Innovative Support for Patients with SARS COV-2 Infections Registry

Hugo Health is participating in a national collaboration to determine the longitudinal effects of SARSCOV2 among patients who have exhibited symptoms of coronavirus and have been tested within the last month. This collaborative seeks to conduct urgently-needed applied research in a large representative sample of the United States population to address the COVID-19 public health emergency.

  • Aim 1: Determine the longitudinal outcomes of SARS COV-2 infections among different age groups in the US population. Our outcomes include healthcare utilization, clinical events, and physical and mental function and status, including neurocognitive function and fatigue. We will also describe outcomes by age of a sample of patients testing negative for SARS COV-2 who will serve as concurrent controls for those who test positive. We will follow participants for up to 18 months and repeatedly measure outcomes.
  • Aim 2: Determine the independent association of age with outcomes after adjustment for sex, race/ethnicity, presence of specific underlying conditions (e.g. hypertension and diabetes), and other characteristics identified in Aim 1.

Study Design

Prospective Cohort Study

  • We will enroll from two populations:
    • Seeking testing but having a negative result
    • Testing positive, across outpatient (including ED) and inpatient (including ICU)
    • In the analytic phase, will establish cohorts based on clinical severity and assess risks of of outcomes
  • We will enroll a total of 3600 cases and 1200 controls
  • We will use the Hugo platform to provide electronic informed consent, connect to EHR data and other data sources, and collect Patient Reported Outcome Measures (PROMs)

Outcomes

The study will collect outcomes through EHR data connections and subject questionnaires within Hugo.

  • EHR data connections are based on standards and can connect across institutions
    • Connect via EHR portals
    • Can receive electronic data from site data warehouses
  • PROMs are survey based, administered electronically, and can be modified to be focused for longitudinal outcomes of interest
  • Incentive provided within Hugo for subject participation and survey completion

PROMs Review
Variable type Instrument source
(No questions)		 Mechanism to obtain data Frequency for data collection (months)
Sociodemographics CDC PUI Survey 0
Testing information CDC PUI Survey 0
Symptom assessment CDC PUI, case studies Survey 0
SDoH (day 14) CMS/AHC Survey 0
Physical/mental health PROMIS-29, PEG, PHQ, GAD, PTSD Survey 1 | 2 | 3 | 4 | 5 | 6
Cognitive screen PROMIS SF 8a Cognition Survey 1 | 2 | 3 | 4 | 5 | 6
Fatigue screen PROMIS-29, FSS Survey 1 | 2 | 3 | 4 | 5 | 6
Post-infectious seq MMRCDS, CCS Survey 1 | 2 | 3 | 4 | 5 | 6

 

Screening criteria (assessed on Hugo platform prior to enrollment screen):

  1. Adults 18 years or older
  2. Tested for COVID-19 at study-affiliated site
  3. Able to read in English or Spanish
  4. Able to access the internet for future surveys

Analytic Approach
  • Establishing cohorts through clinical severity:
    • SARS-COV2 test negative controls
    • Clinical severity for COVID-19 will be defined between mild, moderate, and severe disease
      • testing positive but without symptoms or with mild symptoms and no functional limitations;
      • testing positive and requiring hospitalization but not ICU stay; and
      • testing positive and requiring an ICU stay (with or without the need for mechanical ventilation)
    • Will assess unadjusted and adjusted incidence/risk of outcomes in these cohorts vs. comparators
  • Aim 1 analyses:
    • Describe prevalence and distribution of symptom type, duration, severity and recovery among participants with SARS-CoV-2 by age (eg.<50 years vs 50-65 years vs >65 years)
    • Compare health status at baseline and follow-up between persons in the same age group who test SARS-CoV-2 positive and negative at initial test
    • Characterize health care utilization (ED visits, hospitalizations, post-acute care, telehealth visits) among SARS-CoV-2 positive participants by age
    • Characterize health outcomes by age and SARS-CoV-2 positive status: emergency or ambulatory care, admission to hospital); ICU-free survival; hospital-free survival; clinical events including need for intensive care, need for ventilation, onset of pneumonia or acute respiratory distress syndrome, myocardial infarction, renal failure, treated cardiac arrest, and death; and subsequent patient-reported health status (physical health; mental health; cognition; return to activities/work; ME-CFS)
  • Analyses to address Aim 2 will evaluate the independent effect of age on the outcomes examined in Aim 1 when also adjusted for additional patient level factors of interest, including gender, race/ethnicity, income, and presence of specific underlying conditions such as hypertension and diabetes, and other factors based on clinical experience.
  • We will use statistical modeling to estimate the association between age, and its interaction with key covariates, and outcomes. Survival analysis techniques will be used to analyze time to event outcomes. For binary outcomes (e.g., hospitalization/no hospitalization), we will use logistic regression. For continuous outcomes (e.g., PROMIS-29), we will use linear regression models.
  • Multiple imputation for missing data

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