A Nomogram for Predicting Delayed Viral Shedding in Non-Severe SARS-CoV-2 Omicron Infection

Abstract

The Omicron variant of SARS-CoV-2 has emerged as a significant global concern, characterized by its rapid transmission and resistance to existing treatments and vaccines. However, the specific hematological and biochemical factors that may impact the clearance of Omicron variant infection remain unclear. The present study aimed to identify easily accessible laboratory markers that are associated with prolonged virus shedding in non-severe patients with COVID-19 caused by the Omicron variant. Patients and Methods: A retrospective cohort study was conducted on 882 non-severe COVID-19 patients who were diagnosed with the Omicron variant in Shanghai between March and June 2022. The least absolute shrinkage and selection operator regression model was used for feature selection and dimensional reduction, and multivariate logistic regression analysis was performed to construct a nomogram for predicting the risk of prolonged SARS-CoV-2 RNA positivity lasting for more than 7 days. The receiver operating characteristic (ROC) curve and calibration curves were used to assess predictive discrimination and accuracy, with bootstrap validation. Results: Patients were randomly divided into derivation (70%, n = 618) and validation (30%, n = 264) cohorts. Optimal independent markers for prolonged viral shedding time (VST) over 7 days were identified as Age, C-reactive protein (CRP), platelet count, leukocyte count, lymphocyte count, and eosinophil count. These factors were subsequently incorporated into the nomogram utilizing bootstrap validation. The area under the curve (AUC) in the derivation (0.761) and validation (0.756) cohorts indicated good discriminative ability. The calibration curve showed good agreement between the nomogram-predicted and actual patients with VST over 7 days. Conclusion: Our study confirmed six factors associated with delayed VST in non-severe SARS-CoV-2 Omicron infection and constructed a Nomogram which may assist non-severely affected patients to better estimate the appropriate length of self-isolation and optimize their self-management strategies.

SARS-CoV-2 Omicron variant infection affects blood platelets, a comparative analysis with Delta variant

“…Therefore, platelets, as a prominent component of blood, may participate in the elimination of the Omicron variant or its components. Supporting this possibility, a recent report suggests a correlation between platelet counts and Omicron clearance efficiency ( 53 ). Additionally, it is plausible to suggest that platelets, and megakaryocytes ( 23 ), may contribute to the dissemination of the virus, which first affects the lungs and then spreads via the blood stream, infecting various organs and tissues.…”

Associations between genetic mutations in different SARS-CoV-2 strains and negative conversion time of viral RNA among imported cases in Hangzhou: A cross-sectional study

“… Gui et al (2023) built a nomogram involving four individual and clinical characteristics (older age, more comorbidities, incomplete vaccination course, and lack of antiviral therapy) to accurately predict the risk of 14-day PCR-based negative conversion failure among Omicron cases. Yu et al (2023) reported that six factors (age, C-reactive protein, platelet count, leukocyte count, lymphocyte count, and eosinophil count) were associated with delayed viral shedding time in non-severe SARS-CoV-2 Omicron cases. These studies focused on the influence of demographic and clinical characteristics on NCT.…”