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Characterising patterns of COVID-19 and long COVID symptoms: Evidence from nine UK longitudinal studies
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-22275994
ABSTRACT
Multiple studies across global populations have established the primary symptoms characterising COVID-19 (Coronavirus Disease 2019) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID could not be examined. We aimed to characterise patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ( no COVID-19, COVID-19 in last 12 weeks, COVID-19 > 12 weeks ago), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the COVID-19 in last 12 weeks and no COVID-19 groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the COVID-19 > 12 weeks ago and no COVID-19 groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.
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Texto completo:
1
Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Cohort_studies
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Diagnostic_studies
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Experimental_studies
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Observational_studies
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Prognostic_studies
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Rct
Idioma:
En
Año:
2022
Tipo del documento:
Preprint