Number of initial symptoms is more related to long COVID-19 than acute severity of infection: a prospective cohort of hospitalized patients

Abstract:

Objectives: Post–COVID-19 symptoms experienced by many survivors have a further devastating effect. This study aimed to analyze the risk factors associated with long COVID-19 in a prospective cohort of hospitalized patients including those requiring intensive care unit (ICU) transfer, taking into account objective measures of COVID-19 severity.

Methods: Hospitalized patients with confirmed COVID-19 were enrolled. A structured follow-up visit was performed 4 months after hospital admission. Multivariable adjusted regression models were used to analyse the association between parameters at the acute phase and persistent symptoms.

Results: A follow-up visit was performed in 316 patients including 115 (36.4%) discharged from the ICU. Mean age was 64.1 years, and 201 patients (58.3%) were men. Female sex (odds ratio [OR], 1.94; 95% confidence interval [CI], 1.17-3.22; P =.01), hypertension (OR, 2.01; 95% CI, 1.22-3.31; P <.01), and the number of initial symptoms (NIS) (OR, 1.35; 95% CI, 1.17-1.54; P <.001) were significantly associated with long COVID-19. Number of persistent symptoms was significantly associated with NIS (adjusted incidence rate ratio [aIRR], 1.16; 95% CI, 1.11-1.22; P <.001), female sex (aIRR, 1.56; 95% CI 1.29-1.87; P <.001), hypertension (aIRR, 1.23; 95% CI, 1.02-1.50; P =.03), and length of stay in hospital (aIRR, 1.01; 95% CI, 1.005-1.017; P <.001).

Conclusion: Our study suggested that female sex, hypertension, and NIS had a significant impact on persistent symptoms in hospitalized patients in contrast to severity of acute COVID-19 infection.

Source: Adrien CSK, Alexandre C, Marie M, Cédric J, Schmit JL, Jean-Philippe L, Claire A. Number of initial symptoms is more related to long COVID-19 than acute severity of infection: a prospective cohort of hospitalized patients. Int J Infect Dis. 2022 Mar 4;118:220–3. doi: 10.1016/j.ijid.2022.03.006. Epub ahead of print. PMID: 35257903; PMCID: PMC8896858. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8896858/ (Full text)

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