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Natural course of post COVID-19 condition and implications for trial design and outcome selection: A population-based longitudinal cohort study
Preprint
en En
| PREPRINT-MEDRXIV
| ID: ppmedrxiv-22276746
ABSTRACT
BackgroundEvidence from population-based studies on the longer-term natural course of post COVID-19 condition is limited, but crucial for informing patients and healthcare providers and for effectively designing clinical trials. ObjectivesTo evaluate longer-term symptoms and health outcomes within a cohort of SARS-CoV-2 infected individuals. DesignPopulation-based, longitudinal cohort. SettingGeneral population, Canton of Zurich, Switzerland. Patients1543 adults with confirmed SARS-CoV-2 infection and 628 adults without infection. MeasurementsChanges in self-reported health status over time, factors associated with persistence of non-recovery, and prevalence and excess risk of symptoms at 6 and 12 months post-infection compared to non-infected individuals. Results25% of SARS-CoV-2 infected individuals did not recover by 6 months. Of those, 67% and 58% also did not recover at 12 and 18 months after infection, respectively. Hospitalization for acute COVID-19, pre-existing fatigue and pain or discomfort, and presence of specific systemic, cardiovascular, or musculoskeletal symptoms at 6 months were associated with persistent non-recovery. Symptom prevalence was higher among infected individuals compared to non-infected individuals at 6 months (adjusted risk difference (aRD)=17%) and 12 months (aRD=20%). aRDs for individual symptoms ranged from 2% to 12%, with the highest excess risks observed for altered taste or smell, post-exertional malaise, fatigue, and reduced concentration and memory. LimitationsWe relied on self-reported assessments and did not assess the effects of vaccination or infection with emerging variants of concern. ConclusionThese findings emphasize the need for effective interventions to reduce the burden of post COVID-19 condition. They further demonstrate the importance of using multiple outcome measures and of considering the expected rates of natural recovery and heterogenous patient trajectories in the design and interpretation of clinical trials.
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Texto completo:
1
Colección:
09-preprints
Base de datos:
PREPRINT-MEDRXIV
Tipo de estudio:
Cohort_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