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COVID-19 profiles in general practice: a latent class analysis.
- Source :
-
BMJ open [BMJ Open] 2024 Jun 06; Vol. 14 (6), pp. e080393. Date of Electronic Publication: 2024 Jun 06. - Publication Year :
- 2024
-
Abstract
- Background: General practitioners (GPs) were on the front line of the COVID-19 outbreak. Identifying clinical profiles in COVID-19 might improve patient care and enable closer monitoring of at-risk profiles.<br />Objectives: To identify COVID-19 profiles in a population of adult primary care patients, and to determine whether the profiles were associated with negative outcomes and persistent symptoms.<br />Design, Setting and Participants: In a prospective multicentre study, 44 GPs from multiprofessional primary care practices in the Paris area of France recruited 340 consecutive adult patients (median age: 47 years) with a confirmed diagnosis of COVID-19 during the first two waves of the epidemic.<br />Method and Outcome: A latent class (LC) analysis with 11 indicators (clinical signs and symptoms) was performed. The resulting profiles were characterised by a 3-month composite outcome (COVID-19-related hospital admission and/or death) and persistent symptoms three and 6 months after inclusion.<br />Results: We identified six profiles: 'paucisymptomatic' (LC1, 9%), 'anosmia and/or ageusia' (LC2, 12.9%), 'influenza-like syndrome with anosmia and ageusia' (LC3, 15.5%), 'influenza-like syndrome without anosmia or ageusia' (LC4, 24.5%), 'influenza-like syndrome with respiratory impairment' (LC5) and a 'complete form' (LC6, 17.7%). At 3 months, 7.4% of the patients were hospitalised (with higher rates in LC5), and 18% had persistent symptoms (with higher rates in LC5 and LC6). At 6 months, 6.4% of the patients had persistent symptoms, with no differences between LCs.<br />Conclusion: Our findings might help GPs to identify patients at risk of persistent COVID-19 symptoms and hospital admission and then set up procedures for closer monitoring.<br />Competing Interests: Competing interests: None declared.<br /> (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
- Subjects :
- Humans
Middle Aged
Male
Female
Prospective Studies
Adult
Aged
France epidemiology
Hospitalization statistics & numerical data
Primary Health Care statistics & numerical data
Paris epidemiology
Anosmia epidemiology
Ageusia epidemiology
COVID-19 epidemiology
COVID-19 diagnosis
General Practice statistics & numerical data
SARS-CoV-2
Latent Class Analysis
Subjects
Details
- Language :
- English
- ISSN :
- 2044-6055
- Volume :
- 14
- Issue :
- 6
- Database :
- MEDLINE
- Journal :
- BMJ open
- Publication Type :
- Academic Journal
- Accession number :
- 38844390
- Full Text :
- https://doi.org/10.1136/bmjopen-2023-080393