ArticleBMJ open2024
COVID-19 profiles in general practice: a latent class analysis.
Article in BMJ open, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- COVID-19 Symptoms and Mental Health Outcomes among Italian Healthcare Workers: A Latent Class Analysis.Healthcare (Basel, Switzerland) · 2024Article
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9 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundGeneral 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.
objectivesTo 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. DESIGN, SETTING AND
participantsIn 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. 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.
resultsWe 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.
conclusionOur 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.
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