Potential pitfalls in the use of real-world data for studying long COVID

HG Zhang, JP Honerlaw, M Maripuri… - Nature medicine, 2023 - nature.com
HG Zhang, JP Honerlaw, M Maripuri, MJ Samayamuthu, BR Beaulieu-Jones, HS Baig, S L'yi
Nature medicine, 2023nature.com
The value of large-scale, real-world data—from electronic health records (EHRs), for
example—has been used to establish vaccine efficacy, to elucidate the genetic etiologies of
diseases, and to advance epidemiological research 1–3. Real-world data also have the
potential to capture the wide spectrum of clinical features attributed to post-acute sequalae
of SARS-CoV-2, also called long COVID, in diverse patient populations 4. We are an
international consortium that has operationalized definitions of long COVID using health …
The value of large-scale, real-world data—from electronic health records (EHRs), for example—has been used to establish vaccine efficacy, to elucidate the genetic etiologies of diseases, and to advance epidemiological research 1–3. Real-world data also have the potential to capture the wide spectrum of clinical features attributed to post-acute sequalae of SARS-CoV-2, also called long COVID, in diverse patient populations 4. We are an international consortium that has operationalized definitions of long COVID using health-agency guidelines, and established a chart-review procedure based on these definitions 5. During this process, we identified three major challenges in using real-world data to study long COVID: ambiguity and heterogeneity in clinical coding of long COVID; inadequacy of diagnostic codes in capturing the constellation of symptoms; and biases in EHR data arising from variability in the number and kind of contacts with the healthcare system. These challenges warrant special attention if the clinical community wishes to arrive at a robust understanding of long COVID using evidence derived from real-world data.
We carried out a manual medical-record review of 300 randomly sampled individuals infected with SARS-CoV-2, and assigned an International Classification of Diseases (ICD)-10 code (U09. 9) for long COVID, at the Beth Israel Deaconess Medical Center, University of Pittsburgh Medical Center, and national US Veterans Health Administration 5. These three health systems collectively serve more than 15 million patients each year. We evaluated the extent to which patients with the ICD-10 code for this condition met our operationalized definitions based on guidelines from the World Health Organization (WHO) and the US Centers for Disease Control 5–7. Our definition of long COVID based on WHO guidelines required that a patient present with at least two new-onset persistent symptoms lasting for 60 days after infection, whereas our definition based on CDC guidelines required that a patient present with at least one new-onset persistent symptom lasting for 30 days 5.
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