Evidence map›Paper›PMID 39879159›Full record

ArticlePloS one2025

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

Isabelle Bos, Lisa Bosman, Rinske van den Hoek, Willemijn van Waarden, Matthijs S Berends, Maarten S Homburg, Tim Olde Hartman, Jean Muris, Lilian S Peters, Bart Knottnerus and 2 more

Abstract readComparative Study
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Isabelle BosNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.ORCID 0000-0001-9648-6428
Lisa BosmanNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
Rinske van den HoekNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
Willemijn van WaardenNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
Matthijs S BerendsDepartment of General Practice and Elderly Care Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Maarten S HomburgDepartment of General Practice and Elderly Care Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Tim Olde HartmanDepartment of Primary and Community Care, Radboud Institute of Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands.
Jean MurisCare and Public Health Research Institute (CAPHRI), Department of Family Medicine, Maastricht University, Maastricht, The Netherlands.
Lilian S PetersDepartment of General Practice and Elderly Care Medicine, University Medical Center Groningen, Groningen, The Netherlands.
Bart KnottnerusNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
Karin S HekNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.
Robert A VerheijNivel, Netherlands Institute for Health Services Research, Utrecht, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSome 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.

methodsWe 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 on symptoms and diagnosis recorded in GP-EHR data and healthcare utilization 3-12 months after acute infection) to calculate frequency and characteristics and compared this to the survey results. In a subgroup of the EHR data we conducted community detection analyses to explore clinical subtypes of PCS.

resultsThe frequency of PCS was 15% with on average 4.6 symptoms for which the GP was consulted using the narrow definition and 32% with on average 6.8 symptoms for the broad definition. Across all methods and classifications, the mean age of individuals with PCS was around 53 years and they were more often female. There were small sex differences in the type of symptoms and overall symptoms were persistent for 6 months. The community detection analysis revealed three possible clinical subtypes. DISCUSSION: We showed that frequency rates of PCS differ between methods and data sources, but characteristics of the affected individuals are relatively stable. Overall, PCS is a heterogeneous syndrome affecting a substantial group of individuals who need adequate care. Future studies should focus on care trajectories and qualitative measures such as quality of life of individuals living with PCS.

Indexed as

COVID-19Electronic Health RecordsAdolescentAdultAgedFemaleHumansLongitudinal StudiesMaleMiddle AgedNetherlandsSARS-CoV-2Surveys and QuestionnairesYoung Adult

Identifiers

PMID39879159
PMCPMC11778627

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.