| Description: |
Aims: The aim was to describe the epidemiology, phenotyping, and risk factors of long COVID (LC) in a well-defined cohort of kidney transplant recipients (KTRs) using a novel LC diagnostic method based on self-reported symptoms. Materials and methods: We conducted a cross-sectional study using an electronic survey to inquire about persisting symptoms following COVID-19. KTRs who survived COVID-19 up to February 8, 2023, were considered for inclusion, and 596 KTRs were enrolled. A brief 35-question screening questionnaire was used. A novel statistical approach based on the factor analysis method was used to make LC diagnosis and identify its clinical phenotypes. Results: LC was identified in 33.7% of KTRs who responded to the survey. Male sex (OR 0.69, 95% CI 0.48 - 1.0, p = 0.047), more severe COVID-19 (OR 2.48, 95% CI 1.58 - 3.92, p < 0.001), higher body mass index (OR 1.04, 95% CI 1.0 - 1.08, p = 0.031), and corticosteroids (OR 2.8, 95% CI 1.23 - 7.09, p = 0.02) were independently associated with LC development. Eight LC phenotypes were identified based on symptom clustering: fatigue (32.4% of all KTRs), psychiatric (15.9%), cardiovascular (6%), ophthalmic (13.8%), cognitive (17.8%), fibromyalgia-like (11.1%), integumental (10.6%), and malnutritional (6%). The rate of LC was similar in those who had COVID-19 less/more than a year since responding to the survey. Conclusion: A novel method for determining LC diagnosis and its phenotyping was used in a large cohort of KTRs, which showed that a third of KTRs who responded to the survey developed LC after COVID-19. This method may improve diagnosis and future research of LC. ; Supported by the project National Institute for Research of Metabolic and Cardiovascular Diseases (Programme EXCELES, ID Project No. LX22NPO5104) - Funded by the European Union – Next Generation EU. |