Evidence map›Paper›PMID 37751444›Full record

ArticlePloS one2023

Long Covid symptoms and diagnosis in primary care: A cohort study using structured and unstructured data in The Health Improvement Network primary care database.

Anoop D Shah, Anuradhaa Subramanian, Jadene Lewis, Samir Dhalla, Elizabeth Ford, Shamil Haroon, Valerie Kuan, Krishnarajah Nirantharakumar

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
3.1field-weighted citation impact, top 8% of its field
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

10 citing papers in PubMed, 15 citations in OpenAlex.

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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

8 authors at 5 institutions in 1 country.

Anoop D ShahInstitute of Health Informatics, University College London, London, United Kingdom.ORCID 0000-0002-8907-5724
Anuradhaa SubramanianInstitute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0001-8875-7363
Jadene LewisInstitute of Health Informatics, University College London, London, United Kingdom.ORCID 0000-0001-6953-1852
Samir DhallaThe Health Improvement Network Ltd., London, United Kingdom.
Elizabeth FordBrighton and Sussex Medical School, Brighton, United Kingdom.ORCID 0000-0001-5613-8509
Shamil HaroonInstitute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.ORCID 0000-0002-0096-1413
Valerie KuanInstitute of Health Informatics, University College London, London, United Kingdom.
Krishnarajah NirantharakumarInstitute of Applied Health Research, University of Birmingham, Birmingham, United Kingdom.
University of Birmingham · GBUniversity College London · GBBrighton and Sussex Medical School · GBHealthcare Improvement Scotland · GBUCL Biomedical Research Centre · GB

Funding

Medical Research Council MC_PC_20030Medical Research Council MC_PC_20050Medical Research Council MC_PC_20051Medical Research Council MC_PC_20059Medical Research Council MR/V033867/1Wellcome Trust
6 · The paper itself

Abstract

backgroundLong Covid is a widely recognised consequence of COVID-19 infection, but little is known about the burden of symptoms that patients present with in primary care, as these are typically recorded only in free text clinical notes.

aimsTo compare symptoms in patients with and without a history of COVID-19, and investigate symptoms associated with a Long Covid diagnosis.

methodsWe used primary care electronic health record data until the end of December 2020 from The Health Improvement Network (THIN), a Cegedim database. We included adults registered with participating practices in England, Scotland or Wales. We extracted information about 89 symptoms and 'Long Covid' diagnoses from free text using natural language processing. We calculated hazard ratios (adjusted for age, sex, baseline medical conditions and prior symptoms) for each symptom from 12 weeks after the COVID-19 diagnosis.

resultsWe compared 11,015 patients with confirmed COVID-19 and 18,098 unexposed controls. Only 20% of symptom records were coded, with 80% in free text. A wide range of symptoms were associated with COVID-19 at least 12 weeks post-infection, with strongest associations for fatigue (adjusted hazard ratio (aHR) 3.46, 95% confidence interval (CI) 2.87, 4.17), shortness of breath (aHR 2.89, 95% CI 2.48, 3.36), palpitations (aHR 2.59, 95% CI 1.86, 3.60), and phlegm (aHR 2.43, 95% CI 1.65, 3.59). However, a limited subset of symptoms were recorded within 7 days prior to a Long Covid diagnosis in more than 20% of cases: shortness of breath, chest pain, pain, fatigue, cough, and anxiety / depression.

conclusionsNumerous symptoms are reported to primary care at least 12 weeks after COVID-19 infection, but only a subset are commonly associated with a GP diagnosis of Long Covid.

Indexed as

COVID-19Post-Acute COVID-19 SyndromeAdultChest PainCohort StudiesCOVID-19 TestingDyspneaFatigueFemaleHumansMalePrimary Health Care

Identifiers

PMID37751444
PMCPMC10521988
OpenAlexW4387043483

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.