Evidence map›Paper›PMID 36825252›Full record

ArticleInfluenza and other respiratory viruses2022

Symptom-based case definitions for COVID-19: Time and geographical variations for detection at hospital admission among 260,000 patients.

Joaquin Baruch, Amanda Rojek, Christiana Kartsonaki, Bharath K T Vijayaraghavan, Bronner P Gonçalves, Mark G Pritchard, Laura Merson, Jake Dunning, Matthew Hall, Louise Sigfrid and 5 more

Abstract read
In one paragraph

Article in Influenza and other respiratory viruses, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Review
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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

15 authors.

Joaquin BaruchISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0002-0806-3183
Amanda RojekISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0002-3948-0756
Christiana KartsonakiMRC Population Health Unit, Clinical Trials Service Unit and Epidemiological Studies Unit University of Oxford Oxford UK.ORCID 0000-0002-3981-3418
Bharath K T VijayaraghavanApollo Hospitals Chennai India.ORCID 0000-0002-1801-0667
Bronner P GonçalvesISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.
Mark G PritchardISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0003-1726-8989
Laura MersonISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0002-4168-1960
Jake DunningISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0002-4035-4562
Matthew HallBig Data Institute University of Oxford Oxford UK.
Louise SigfridISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.
Barbara W CitarellaISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0001-8968-0708
Srinivas MurthyFaculty of Medicine University of British Columbia Vancouver Canada.ORCID 0000-0002-9476-839X
Trokon O YeabahInfectious Diseases Data Observatory, Centre for Tropical Medicine and Global Health University of Oxford Oxford UK.
Piero OlliaroISARIC, Pandemic Sciences Institute University of Oxford Oxford UK.ORCID 0000-0003-1426-3680
ISARIC Clinical Characterisation Group

Funding

Cancer Research UK C18616/A25153Department of Health 200907Department of Health 200927Department of Health CO-CIN-01Department of Health ISBRC-1215-20013Department of Health NIHR201385Medical Research Council MC_PC_19059Wellcome Trust 205228/Z/16/ZWellcome Trust 215091/Z/18/ZWellcome Trust 220757/Z/20/Z
6 · The paper itself

Abstract

Introduction: Case definitions are used to guide clinical practice, surveillance and research protocols. However, how they identify COVID-19-hospitalised patients is not fully understood. We analysed the proportion of hospitalised patients with laboratory-confirmed COVID-19, in the ISARIC prospective cohort study database, meeting widely used case definitions. Methods: Patients were assessed using the Centers for Disease Control (CDC), European Centre for Disease Prevention and Control (ECDC), World Health Organization (WHO) and UK Health Security Agency (UKHSA) case definitions by age, region and time. Case fatality ratios (CFRs) and symptoms of those who did and who did not meet the case definitions were evaluated. Patients with incomplete data and non-laboratory-confirmed test result were excluded. Results: A total of 263,218 of the patients (42%) in the ISARIC database were included. Most patients (90.4%) were from Europe and Central Asia. The proportions of patients meeting the case definitions were 56.8% (WHO), 74.4% (UKHSA), 81.6% (ECDC) and 82.3% (CDC). For each case definition, patients at the extremes of age distribution met the criteria less frequently than those aged 30 to 70 years; geographical and time variations were also observed. Estimated CFRs were similar for the patients who met the case definitions. However, when more patients did not meet the case definition, the CFR increased. Conclusions: The performance of case definitions might be different in different regions and may change over time. Similarly concerning is the fact that older patients often did not meet case definitions, risking delayed medical care. While epidemiologists must balance their analytics with field applicability, ongoing revision of case definitions is necessary to improve patient care through early diagnosis and limit potential nosocomial spread.

Indexed as

COVID-19EuropeHospitalizationHospitalsHumansProspective Studiescase definitionsCOVID‐19hospitalisation

Identifiers

PMID36825252
PMCPMC9530510

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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.