent Strategy for Children and Adolescents Affected by TB. Pathogens. 2021 Dec 1;10(12):1568. doi: 10.3390/pathogens10121568.</citation>
      <PMID>34959523</PMID>
    </reference>
    <reference>
      <citation>Dodd PJ, Yuen CM, Sismanidis C, Seddon JA, Jenkins HE. The global burden of tuberculosis mortality in children: a mathematical modelling study. Lancet Glob Health. 2017 Sep;5(9):e898-e906. doi: 10.1016/S2214-109X(17)30289-9.</citation>
      <PMID>28807188</PMID>
    </reference>
    <reference>
      <citation>World Health Organization. High-priority target product profiles for new tuberculosis diagnostics: report of a consensus meeting. Available at: http://apps.who.int/iris/bitstream/handle/10665/135617/WHO_HTM_TB_2014.18_eng.pdf?sequence=12014.</citation>
    </reference>
    <reference>
      <citation>Andama A, Whitman GR, Crowder R, Reza TF, Jaganath D, Mulondo J, Nalugwa TK, Semitala FC, Worodria W, Cook C, Wood RC, Weigel KM, Olson AM, Lohmiller Shaw J, Kato-Maeda M, Denkinger CM, Nahid P, Cangelosi GA, Cattamanchi A. Accuracy of Tongue Swab Testing Using Xpert MTB-RIF Ultra for Tuberculosis Diagnosis. J Clin Microbiol. 2022 Jul 20;60(7):e0042122. doi: 10.1128/jcm.00421-22. Epub 2022 Jun 27.</citation>
      <PMID>35758702</PMID>
    </reference>
    <reference>
      <citation>Nkereuwem E, Togun T, Gomez MP, Szekely R, Mace A, Jobe D, Schumacher SG, Kampmann B, Denkinger CM; Reach4KidsAfrica (R4KA) Consortium. Comparing accuracy of lipoarabinomannan urine tests for diagnosis of pulmonary tuberculosis in children from four African countries: a cross-sectional study. Lancet Infect Dis. 2021 Mar;21(3):376-384. doi: 10.1016/S1473-3099(20)30598-3. Epub 2020 Dec 11.</citation>
      <PMID>33316214</PMID>
    </reference>
    <reference>
      <citation>Yellapu GD, Rudraraju G, Sripada NR, Mamidgi B, Jalukuru C, Firmal P, Yechuri V, Varanasi S, Peddireddi VS, Bhimarasetty DM, Kanisetti S, Joshi N, Mohapatra P, Pamarthi K. Development and clinical validation of Swaasa AI platform for screening and prioritization of pulmonary TB. Sci Rep. 2023 Mar 23;13(1):4740. doi: 10.1038/s41598-023-31772-9. Erratum In: Sci Rep. 2023 Jun 26;13(1):10353.</citation>
      <PMID>36959347</PMID>
    </reference>
    <reference>
      <citation>Kevat A, Kalirajah A, Roseby R. Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes. Respir Res. 2020 Sep 29;21(1):253. doi: 10.1186/s12931-020-01523-9.</citation>
      <PMID>32993620</PMID>
    </reference>
    <reference>
      <citation>Harris M, Qi A, Jeagal L, Torabi N, Menzies D, Korobitsyn A, Pai M, Nathavitharana RR, Ahmad Khan F. A systematic review of the diagnostic accuracy of artificial intelligence-based computer programs to analyze chest x-rays for pulmonary tuberculosis. PLoS One. 2019 Sep 3;14(9):e0221339. doi: 10.1371/journal.pone.0221339. eCollection 2019.</citation>
      <PMID>31479448</PMID>
    </reference>
    <reference>
      <citation>UCSF Human Research Protection Program. The Level of Review and Minimal Risk. Available at: https://irb.ucsf.edu/levels-review#Category-2-Blood-sampling-limited-amounts. Last accessed 4 Jan 2023.</citation>
    </reference>
    <reference>
      <citation>Howie SR. Blood sample volumes in child health research: review of safe limits. Bull World Health Organ. 2011 Jan 1;89(1):46-53. doi: 10.2471/BLT.10.080010. Epub 2010 Sep 10.</citation>
      <PMID>21346890</PMID>
    </reference>
    <verification_date>August 2023</verification_date>
    <study_first_submitted>July 28, 2023</study_first_submitted>
    <study_first_submitted_qc>August 9, 2023</study_first_submitted_qc>
    <study_first_posted type="Actual">August 14, 2023</study_first_posted>
    <last_update_submitted>August 9, 2023</last_update_submitted>
    <last_update_submitted_qc>August 9, 2023</last_update_submitted_qc>
    <last_update_posted type="Actual">August 14, 2023</last_update_posted>
    <responsible_party>
      <responsible_party_type>Sponsor</responsible_party_type>
    </responsible_party>
    <condition_browse>
      <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
      <mesh_term>Tuberculosis</mesh_term>
    </condition_browse>
    <patient_data>
      <sharing_ipd>No</sharing_ipd>
    </patient_data>
    <!-- Results have not yet been posted for this study                                          -->
  </clinical_study>
  
  
text: 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/NCT05989802
  org study id: R01HL169449
  secondary id: U01AI152087
  secondary id: 7200AA22RFA00004
  nct id: NCT05989802
  lead sponsor: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  collaborator: 
  has dmc: No
  is fda regulated drug: No
  is fda regulated device: Yes
  is unapproved device: Yes
  is us export: Yes
  Every year there are an estimated 230,000 childhood deaths from TB. There is an urgent need
        for novel tests for TB diagnosis in children under 15 years. The Rapid Research in
        Diagnostics Development for TB Network (R2D2 Kids) and the Assessing Diagnostics at
        Point-of-care for Tuberculosis in children (ADAPT for Kids) studies seek to reduce the burden
        of TB worldwide by evaluating faster, simpler, and less expensive TB triage and diagnostic
        tests for use in children.
  The Rapid Research in Diagnostics Development for TB Network (R2D2 Kids) and the Assessing
        Diagnostics at Point-of-care for Tuberculosis in children (ADAPT for Kids) studies will
        rigorously assess promising, point-of-care (POC) TB diagnostic tests in clinical studies
        conducted among children at settings of intended use. There is an urgent need for novel tests
        for TB diagnosis in children under 15 years because of the challenge of obtaining sputum
        samples from children and the low sputum bacillary burden among children with TB even when a
        sample is obtained. This creates delays in diagnosis and treatment initiation, and is a major
        contributor to the 230,000 childhood deaths from TB each year. Therefore, a non-sputum
        biomarker-based test has been ranked among the highest priority target product profiles for
        new TB diagnostics. If inexpensive and simple to perform, such a diagnostic tool could have
        significant impact by facilitating rapid diagnosis and TB treatment in children. The studies
        will evaluate the sensitivity and specificity of novel diagnostic tests in children in
        reference to NIH consensus definitions for childhood TB. In addition, the usability and
        acceptability of the novel TB diagnostic tests will be assessed through direct observations
        and surveys of routine health workers.
  allocation: N/A
  intervention model: Single Group Assignment
  primary purpose: Diagnostic
  masking: None (Open Label)
  measure: Proportion with positive index test result among participants with tuberculosis (TB)
  time frame: 2 years
  description: Sensitivity - Number with positive index test result/(Number with positive or negative index t test result) among participants with TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)
  measure: Proportion with negative index test result among participants without tuberculosis (TB)
  time frame: 2 years
  description: Specificity - Number with negative index test results/(Number with positive or negative index t test result) among participants without TB. TB will be defined based on a microbiological reference standard (sputum mycobacterial culture results)
  arm group label: Evaluation of various novel TB triage and diagnostic tests
  arm group type: Experimental
  description: The investigators will conduct evaluation of novel TB triage and diagnostic tests in a cohort of children with presumed TB. The investigators aim to enroll 250 participants per year at each of three enrollment sites for evaluation of various novel TB triage and diagnostic tests and 30 health workers to assess test usability. Novel test evaluations will be conducted on a rolling basis as new tests ready for field evaluation are identified.
  intervention type: Diagnostic Test
  intervention name: Oral swab molecular testing
  description: Swab-based testing provides a non-invasive approach to collect respiratory specimens for TB testing. Data in adults suggests that swab-based testing could be valuable when sputum collection is not feasible or available.
  arm group label: Evaluation of various novel TB triage and diagnostic tests
  intervention type: Diagnostic Test
  intervention name: Automated Cough Sound Analysis
  description: Cough sounds can be collected through a mobile phone and tablet, and then analyzed with machine learning algorithms to predict TB.
  arm group label: Evaluation of various novel TB triage and diagnostic tests
  intervention type: Diagnostic Test
  intervention name: Automated Lung Sound Analysis
  description: Lung sounds can be collected with a non-invasive digital stethoscope, and then saved on a tablet or phone and analyzed by machine learning algorithms to predict TB.
  arm group label: Evaluation of various novel TB triage and diagnostic tests
  intervention type: Other
  intervention name: Chest X Ray Computer Aided Detection
  description: Several artificial intelligence algorithms have been developed to predict TB, though this has not yet been validated in children.
  arm group label: Evaluation of various novel TB triage and diagnostic tests
  other name: Artificial Intelligence algorithm
  criteria: 
  gender: All
  minimum age: N/A
  maximum age: 65 Years
  healthy volunteers: Accepts Healthy Volunteers
  last name: Adithya Cattamanchi, MD, MAS
  role: Principal Investigator
  affiliation: University of California, Irvine
  last name: Nilesh Bhatt
  role: Principal Investigator
  affiliation: Elizabeth Glazer Pediatric AIDS Foundation
  last name: Devan Jaganath, MD
  phone: 415-514-4692
  email: devan.jaganath@ucsf.edu
  last name: Brittney Sweetser, MPH
  email: bsweetse@hs.uci.edu
  facility: 
  contact: 
  facility: 
  contact: 
  facility: 
  contact: 
  country: Mozambique
  country: South Africa
  country: Uganda
  citation: Perez-Velez CM, Marais BJ. Tuberculosis in children. N Engl J Med. 2012 Jul 26;367(4):348-61. doi: 10.1056/NEJMra1008049. No abstract available.
  PMID: 22830465
  citation: World Health Organization. Roadmap towards ending TB in children and adolescents. Geneva: World Health Organization, 2018. Available at: https://www.who.int/tb/publications/2018/tb-childhoodroadmap/en/. Last accessed 1 June 2022.
  citation: WHO. High-priority target product profiles for new tuberculosis diagnostics: Report of a consensus meeting. Geneva, Switzerland. Available at: http://www.who.int/tb/publications/tpp_report/en/, 2014.
  citation: Graham SM, Cuevas LE, Jean-Philippe P, Browning R, Casenghi M, Detjen AK, Gnanashanmugam D, Hesseling AC, Kampmann B, Mandalakas A, Marais BJ, Schito M, Spiegel HM, Starke JR, Worrell C, Zar HJ. Clinical Case Definitions for Classification of Intrathoracic Tuberculosis in Children: An Update. Clin Infect Dis. 2015 Oct 15;61Suppl 3(Suppl 3):S179-87. doi: 10.1093/cid/civ581.
  PMID: 26409281
  citation: World Health Organization. Global Tuberculosis Report 2021. Geneva: World Health Organization, 2021.
  citation: World Health Organization. Roadmap towards ending TB in children and adolescents. Geneva: World Health Organization, 2018.
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  responsible party type: Sponsor
  mesh term: Tuberculosis
  sharing ipd: No