• FluTrackers.com Inc. does not provide medical advice. Information on this web site is collected from various internet resources, and the FluTrackers board of directors makes no warranty to the safety, efficacy, correctness or completeness of the information posted on this site by any author or poster. The information collated here is for instructional and/or discussion purposes only and is NOT intended to diagnose or treat any disease, illness, or other medical condition. Every individual reader or poster should seek advice from their personal physician/healthcare practitioner before considering or using any interventions that are discussed on this website. By continuing to access this website you agree to consult your personal physican before using any interventions posted on this website, and you agree to hold harmless FluTrackers.com Inc., the board of directors, the members, and all authors and posters for any effects from use of any medication, supplement, vitamin or other substance, device, intervention, etc. mentioned in posts on this website, or other internet venues referenced in posts on this website.
  • We are not asking for any donations. Do not donate to any entity who says they are raising funds for us.

Brain Behav Immun Health . Clinical features and predictive nomogram for fatigue sequelae in non-severe patients infected with SARS-CoV-2 Omicron va

tetano

Editor, Senior Moderator
Brain Behav Immun Health


. 2024 Oct 18:42:100889.
doi: 10.1016/j.bbih.2024.100889. eCollection 2024 Dec. Clinical features and predictive nomogram for fatigue sequelae in non-severe patients infected with SARS-CoV-2 Omicron variant in Shanghai, China

Xiao-Lei Shen[SUP] 1 [/SUP], Yu-Han Jiang[SUP] 1 [/SUP], Shen-Jie Li[SUP] 1 [/SUP], Xin-Yi Xie[SUP] 1 [/SUP], Yu Cheng[SUP] 1 [/SUP], Li Wu[SUP] 1 [/SUP], Jun Shen[SUP] 1 [/SUP], Wei Chen[SUP] 1 [/SUP], Jian-Ren Liu[SUP] 1 [/SUP]



Affiliations
Abstract

Background: Patients with coronavirus disease 2019(COVID-2019) infections may still experience long-term effects, with fatigue being one of the most frequent ones. Clinical research on the long COVID in the Chinese population after infection is comparatively lacking.
Objective: To collect and analyze the long-term effects of non-severe COVID-19 infection patients and to develop a model for the prediction of fatigue symptoms.
Methods: 223 non-severe COVID-19 patients admitted to one designated hospital were enrolled after finish all the self-designed clinical information registration form and nine-month follow-up. We explored the frequency and symptom types of long COVID. Correlation analysis was done on the neuropsychological scale results. After cluster analysis, lasoo regression and logistic regressions, a nomogram prediction model was produced as a result of investigating the risk factors for fatigue.
Results: A total of 108 (48.4%) of the 223 non-severe COVID-19 patients reported sequelae for more than 4 weeks, and of these, 35 (15.7%) had fatigue sequelae that were scale-confirmed. Other sequelae of more than 10% were brain fog (n = 37,16.6%), cough (n = 26,11.7%) and insomnia (n = 23,10.3%). A correlation between depression and fatigue was discovered following the completion of neuropsychological scale. The duration of hospitalization, the non-use of antiviral medications in treatment, IL-6 and CD16+CD56[SUP]+[/SUP] cell levels in blood are the main independent risk factors and predictors of fatigue sequelae in long COVID. Additionally, the neurology diseases and vaccination status may also influence the fatigue sequelae.
Conclusion: Nearly half of the patients infected with COVID-19 Omicron variant complained of sequelae, and fatigue was the most common symptom, which was correlated with depression. Significant predictors of fatigue sequelae included length of hospitalization, non-use of antiviral drug, and immune-related serum markers of IL-6 and CD16+CD56[SUP]+[/SUP] NK cell levels. The presence of neurology diseases and a lack of vaccination could also predict the occurrence of fatigue sequelae.

Keywords: COVID-19; Fatigue; Long COVID syndrome; Omicron; SARS-CoV-2.

 
Back
Top Bottom