Incidence, symptom clusters and determinants of post-acute COVID symptoms: a population-based surveillance in community-dwelling users of the COVID RADAR app
Year: 2024
Type: article
Study design: Observational Study
Abstract: OBJECTIVES: This study aims to describe the incidence, symptom clusters and determinants of post-acute COVID symptoms using data from the COVID RADAR app in the Netherlands. DESIGN: Prospective cohort. SETTING: General population in the Netherlands from April 2020 to February 2022. PARTICIPANTS: A total of 1478 COVID RADAR app users, with data spanning 40 days before to 100 days after positive SARS-CoV-2 test. OUTCOME MEASURES: Incidence and duration of 10 new symptoms that developed during acute infection, defined as 10 days prior and 10 days after positive test. Clustering of these post-acute COVID symptoms and associations between factors known in the acute phase and 100-day symptom persistence. RESULTS: The most frequent post-acute symptoms were cough, loss of smell or taste and fatigue. At 100 days postinfection, 86 (8%) participants still experienced symptoms. Three post-acute COVID symptom clusters were identified: non-respiratory (headache and fatigue; 49% of participants with post-acute COVID symptoms); olfactory (15%) and respiratory (8%). Vaccination was associated with a lower risk of post-acute COVID symptoms 100 days after infection, although CIs were wide (OR: 0.5; 95% CI: 0.2 to 1.5), but not with non-respiratory symptoms (OR: 1.0; 95% CI: 0.3 to 4.4). Severe acute disease increased the risk of post-acute COVID symptoms (OR: 1.4; 95% CI: 1.2 to 1.5; per additional acute symptom). CONCLUSIONS: In this cohort of infected community-dwelling app users, 5%-10% experienced post-acute COVID symptoms. The symptoms cluster in several distinct entities, which differ in incidence, patient characteristics and vaccination effects. This suggests multiple mechanisms underlying the development of post-acute COVID symptoms.
Source: BMJ Open
Institution: Leiden University Medical Center
Language: English
Subfield: Neurology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $1,839
Funder: ZonMw
Awards: G1368052221, G5648552784, G5917476132
OpenAlex ID: W4402452167
