Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post-COVID-19 Condition: Protocol for an Observational Study.

Journal: JMIR research protocols
PMID:

Abstract

BACKGROUND: Post-COVID-19 condition is emerging as a new epidemic, characterized by the persistence of COVID-19 symptoms beyond 3 months, and is anticipated to substantially alter the lives of millions of people globally. Patients with severe episodes of COVID-19 are significantly more likely to be hospitalized in the following months. The pathophysiological mechanisms for delayed complications are still poorly understood, with a dissociation seen between ongoing symptoms and objective measures of cardiopulmonary health. COVID-19 is anticipated to alter the long-term trajectory of many chronic cardiovascular and pulmonary diseases, which are common among those at risk of severe disease.

Authors

  • Jenny Mathew
    Aidar Health, Inc, Columbia, MD, United States.
  • Jaclyn A Pagliaro
    Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, United States.
  • Sathyanarayanan Elumalai
    Aidar Health, Inc, Columbia, MD, United States.
  • Lauren K Wash
    Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, United States.
  • Ka Ly
    Clinical Informatics, Providence VA Medical Center, Providence, RI, United States.
  • Alison J Leibowitz
    Center for Healthcare Organization and Implementation Research (CHOIR), VA Bedford Healthcare System, Bedford, MA, United States.
  • Varsha G Vimalananda
    Bedford Veterans Affairs Medical Center, Center for Healthcare Organization and Implementation Research, Bedford, MA, United States.