Evidence map›Paper›PMID 39552716›Full record

ArticleEClinicalMedicine2024

Incidence of post-acute COVID-19 symptoms across healthcare settings in seven countries: an international retrospective cohort study using routinely-collected data.

Junqing Xie, Kim López-Güell, Daniel Dedman, Talita Duarte-Salles, Raivo Kolde, Raúl López-Blasco, Álvaro Martínez, Gregoire Mercier, Alicia Abellan, Johnmary T Arinze and 28 more

Abstract read
In one paragraph

Article in EClinicalMedicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

38 authors.

Junqing XieNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Kim López-GüellNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Daniel DedmanCPRD, Medicines and Healthcare Products Regulatory Agency, London, UK.
Talita Duarte-SallesFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Raivo KoldeInstitute of Computer Science, University of Tartu, Tartu, Estonia.
Raúl López-BlascoBiocomputing Unit, Aragon Health Sciences Institute (IACS), Zaragoza, Spain.
Álvaro MartínezThe Health Research Institute Hospital La Fe, Avenida Fernando Abril Martorell, 106 Torre A 7a Planta, 46026, Valencia, Spain.
Gregoire MercierPublic Health Department, University Hospital of Montpellier, 34295 Montpellier, France.
Alicia AbellanFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Johnmary T ArinzeDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Zara CuccuCPRD, Medicines and Healthcare Products Regulatory Agency, London, UK.
Antonella DelmestriNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Dominique DelsenyPublic Health Department, University Hospital of Montpellier, 34295 Montpellier, France.
Sara KhalidNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Chungsoo KimDepartment of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Republic of Korea.
Ji-Woo KimBig Data Department, Health Insurance Review and Assessment Service, Wonju, Republic of Korea.
Kristin KostkaNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Cora LosteDepartment of Infectious Diseases, Hospital Germans Trias i Pujol, Badalona, Catalonia, Spain.
Lourdes MateuDepartment of Infectious Diseases, Hospital Germans Trias i Pujol, Badalona, Catalonia, Spain.
Miguel A MayerParc de Salut Mar, Hospital del Mar Medical Research Institute, Barcelona, Spain.
Jaime Meléndez-CardielBiocomputing Unit, Aragon Health Sciences Institute (IACS), Zaragoza, Spain.
Núria Mercadé-BesoraNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Mees MosseveldDepartment of Medical Informatics, Erasmus University Medical Center, Rotterdam, the Netherlands.
Akihito NishimuraDepartment of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Hedvig M E NordengPharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
Jessie O OyinlolaCPRD, Medicines and Healthcare Products Regulatory Agency, London, UK.
Laura Pérez-CrespoFundació Institut Universitari per a la recerca a l'Atenció Primària de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain.
Marta Pineda-MoncusíNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Juan Manuel Ramírez-AnguitaParc de Salut Mar, Hospital del Mar Medical Research Institute, Barcelona, Spain.
Nhung T H TrinhPharmacoepidemiology and Drug Safety Research Group, Department of Pharmacy, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway.
Anneli UuskülaInstitute of Family Medicine and Public Health, University of Tartu, Tartu, Estonia.
Bernardo ValdiviesoThe Health Research Institute Hospital La Fe, Avenida Fernando Abril Martorell, 106 Torre A 7a Planta, 46026, Valencia, Spain.
Theresa BurkardNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Edward BurnNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Martí CatalàNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Daniel Prieto-AlhambraNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
Roger ParedesDepartment of Infectious Diseases, Hospital Germans Trias i Pujol, Badalona, Catalonia, Spain.
Annika M JödickeNuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The World Health Organisation (WHO) has identified a range of symptomatic manifestations to aid in the clinical diagnosis of post-COVID conditions, herein referred to as post-acute COVID-19 symptoms. We conducted an international network cohort study to estimate the burden of these symptoms in North American, European, and Asian populations. Methods: A federated analysis was conducted including 10 databases from the United Kingdom, Netherlands, Norway, Estonia, Spain, France, South Korea, and the United States, between September 1st 2020 and latest data availability (which varied from December 31st 2021 to February 28th 2023), covering primary and secondary care, nationwide registries, and claims data, all mapped to the Observational Medical Outcomes Partnership Common Data Model (OMOP CDM). We defined two cohorts for the main analyses: a SARS-CoV-2 infection cohort [positive polymerase chain reaction (PCR) or rapid lateral flow test (LFT) result or clinical COVID-19 diagnosis] and a general population cohort. Individuals with less than 365 days of prior history or 120 days of follow-up were excluded. We estimated incidence rates (IRs) of the 25 WHO-proposed post-acute COVID-19 symptoms, considering symptoms that occurred ≥90 and ≤365 days after index date, excluding individuals with the respective symptoms 180 days prior to the index event. Stratified analyses were conducted by age and sex. Incidence rate ratios (IRRs) were calculated comparing rates in the infected cohort versus the general population. Results from the different databases were combined using random-effects meta-analyses. Findings: 3,019,408 individuals were included in the infection cohort. 1,585,160 of them were female and 1,434,248 of them male. 929,351,505 individuals were included in the general population group. 461,195,036 of them were female and 466,022,004 of them male. The 1-year IR of any post-acute COVID-19 symptom in the COVID-19 infection cohort varied significantly across databases, from 4.4 (95% CI 3.8-5.1) per 100 person-years to 103.9 (95% CI 103.2-104.7). The five most common symptoms were joint pain (from 1.6 (95% CI 1.3-1.9) to 14.3 (95% CI 14.1-14.6)), abdominal pain (from 0.3 (95% CI 0.1-0.5) to 9.9 (95% CI 9.7-10.1)), gastrointestinal issues (from 0.6 (95% CI 0.4-0.9) to 13.3 (95% CI 13.1-13.6)), cough (from 0.3 (95% CI 0.2-0.5) to 9.1 (95% CI 8.9-9.3)), and anxiety (from 0.8 (95% CI 0.6-1.2) to 11.4 (95% CI 11.2-11.6)); whereas muscle spasms (from 0.01 (95% CI 0.008-0.2) to 1.7 (95% CI 1.6-1.8)), pins and needles (from 0.05 (95% CI 0.03-0.0.9) to 1.5 (95% CI 1.4-1.6)), memory issues (from 0.03 (95% CI 0.02-0.06) to 0.8 (95% CI 0.7-0.8)), cognitive dysfunction (from 0.007 (95% CI 0.004-0.01) to 0.6 (95% CI 0.4-0.8)), and altered smell and/or taste (from 0.04 (95% CI 0.03-0.04) to 0.7 (95% CI 0.6-0.8)) were least common. Incidence rates of any post-acute COVID-19 symptoms generally increased with age, with certain symptoms peaking in middle-aged adults (anxiety, depressive disorders, headache, altered smell and taste) and others in pre-school children (gastrointestinal issues and cough). Females had higher incidence rates for most symptoms. Based on the random-effects model, the infected cohort had a higher incidence of any post-acute COVID-19 symptom than the general population, with a meta-analytic incidence rate ratio (meta-IRR) of 1.4 (1-2). A similar pattern was seen for all individual symptoms. The highest meta-IRRs were depressive disorder, 2.6 (1.7-3.9); anxiety, 2.3 (1.4-3.8); allergy, 2.1 (1.7-2.8) and sleep disorders, 2.1 (1.5-2.6). The meta-IRR for altered smell and/or taste was 1.9 (1.3-2.8). Interpretation: Post-acute COVID-19 symptoms, as listed by the WHO, were commonly observed following COVID-19 infection. However, even after standardising research methods, there was significant heterogeneity in the incidence rates from different healthcare settings and geographical locations. This is the first international study of the epidemiology of post-acute COVID-19 symptoms using the WHO-listed symptoms. Its findings contibute to understand the epidemiology of this condition from a multinational approach. Limitations of this study include the lack of consensus of the post-acute COVID-19 definition, as well as the difficulty to capture the impact on daily life of the post-acute COVID-19 symptoms in the available datasets. Funding: This work has been funded by the European Health Data Evidence Network (EHDEN) through an Evidence Generation Fund Grant and by the National Institute for Health and Care Research (NIHR) Oxford Biomedical Research Centre (BRC).

Indexed as

EpidemiologyIncidence of post-acute COVID-19 symptomsInternational cohort studyPost-acute COVID-19 conditionReal world data

Identifiers

PMID39552716
PMCPMC11564986

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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.