<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/NCT04425720</url>
  </required_header>
  <id_info>
    <org_study_id>2020-11824</org_study_id>
    <nct_id>NCT04425720</nct_id>
  </id_info>
  <brief_title>Use of Remote Monitoring for COVID-19 Patient</brief_title>
  <acronym>RPM</acronym>
  <official_title>Use of Remote Patient Monitoring (RPM) Platform for COVID-19 Patient</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>Montefiore Medical Center</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>Montefiore Medical Center</source>
  <oversight_info>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>Yes</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The central hypothesis motivating this study is that remote patient monitoring (RPM) of&#xD;
      infectious disease patients can efficiently facilitate self-isolation. Additionally, RPM can&#xD;
      assist in more rapid identification of patients at risk, facilitate detection of patient&#xD;
      deterioration, and enable early interventions, all of which play a vital role in resource&#xD;
      utilization and outcomes.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Aim-I To develop and test a clinical care pathway that can be utilized in similar epidemic&#xD;
      conditions in the future. To study this aim, the investigators will be using the COVID-19&#xD;
      medical surge as a condition to evaluate the framework of delivering care through remote&#xD;
      patient monitoring. The success of this care delivery model will be evaluated on ease of&#xD;
      model implementation, patient satisfaction, clinical outcomes, and the utilization of shared&#xD;
      decision making.&#xD;
&#xD;
      Aim-II To evaluate remote patient monitoring for appropriate resource utilization in epidemic&#xD;
      and pandemic conditions. To evaluate this aim, the investigators plan to compare the&#xD;
      emergency department (ED) visits and in-patient admission of patients with and without&#xD;
      wearable remote patient monitoring devices. Additionally, the investigators will compare the&#xD;
      number of patients that required critical interventions (mechanical ventilation and ECMO)&#xD;
      during the hospital stay.&#xD;
&#xD;
      Aim III To evaluate the utilization of wearable technology for upfront predictions of&#xD;
      patients that would require in-patient admissions. To evaluate this aim, patients who are&#xD;
      diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a&#xD;
      wearable device, and shared-clinical decisions will be made based on the monitored data and&#xD;
      patient diary. The comparison group will be patients undergoing routine standard of care at&#xD;
      the hospital. ED visits, in-patient hospital admissions, and patient satisfaction will be the&#xD;
      outcome measures compared between the two groups.&#xD;
&#xD;
      Aim IV To evaluate the association between early identification of critical, abnormal vital&#xD;
      signs and the prevention of serious adverse events. To evaluate this aim, patients in the&#xD;
      monitored group and non-monitored group will be compared for ED visits, in-patient&#xD;
      admissions, length of hospital stay, and serious adverse events.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">September 1, 2020</start_date>
  <completion_date type="Actual">December 10, 2021</completion_date>
  <primary_completion_date type="Actual">February 10, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Supportive Care</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Number of Monitored Versus Non-Monitored In-patient Admission</measure>
    <time_frame>14 days</time_frame>
    <description>compare the number of in-patient admissions between the monitored and non-monitored patients</description>
  </primary_outcome>
  <primary_outcome>
    <measure>How Many Subjects Needed to Visit the Emergency Department</measure>
    <time_frame>14 days</time_frame>
    <description>compare the number of participants who visited Emergency Department between both arms</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Length of Stay</measure>
    <time_frame>14 days</time_frame>
    <description>Length of stay of subject if hospitalized</description>
  </primary_outcome>
  <primary_outcome>
    <measure>How Many Completed the Patient Satisfaction Survey</measure>
    <time_frame>14 days</time_frame>
    <description>Survey given to patients who were monitored to ask about satisfaction with the program. A research associate calls enrolled subjects to determine their opinions having participated in the program.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>How Many Subjects End up Requiring Mechanical Ventilation and ECMO</measure>
    <time_frame>14 days</time_frame>
    <description>How often does a subject end up getting mechanical ventilation or ECMO</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Serious Adverse Events</measure>
    <time_frame>14 days</time_frame>
    <description>events requiring extended hospital stay</description>
  </primary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">300</enrollment>
  <condition>COVID</condition>
  <arm_group>
    <arm_group_label>Standard Of Care</arm_group_label>
    <arm_group_type>Active Comparator</arm_group_type>
    <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Monitored</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary</description>
  </arm_group>
  <intervention>
    <intervention_type>Device</intervention_type>
    <intervention_name>LifeSignals Biosensor 1AX*</intervention_name>
    <description>Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
    <arm_group_label>Monitored</arm_group_label>
  </intervention>
  <intervention>
    <intervention_type>Other</intervention_type>
    <intervention_name>Standard of Care</intervention_name>
    <description>This group will be treated based on standard of care at our institution.</description>
    <arm_group_label>Standard Of Care</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Covid-19 positive patient&#xD;
&#xD;
          -  Does not require in-patient admission&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Allergic to sensor patch&#xD;
&#xD;
          -  Has implanted pacemaker&#xD;
&#xD;
          -  Has excessive sweating&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>90 Years</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Jonathan Leff, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>Montefiore Medical Center</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>Montefiore Medical Center</name>
      <address>
        <city>Bronx</city>
        <state>New York</state>
        <zip>10467</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <reference>
    <citation>Sohrabi C, Alsafi Z, O'Neill N, Khan M, Kerwan A, Al-Jabir A, Iosifidis C, Agha R. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). Int J Surg. 2020 Apr;76:71-76. doi: 10.1016/j.ijsu.2020.02.034. Epub 2020 Feb 26. Erratum In: Int J Surg. 2020 May;77:217.</citation>
    <PMID>32112977</PMID>
  </reference>
  <reference>
    <citation>Wilder-Smith A, Chiew CJ, Lee VJ. Can we contain the COVID-19 outbreak with the same measures as for SARS? Lancet Infect Dis. 2020 May;20(5):e102-e107. doi: 10.1016/S1473-3099(20)30129-8. Epub 2020 Mar 5.</citation>
    <PMID>32145768</PMID>
  </reference>
  <reference>
    <citation>Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 Feb 15;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5. Epub 2020 Jan 24. Erratum In: Lancet. 2020 Jan 30;:</citation>
    <PMID>31986264</PMID>
  </reference>
  <reference>
    <citation>Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585. Erratum In: JAMA. 2021 Mar 16;325(11):1113.</citation>
    <PMID>32031570</PMID>
  </reference>
  <reference>
    <citation>Liu K, Fang YY, Deng Y, Liu W, Wang MF, Ma JP, Xiao W, Wang YN, Zhong MH, Li CH, Li GC, Liu HG. Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province. Chin Med J (Engl). 2020 May 5;133(9):1025-1031. doi: 10.1097/CM9.0000000000000744.</citation>
    <PMID>32044814</PMID>
  </reference>
  <reference>
    <citation>Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020 Apr 7;323(13):1239-1242. doi: 10.1001/jama.2020.2648. No abstract available.</citation>
    <PMID>32091533</PMID>
  </reference>
  <reference>
    <citation>Grech V. Unknown unknowns - COVID-19 and potential global mortality. Early Hum Dev. 2020 May;144:105026. doi: 10.1016/j.earlhumdev.2020.105026. Epub 2020 Mar 31.</citation>
    <PMID>32247898</PMID>
  </reference>
  <reference>
    <citation>Goh KJ, Choong MC, Cheong EH, Kalimuddin S, Duu Wen S, Phua GC, Chan KS, Haja Mohideen S. Rapid Progression to Acute Respiratory Distress Syndrome: Review of Current Understanding of Critical Illness from Coronavirus Disease 2019 (COVID-19) Infection. Ann Acad Med Singap. 2020 Mar 16;49(3):108-118.</citation>
    <PMID>32200400</PMID>
  </reference>
  <reference>
    <citation>Liu V, Kipnis P, Rizk NW, Escobar GJ. Adverse outcomes associated with delayed intensive care unit transfers in an integrated healthcare system. J Hosp Med. 2012 Mar;7(3):224-30. doi: 10.1002/jhm.964. Epub 2011 Oct 28.</citation>
    <PMID>22038879</PMID>
  </reference>
  <reference>
    <citation>Mardini L, Lipes J, Jayaraman D. Adverse outcomes associated with delayed intensive care consultation in medical and surgical inpatients. J Crit Care. 2012 Dec;27(6):688-93. doi: 10.1016/j.jcrc.2012.04.011. Epub 2012 Jun 12.</citation>
    <PMID>22699035</PMID>
  </reference>
  <reference>
    <citation>Mokart D, Lambert J, Schnell D, Fouche L, Rabbat A, Kouatchet A, Lemiale V, Vincent F, Lengline E, Bruneel F, Pene F, Chevret S, Azoulay E. Delayed intensive care unit admission is associated with increased mortality in patients with cancer with acute respiratory failure. Leuk Lymphoma. 2013 Aug;54(8):1724-9. doi: 10.3109/10428194.2012.753446. Epub 2012 Dec 26.</citation>
    <PMID>23185988</PMID>
  </reference>
  <reference>
    <citation>Cheng PK, Wong DA, Tong LK, Ip SM, Lo AC, Lau CS, Yeung EY, Lim WW. Viral shedding patterns of coronavirus in patients with probable severe acute respiratory syndrome. Lancet. 2004 May 22;363(9422):1699-700. doi: 10.1016/S0140-6736(04)16255-7.</citation>
    <PMID>15158632</PMID>
  </reference>
  <reference>
    <citation>Weiss P, Murdoch DR. Clinical course and mortality risk of severe COVID-19. Lancet. 2020 Mar 28;395(10229):1014-1015. doi: 10.1016/S0140-6736(20)30633-4. Epub 2020 Mar 17. No abstract available.</citation>
    <PMID>32197108</PMID>
  </reference>
  <reference>
    <citation>Tian S, Hu W, Niu L, Liu H, Xu H, Xiao SY. Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer. J Thorac Oncol. 2020 May;15(5):700-704. doi: 10.1016/j.jtho.2020.02.010. Epub 2020 Feb 28.</citation>
    <PMID>32114094</PMID>
  </reference>
  <reference>
    <citation>Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020 Apr 30;382(18):1708-1720. doi: 10.1056/NEJMoa2002032. Epub 2020 Feb 28.</citation>
    <PMID>32109013</PMID>
  </reference>
  <reference>
    <citation>Bonow RO, Fonarow GC, O'Gara PT, Yancy CW. Association of Coronavirus Disease 2019 (COVID-19) With Myocardial Injury and Mortality. JAMA Cardiol. 2020 Jul 1;5(7):751-753. doi: 10.1001/jamacardio.2020.1105. No abstract available.</citation>
    <PMID>32219362</PMID>
  </reference>
  <reference>
    <citation>Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020 Mar 28;395(10229):1054-1062. doi: 10.1016/S0140-6736(20)30566-3. Epub 2020 Mar 11. Erratum In: Lancet. 2020 Mar 28;395(10229):1038. Lancet. 2020 Mar 28;395(10229):1038.</citation>
    <PMID>32171076</PMID>
  </reference>
  <reference>
    <citation>Hu SB, Wong DJ, Correa A, Li N, Deng JC. Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model. PLoS One. 2016 Aug 17;11(8):e0161401. doi: 10.1371/journal.pone.0161401. eCollection 2016.</citation>
    <PMID>27532679</PMID>
  </reference>
  <reference>
    <citation>Yancy CW. COVID-19 and African Americans. JAMA. 2020 May 19;323(19):1891-1892. doi: 10.1001/jama.2020.6548. No abstract available.</citation>
    <PMID>32293639</PMID>
  </reference>
  <reference>
    <citation>Izmailova ES, Wagner JA, Perakslis ED. Wearable Devices in Clinical Trials: Hype and Hypothesis. Clin Pharmacol Ther. 2018 Jul;104(1):42-52. doi: 10.1002/cpt.966. Epub 2018 Apr 2.</citation>
    <PMID>29205294</PMID>
  </reference>
  <reference>
    <citation>Menta AK, Subbiah IM, Subbiah V. Bringing wearable devices into oncology practice: fitting smart technology in the clinic. Discov Med. 2018 Dec;26(145):261-270.</citation>
    <PMID>30695675</PMID>
  </reference>
  <reference>
    <citation>Ip JE. Wearable Devices for Cardiac Rhythm Diagnosis and Management. JAMA. 2019 Jan 29;321(4):337-338. doi: 10.1001/jama.2018.20437. No abstract available.</citation>
    <PMID>30633301</PMID>
  </reference>
  <reference>
    <citation>Shan R, Sarkar S, Martin SS. Digital health technology and mobile devices for the management of diabetes mellitus: state of the art. Diabetologia. 2019 Jun;62(6):877-887. doi: 10.1007/s00125-019-4864-7. Epub 2019 Apr 8.</citation>
    <PMID>30963188</PMID>
  </reference>
  <reference>
    <citation>Radin JM, Wineinger NE, Topol EJ, Steinhubl SR. Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. Lancet Digit Health. 2020 Feb;2(2):e85-e93. doi: 10.1016/S2589-7500(19)30222-5. Epub 2020 Jan 16.</citation>
    <PMID>33334565</PMID>
  </reference>
  <verification_date>January 2022</verification_date>
  <study_first_submitted>June 2, 2020</study_first_submitted>
  <study_first_submitted_qc>June 8, 2020</study_first_submitted_qc>
  <study_first_posted type="Actual">June 11, 2020</study_first_posted>
  <results_first_submitted>November 4, 2021</results_first_submitted>
  <results_first_submitted_qc>November 18, 2021</results_first_submitted_qc>
  <results_first_posted type="Actual">November 19, 2021</results_first_posted>
  <last_update_submitted>January 20, 2022</last_update_submitted>
  <last_update_submitted_qc>January 20, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">January 24, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Sponsor</responsible_party_type>
  </responsible_party>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Study Protocol and Statistical Analysis Plan</document_type>
      <document_has_protocol>Yes</document_has_protocol>
      <document_has_icf>No</document_has_icf>
      <document_has_sap>Yes</document_has_sap>
      <document_date>July 8, 2020</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/20/NCT04425720/Prot_SAP_000.pdf</document_url>
    </provided_document>
  </provided_document_section>

  <clinical_results>

    <participant_flow>
      <group_list>
        <group group_id="P1">
          <title>Standard Of Care</title>
          <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
        </group>
        <group group_id="P2">
          <title>Monitored</title>
          <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
        </group>
      </group_list>
      <period_list>
        <period>
          <title>Overall Study</title>
          <milestone_list>
            <milestone>
              <title>STARTED</title>
              <participants_list>
                <participants group_id="P1" count="150"/>
                <participants group_id="P2" count="150"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="150"/>
                <participants group_id="P2" count="130"/>
              </participants_list>
            </milestone>
            <milestone>
              <title>NOT COMPLETED</title>
              <participants_list>
                <participants group_id="P1" count="0"/>
                <participants group_id="P2" count="20"/>
              </participants_list>
            </milestone>
          </milestone_list>
          <drop_withdraw_reason_list>
            <drop_withdraw_reason>
              <title>Withdrawal by Subject</title>
              <participants_list>
                <participants group_id="P1" count="0"/>
                <participants group_id="P2" count="20"/>
              </participants_list>
            </drop_withdraw_reason>
          </drop_withdraw_reason_list>
        </period>
      </period_list>
    </participant_flow>

    <baseline>
      <group_list>
        <group group_id="B1">
          <title>Standard Of Care</title>
          <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
        </group>
        <group group_id="B2">
          <title>Monitored</title>
          <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
        </group>
        <group group_id="B3">
          <title>Total</title>
          <description>Total of all reporting groups</description>
        </group>
      </group_list>
      <analyzed_list>
        <analyzed>
          <units>Participants</units>
          <scope>Overall</scope>
          <count_list>
            <count group_id="B1" value="150"/>
            <count group_id="B2" value="130"/>
            <count group_id="B3" value="280"/>
          </count_list>
        </analyzed>
      </analyzed_list>
      <measure_list>
        <measure>
          <title>Age, Customized</title>
          <units>years</units>
          <param>Mean</param>
          <dispersion>Inter-Quartile Range</dispersion>
          <class_list>
            <class>
              <title>Average Age in Years</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="65.50" lower_limit="44" upper_limit="73"/>
                    <measurement group_id="B2" value="64" lower_limit="58" upper_limit="74"/>
                    <measurement group_id="B3" value="65" lower_limit="53" upper_limit="74"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Sex: Female, Male</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Female</title>
                  <measurement_list>
                    <measurement group_id="B1" value="82"/>
                    <measurement group_id="B2" value="88"/>
                    <measurement group_id="B3" value="170"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Male</title>
                  <measurement_list>
                    <measurement group_id="B1" value="68"/>
                    <measurement group_id="B2" value="42"/>
                    <measurement group_id="B3" value="110"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Ethnicity (NIH/OMB)</title>
          <units>Participants</units>
          <param>Count of Participants</param>
          <class_list>
            <class>
              <category_list>
                <category>
                  <title>Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="90"/>
                    <measurement group_id="B2" value="89"/>
                    <measurement group_id="B3" value="179"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Not Hispanic or Latino</title>
                  <measurement_list>
                    <measurement group_id="B1" value="60"/>
                    <measurement group_id="B2" value="41"/>
                    <measurement group_id="B3" value="101"/>
                  </measurement_list>
                </category>
                <category>
                  <title>Unknown or Not Reported</title>
                  <measurement_list>
                    <measurement group_id="B1" value="0"/>
                    <measurement group_id="B2" value="0"/>
                    <measurement group_id="B3" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
        <measure>
          <title>Region of Enrollment</title>
          <units>participants</units>
          <param>Number</param>
          <class_list>
            <class>
              <title>United States</title>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="B1" value="150"/>
                    <measurement group_id="B2" value="130"/>
                    <measurement group_id="B3" value="280"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </measure_list>
    </baseline>

    <outcome_list>
      <outcome>
        <type>Primary</type>
        <title>Number of Monitored Versus Non-Monitored In-patient Admission</title>
        <description>compare the number of in-patient admissions between the monitored and non-monitored patients</description>
        <time_frame>14 days</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Standard Of Care</title>
            <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
          </group>
          <group group_id="O2">
            <title>Monitored</title>
            <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
          </group>
        </group_list>
        <measure>
          <title>Number of Monitored Versus Non-Monitored In-patient Admission</title>
          <description>compare the number of in-patient admissions between the monitored and non-monitored patients</description>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="150"/>
                <count group_id="O2" value="130"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="8"/>
                    <measurement group_id="O2" value="9"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>How Many Subjects Needed to Visit the Emergency Department</title>
        <description>compare the number of participants who visited Emergency Department between both arms</description>
        <time_frame>14 days</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Standard Of Care</title>
            <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
          </group>
          <group group_id="O2">
            <title>Monitored</title>
            <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
          </group>
        </group_list>
        <measure>
          <title>How Many Subjects Needed to Visit the Emergency Department</title>
          <description>compare the number of participants who visited Emergency Department between both arms</description>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="150"/>
                <count group_id="O2" value="130"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="14"/>
                    <measurement group_id="O2" value="12"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Length of Stay</title>
        <description>Length of stay of subject if hospitalized</description>
        <time_frame>14 days</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Standard Of Care</title>
            <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
          </group>
          <group group_id="O2">
            <title>Monitored</title>
            <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
          </group>
        </group_list>
        <measure>
          <title>Length of Stay</title>
          <description>Length of stay of subject if hospitalized</description>
          <units>days</units>
          <param>Median</param>
          <dispersion>Inter-Quartile Range</dispersion>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="150"/>
                <count group_id="O2" value="130"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="7" lower_limit="1" upper_limit="14"/>
                    <measurement group_id="O2" value="7" lower_limit="4.5" upper_limit="9.5"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>How Many Completed the Patient Satisfaction Survey</title>
        <description>Survey given to patients who were monitored to ask about satisfaction with the program. A research associate calls enrolled subjects to determine their opinions having participated in the program.</description>
        <time_frame>14 days</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Monitored</title>
            <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
          </group>
        </group_list>
        <measure>
          <title>How Many Completed the Patient Satisfaction Survey</title>
          <description>Survey given to patients who were monitored to ask about satisfaction with the program. A research associate calls enrolled subjects to determine their opinions having participated in the program.</description>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="130"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="84"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>How Many Subjects End up Requiring Mechanical Ventilation and ECMO</title>
        <description>How often does a subject end up getting mechanical ventilation or ECMO</description>
        <time_frame>14 days</time_frame>
        <population>As only those monitored were surveyed, the following results only reflect one of the arms. There is no reason to conduct a satisfaction survey on individuals who received standard of care because they would not be aware of the monitoring option.</population>
        <group_list>
          <group group_id="O1">
            <title>Monitored</title>
            <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
          </group>
        </group_list>
        <measure>
          <title>How Many Subjects End up Requiring Mechanical Ventilation and ECMO</title>
          <description>How often does a subject end up getting mechanical ventilation or ECMO</description>
          <population>As only those monitored were surveyed, the following results only reflect one of the arms. There is no reason to conduct a satisfaction survey on individuals who received standard of care because they would not be aware of the monitoring option.</population>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="130"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="0"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
      <outcome>
        <type>Primary</type>
        <title>Serious Adverse Events</title>
        <description>events requiring extended hospital stay</description>
        <time_frame>14 days</time_frame>
        <group_list>
          <group group_id="O1">
            <title>Standard Of Care</title>
            <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
          </group>
          <group group_id="O2">
            <title>Monitored</title>
            <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
          </group>
        </group_list>
        <measure>
          <title>Serious Adverse Events</title>
          <description>events requiring extended hospital stay</description>
          <units>Participants</units>
          <param>Count of Participants</param>
          <analyzed_list>
            <analyzed>
              <units>Participants</units>
              <scope>Measure</scope>
              <count_list>
                <count group_id="O1" value="150"/>
                <count group_id="O2" value="130"/>
              </count_list>
            </analyzed>
          </analyzed_list>
          <class_list>
            <class>
              <category_list>
                <category>
                  <measurement_list>
                    <measurement group_id="O1" value="2"/>
                    <measurement group_id="O2" value="1"/>
                  </measurement_list>
                </category>
              </category_list>
            </class>
          </class_list>
        </measure>
      </outcome>
    </outcome_list>

    <reported_events>
      <time_frame>Up to 17 days after admission</time_frame>
      <desc>As this is a novel pandemic, there are limited resources available for accurate identification of patients at high risk for respiratory failure and other adverse events. Subjects who were repeatedly admitted into the hospital will count as an adverse event. Death will count as a serious adverse event.</desc>
      <group_list>
        <group group_id="E1">
          <title>Standard Of Care</title>
          <description>Patients without wearable monitoring technology undergoing routine standard of care at the hospital.&#xD;
Standard of Care: This group will be treated based on standard of care at our institution.</description>
        </group>
        <group group_id="E2">
          <title>Monitored</title>
          <description>Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary&#xD;
LifeSignals Biosensor 1AX*: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.</description>
        </group>
      </group_list>
      <serious_events>
        <default_assessment>Systematic Assessment</default_assessment>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, all-cause mortality</sub_title>
                <counts group_id="E1" subjects_affected="2" subjects_at_risk="150"/>
                <counts group_id="E2" subjects_affected="1" subjects_at_risk="130"/>
              </event>
              <event>
                <sub_title>Total, serious adverse events</sub_title>
                <counts group_id="E1" subjects_affected="2" subjects_at_risk="150"/>
                <counts group_id="E2" subjects_affected="1" subjects_at_risk="130"/>
              </event>
            </event_list>
          </category>
          <category>
            <title>Respiratory, thoracic and mediastinal disorders</title>
            <event_list>
              <event>
                <sub_title>Death</sub_title>
                <counts group_id="E1" events="2" subjects_affected="2" subjects_at_risk="150"/>
                <counts group_id="E2" events="1" subjects_affected="1" subjects_at_risk="130"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </serious_events>
      <other_events>
        <frequency_threshold>1</frequency_threshold>
        <default_assessment>Systematic Assessment</default_assessment>
        <category_list>
          <category>
            <title>Total</title>
            <event_list>
              <event>
                <sub_title>Total, other adverse events</sub_title>
                <counts group_id="E1" subjects_affected="8" subjects_at_risk="150"/>
                <counts group_id="E2" subjects_affected="9" subjects_at_risk="130"/>
              </event>
            </event_list>
          </category>
          <category>
            <title>Infections and infestations</title>
            <event_list>
              <event>
                <sub_title>Repeated Admission</sub_title>
                <description>Subjects who were repeatedly admitted into the hospital</description>
                <counts group_id="E1" events="8" subjects_affected="8" subjects_at_risk="150"/>
                <counts group_id="E2" events="9" subjects_affected="9" subjects_at_risk="130"/>
              </event>
            </event_list>
          </category>
        </category_list>
      </other_events>
    </reported_events>

    <certain_agreements>
      <pi_employee>Principal Investigators are NOT employed by the organization sponsoring the study.</pi_employee>
      <restrictive_agreement>There is NOT an agreement between Principal Investigators and the Sponsor (or its agents) that restricts the PI's rights to discuss or publish trial results after the trial is completed. </restrictive_agreement>
    </certain_agreements>
    <point_of_contact>
      <name_or_title>Dr. Jonathan Leff</name_or_title>
      <organization>Montefiore Medical Center</organization>
      <phone>7189204316</phone>
      <email>jleff@montefiore.org</email>
    </point_of_contact>
  </clinical_results>
</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/NCT04425720
org study id: 2020-11824
nct id: NCT04425720
lead sponsor: 
is fda regulated drug: No
is fda regulated device: Yes
The central hypothesis motivating this study is that remote patient monitoring (RPM) of
      infectious disease patients can efficiently facilitate self-isolation. Additionally, RPM can
      assist in more rapid identification of patients at risk, facilitate detection of patient
      deterioration, and enable early interventions, all of which play a vital role in resource
      utilization and outcomes.
Aim-I To develop and test a clinical care pathway that can be utilized in similar epidemic
      conditions in the future. To study this aim, the investigators will be using the COVID-19
      medical surge as a condition to evaluate the framework of delivering care through remote
      patient monitoring. The success of this care delivery model will be evaluated on ease of
      model implementation, patient satisfaction, clinical outcomes, and the utilization of shared
      decision making.

      Aim-II To evaluate remote patient monitoring for appropriate resource utilization in epidemic
      and pandemic conditions. To evaluate this aim, the investigators plan to compare the
      emergency department (ED) visits and in-patient admission of patients with and without
      wearable remote patient monitoring devices. Additionally, the investigators will compare the
      number of patients that required critical interventions (mechanical ventilation and ECMO)
      during the hospital stay.

      Aim III To evaluate the utilization of wearable technology for upfront predictions of
      patients that would require in-patient admissions. To evaluate this aim, patients who are
      diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a
      wearable device, and shared-clinical decisions will be made based on the monitored data and
      patient diary. The comparison group will be patients undergoing routine standard of care at
      the hospital. ED visits, in-patient hospital admissions, and patient satisfaction will be the
      outcome measures compared between the two groups.

      Aim IV To evaluate the association between early identification of critical, abnormal vital
      signs and the prevention of serious adverse events. To evaluate this aim, patients in the
      monitored group and non-monitored group will be compared for ED visits, in-patient
      admissions, length of hospital stay, and serious adverse events.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Supportive Care
masking: None (Open Label)
measure: Number of Monitored Versus Non-Monitored In-patient Admission
time frame: 14 days
description: compare the number of in-patient admissions between the monitored and non-monitored patients
measure: How Many Subjects Needed to Visit the Emergency Department
time frame: 14 days
description: compare the number of participants who visited Emergency Department between both arms
measure: Length of Stay
time frame: 14 days
description: Length of stay of subject if hospitalized
measure: How Many Completed the Patient Satisfaction Survey
time frame: 14 days
description: Survey given to patients who were monitored to ask about satisfaction with the program. A research associate calls enrolled subjects to determine their opinions having participated in the program.
measure: How Many Subjects End up Requiring Mechanical Ventilation and ECMO
time frame: 14 days
description: How often does a subject end up getting mechanical ventilation or ECMO
measure: Serious Adverse Events
time frame: 14 days
description: events requiring extended hospital stay
arm group label: Standard Of Care
arm group type: Active Comparator
description: Patients without wearable monitoring technology undergoing routine standard of care at the hospital.
arm group label: Monitored
arm group type: Experimental
description: Patients who are diagnosed with COVID-19 and are undergoing self-quarantine will be closely monitored using a wearable device, and shared-clinical decisions will be made based on the monitored data and patient diary
intervention type: Device
intervention name: LifeSignals Biosensor 1AX*
description: Shared-clinical decisions will be made based on the monitored data and patient diary. Two devices will be used to monitor data, LifeSignals Biosensor 1AX* and a pulse oximeter.
arm group label: Monitored
intervention type: Other
intervention name: Standard of Care
description: This group will be treated based on standard of care at our institution.
arm group label: Standard Of Care
criteria: 
gender: All
minimum age: 18 Years
maximum age: 90 Years
healthy volunteers: No
last name: Jonathan Leff, MD
role: Principal Investigator
affiliation: Montefiore Medical Center
facility: 
country: United States
citation: Sohrabi C, Alsafi Z, O'Neill N, Khan M, Kerwan A, Al-Jabir A, Iosifidis C, Agha R. World Health Organization declares global emergency: A review of the 2019 novel coronavirus (COVID-19). Int J Surg. 2020 Apr;76:71-76. doi: 10.1016/j.ijsu.2020.02.034. Epub 2020 Feb 26. Erratum In: Int J Surg. 2020 May;77:217.
PMID: 32112977
citation: Wilder-Smith A, Chiew CJ, Lee VJ. Can we contain the COVID-19 outbreak with the same measures as for SARS? Lancet Infect Dis. 2020 May;20(5):e102-e107. doi: 10.1016/S1473-3099(20)30129-8. Epub 2020 Mar 5.
PMID: 32145768
citation: Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, Zhang L, Fan G, Xu J, Gu X, Cheng Z, Yu T, Xia J, Wei Y, Wu W, Xie X, Yin W, Li H, Liu M, Xiao Y, Gao H, Guo L, Xie J, Wang G, Jiang R, Gao Z, Jin Q, Wang J, Cao B. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020 Feb 15;395(10223):497-506. doi: 10.1016/S0140-6736(20)30183-5. Epub 2020 Jan 24. Erratum In: Lancet. 2020 Jan 30;:
PMID: 31986264
citation: Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, Wang B, Xiang H, Cheng Z, Xiong Y, Zhao Y, Li Y, Wang X, Peng Z. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020 Mar 17;323(11):1061-1069. doi: 10.1001/jama.2020.1585. Erratum In: JAMA. 2021 Mar 16;325(11):1113.
PMID: 32031570
citation: Liu K, Fang YY, Deng Y, Liu W, Wang MF, Ma JP, Xiao W, Wang YN, Zhong MH, Li CH, Li GC, Liu HG. Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province. Chin Med J (Engl). 2020 May 5;133(9):1025-1031. doi: 10.1097/CM9.0000000000000744.
PMID: 32044814
citation: Wu Z, McGoogan JM. Characteristics of and Important Lessons From the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases From the Chinese Center for Disease Control and Prevention. JAMA. 2020 Apr 7;323(13):1239-1242. doi: 10.1001/jama.2020.2648. No abstract available.
PMID: 32091533
citation: Grech V. Unknown unknowns - COVID-19 and potential global mortality. Early Hum Dev. 2020 May;144:105026. doi: 10.1016/j.earlhumdev.2020.105026. Epub 2020 Mar 31.
PMID: 32247898
citation: Goh KJ, Choong MC, Cheong EH, Kalimuddin S, Duu Wen S, Phua GC, Chan KS, Haja Mohideen S. Rapid Progression to Acute Respiratory Distress Syndrome: Review of Current Understanding of Critical Illness from Coronavirus Disease 2019 (COVID-19) Infection. Ann Acad Med Singap. 2020 Mar 16;49(3):108-118.
PMID: 32200400
citation: Liu V, Kipnis P, Rizk NW, Escobar GJ. Adverse outcomes associated with delayed intensive care unit transfers in an integrated healthcare system. J Hosp Med. 2012 Mar;7(3):224-30. doi: 10.1002/jhm.964. Epub 2011 Oct 28.
PMID: 22038879
citation: Mardini L, Lipes J, Jayaraman D. Adverse outcomes associated with delayed intensive care consultation in medical and surgical inpatients. J Crit Care. 2012 Dec;27(6):688-93. doi: 10.1016/j.jcrc.2012.04.011. Epub 2012 Jun 12.
PMID: 22699035
citation: Mokart D, Lambert J, Schnell D, Fouche L, Rabbat A, Kouatchet A, Lemiale V, Vincent F, Lengline E, Bruneel F, Pene F, Chevret S, Azoulay E. Delayed intensive care unit admission is associated with increased mortality in patients with cancer with acute respiratory failure. Leuk Lymphoma. 2013 Aug;54(8):1724-9. doi: 10.3109/10428194.2012.753446. Epub 2012 Dec 26.
PMID: 23185988
citation: Cheng PK, Wong DA, Tong LK, Ip SM, Lo AC, Lau CS, Yeung EY, Lim WW. Viral shedding patterns of coronavirus in patients with probable severe acute respiratory syndrome. Lancet. 2004 May 22;363(9422):1699-700. doi: 10.1016/S0140-6736(04)16255-7.
PMID: 15158632
citation: Weiss P, Murdoch DR. Clinical course and mortality risk of severe COVID-19. Lancet. 2020 Mar 28;395(10229):1014-1015. doi: 10.1016/S0140-6736(20)30633-4. Epub 2020 Mar 17. No abstract available.
PMID: 32197108
citation: Tian S, Hu W, Niu L, Liu H, Xu H, Xiao SY. Pulmonary Pathology of Early-Phase 2019 Novel Coronavirus (COVID-19) Pneumonia in Two Patients With Lung Cancer. J Thorac Oncol. 2020 May;15(5):700-704. doi: 10.1016/j.jtho.2020.02.010. Epub 2020 Feb 28.
PMID: 32114094
citation: Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020 Apr 30;382(18):1708-1720. doi: 10.1056/NEJMoa2002032. Epub 2020 Feb 28.
PMID: 32109013
citation: Bonow RO, Fonarow GC, O'Gara PT, Yancy CW. Association of Coronavirus Disease 2019 (COVID-19) With Myocardial Injury and Mortality. JAMA Cardiol. 2020 Jul 1;5(7):751-753. doi: 10.1001/jamacardio.2020.1105. No abstract available.
PMID: 32219362
citation: Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, Xiang J, Wang Y, Song B, Gu X, Guan L, Wei Y, Li H, Wu X, Xu J, Tu S, Zhang Y, Chen H, Cao B. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020 Mar 28;395(10229):1054-1062. doi: 10.1016/S0140-6736(20)30566-3. Epub 2020 Mar 11. Erratum In: Lancet. 2020 Mar 28;395(10229):1038. Lancet. 2020 Mar 28;395(10229):1038.
PMID: 32171076
citation: Hu SB, Wong DJ, Correa A, Li N, Deng JC. Prediction of Clinical Deterioration in Hospitalized Adult Patients with Hematologic Malignancies Using a Neural Network Model. PLoS One. 2016 Aug 17;11(8):e0161401. doi: 10.1371/journal.pone.0161401. eCollection 2016.
PMID: 27532679
citation: Yancy CW. COVID-19 and African Americans. JAMA. 2020 May 19;323(19):1891-1892. doi: 10.1001/jama.2020.6548. No abstract available.
PMID: 32293639
citation: Izmailova ES, Wagner JA, Perakslis ED. Wearable Devices in Clinical Trials: Hype and Hypothesis. Clin Pharmacol Ther. 2018 Jul;104(1):42-52. doi: 10.1002/cpt.966. Epub 2018 Apr 2.
PMID: 29205294
citation: Menta AK, Subbiah IM, Subbiah V. Bringing wearable devices into oncology practice: fitting smart technology in the clinic. Discov Med. 2018 Dec;26(145):261-270.
PMID: 30695675
citation: Ip JE. Wearable Devices for Cardiac Rhythm Diagnosis and Management. JAMA. 2019 Jan 29;321(4):337-338. doi: 10.1001/jama.2018.20437. No abstract available.
PMID: 30633301
citation: Shan R, Sarkar S, Martin SS. Digital health technology and mobile devices for the management of diabetes mellitus: state of the art. Diabetologia. 2019 Jun;62(6):877-887. doi: 10.1007/s00125-019-4864-7. Epub 2019 Apr 8.
PMID: 30963188
citation: Radin JM, Wineinger NE, Topol EJ, Steinhubl SR. Harnessing wearable device data to improve state-level real-time surveillance of influenza-like illness in the USA: a population-based study. Lancet Digit Health. 2020 Feb;2(2):e85-e93. doi: 10.1016/S2589-7500(19)30222-5. Epub 2020 Jan 16.
PMID: 33334565
responsible party type: Sponsor
sharing ipd: No
provided document: 
participant flow: 
baseline: 
outcome list: 
reported events: 
certain agreements: 
point of contact: 