dbGaP Study Accession: phs002523
NIH Institute/Center: NINR
RADx Data Program: RADx-rad
DOI: 10.60773/dwzp-am60
Release Date: 11/07/2022
Study Description: The data collection system was extended and improved in using wearables for the early detection of COVID-19 infection. With over 5,000 patients recruited in the original Phase 1 IRB-approved study, the existing algorithms were further optimized, especially on its application in individuals with diverse ethnic backgrounds (Aim 1). This study further integrated and optimized the Personal Health Dashboard (MyPHD) to enable real-time online detection of COVID-19 (Aim 2). MyPHD was deployed on the different concentrated populations including pediatric kidney transplant patients, Pac-12 student athletes, and senior living residents (Aim 3).
Updated Date: 01/17/2024
Principal Investigator: Snyder, Michael P
Has Data Files: No
Study Domain: Biosensor Technologies; Digital Health Applications; Disease Surveillance; Multimodal Surveillance
Data Collection Method: Wearable
Keywords: Predictive Markers; Surveillance Data; Transplant Patients
Study Design: Longitudinal Cohort
Multi-Center Study: No
Data Types: Biosensor; Physical Activity; Questionnaire or Survey
Study Start Date: 12/21/2020
Study End Date: 11/30/2022
Species: Human Data
Estimated Cohort Size: 3700
Study Population Focus: Dialysis Patients; Incarcerated or Institutionalized Populations; Intellectual or Developmental Disabilities; Lower Socioeconomic Status (SES) Populations; Older Adults or Elderly; School Communities; Underserved or Vulnerable Populations
Publication URL: https://pubmed.ncbi.nlm.nih.gov/34189532/; https://pubmed.ncbi.nlm.nih.gov/34845389/
Acknowledgement Statement: This study was supported through funding, 4R01NR020105-02, for the National Institute of Nursing Research (NINR) as part of the RADx-rad program. This work was also supported by gifts from the Flu Lab, as well as departmental funding from the Stanford Genetics department. This study was supported by the Amazon Web Services Diagnostic Development Initiative. The Google Cloud Platform costs were covered by Google for Education academic research and COVID-19 grant awards. The team acknowledges the Stanford Genetics Bioinformatics Service Center (GBSC) for providing the gateway to the SCG cluster, Google Cloud Platform and Amazon Web Services for this research. The Stanford REDCap platform (http://redcap.stanford.edu) was developed and operated by the Stanford Medicine Research IT team. The REDCap platform services at Stanford are subsidized by a) Stanford School of Medicine Research Office, and b) the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through grant UL1TR001085. Approved users should acknowledge the provision of data access by dbGaP for accession phs002523.v1.p1, and the NIH RADx Data Hub. Approved users should also acknowledge the specific version(s) of the dataset(s) obtained from the NIH RADx Data Hub.
Funding Opportunity Announcement (FOA) Number: RFA-OD-20-016
NIH Grant or Contract Number(s): 4R01NR020105-02
Consent/Data Use Limitations: General Research Use