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. 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  1 , Yu-Han Jiang  1 , Shen-Jie Li  1 , Xin-Yi Xie  1 , Yu Cheng  1 , Li Wu  1 , Jun Shen  1 , Wei Chen  1 , Jian-Ren Liu  1
Affiliations

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 et al. Brain Behav Immun Health. .

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+ 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+ 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.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
LASSO regression algorithm.
Fig. 2
Fig. 2
Nomogram prediction model for fatigue in Long COVID.
Fig. 3
Fig. 3
ROC and AUC of nomogram prediction model.
See this image and copyright information in PMC

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