Comparison of observational methods to identify and characterize post-COVID syndrome in the Netherlands using electronic health records and questionnaires.

ABSTRACT:

Background

Some of those infected with SARS-CoV-2 suffer from post-COVID syndrome (PCS). However, an uniform definition of PCS is lacking, causing uncertainty about the prevalence and nature of this syndrome. We aimed to improve understanding of PCS by operationalizing different classifications and to explore clinical subtypes.

Methods

We used data from Nivel Primary Care database from 2019-2020 which consists of electronic health records (EHR) from general practices (GPs) combined with sociodemographic data for n = 10,313 individuals infected with the SARS-CoV-2. In addition, data from n = 276 individuals who had been infected with the SARS-CoV-2 in 2021, collected via a longitudinal survey, was used. In the GP-EHR data, we operationalized two classifications of PCS (based

SUBMITTER: Bos I 

PROVIDER: S-EPMC11778627 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature