(34) Techniques for Characterising Long COVID in Real World Data

Sunday, August 28, 2022

8:00 AM – 1:45 PM CEST

Location: Hall C

Publication Number: 1079

Presenting Author(s)

Kristin Kostka
– OHDSI, University of Oxford, NDORMS, Portland, Maine, United States

Co-Author(s)

Evan Minty, MD
– Clinical Assistant Professor, O'Brien Institute for Public Health, Faculty of Medicine, University of Calgary, Canada, Calgary, AB, Canada
Antonella Delmestri, PhD
– SENIOR HEALTH DATA SCIENTIST, Pharmaco- and Device Epidemiology, Centre for Statistics in Medicine - Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Windmill Road, Oxford, England, United Kingdom
Barrack Omondi
– Pharmaco- and Device Epidemiology, Centre for Statistics in Medicine - Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, Botnar Research Centre, University of Oxford, Windmill Road, Oxford, England, United Kingdom
Daniel Prieto-Alhambra, MD, MSc, PhD, FISPE
– Professor of Pharmaco- and Device Epidemiology, CSM, NDORMS, University of Oxford, University of Oxford, Oxford, United Kingdom
Annika Joedicke
– Nuffield Department of Orthopaedics, Rheumatology, and Musculoskeletal Sciences,University of Oxford, Oxfordshire, United Kingdom

Background: “Post-acute COVID-19 syndrome” or “long COVID” is an emerging clinical condition characterised by persistent symptoms that continue for at least 2 3 months following acute COVID-19 disease. Clinicians have varying familiarity in the characteristic symptoms associated with long COVID, creating considerable challenges in defining and measuring this pressing public health issue at scale.

Objectives: 1. To create a clinical phenotype from the WHO post COVID-19 Delphi consensus of 25 recognized symptoms.
2. To assess the prevalence of expected long COVID symptoms in a large database of UK-based primary care electronic health records.

Methods: We conducted a descriptive, retrospective cohort study using a large database of UK-based primary care electronic health records, Clinical Practice Research Datalink (CPRD) Aurum. We evaluated the prevalence of 25 symptoms in persons with COVID-19 diagnosis or a positive test in a primary care setting. The study period started on 1 January 2020 and ended at the last available date (3 Nov 2021). Persons were required to have 180 days prior to diagnosis or test and no history of the symptom prior to index. We then evaluated the role of required time in persistent symptoms (e.g. +28 days, +90 days, +180 days after diagnosis or test) and prior history (- 90 days, -180 days).

Results: A total of 458,975 persons with COVID-19 diagnosis or a positive test met the cohort entry criteria. Of the symptoms evaluated, dyspnea was the most common with 4,005 persons (0.87%) experiencing persistent dyspnea at least 28 days after index and no history of dyspnea in the prior 90 days. Other top symptoms included anxiety (n=3,378) and joint pain (n=3,340). Symptoms varied by age. Younger people (age 20-29) reported more anxiety (IR: 0.58 per 1,000 person-years). Older people (age 70+) reported more dyspnea (IR ranged: 2.25 to 4.22 per 1,000 person-years).

Conclusions: We investigated multiple techniques for characterising expected long COVID symptoms in a large database of UK-based primary care electronic health records. We found differences in cohort counts based on changes in prior follow-up time, time for symptom persistence, gender, and age. We intend to study all WHO recognized symptoms across other primary care databases. Our work will provide diagnostic views into the operating characteristics of contributing databases. Our findings can help researchers understand the impact of varying clinical logic on describing and measuring long COVID.