Clinical predictors and RT-PCR profile of prolonged viral shedding in patients with SARS-CoV-2 Omicron variant in Shanghai: A retrospective observational study

Machine learning based predictive modeling and risk factors for prolonged SARS-CoV-2 shedding

BACKGROUND

The global outbreak of the coronavirus disease 2019 (COVID-19) has been enormously damaging, in which prolonged shedding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, previously 2019-nCoV) infection is a challenge in the prevention and treatment of COVID-19. However, there is still incomplete research on the risk factors that affect delayed shedding of SARS-CoV-2.

METHODS

In a retrospective analysis of 56,878 hospitalized patients in the Fangcang Shelter Hospital (National Convention and Exhibition Center) in Shanghai, China, we compared patients with the duration of SARS-CoV-2 viral shedding > 12 days with those days < 12 days. The results of real-time polymerase chain reaction (RT-PCR) tests determined the duration of viral shedding from the first day of SARS-CoV-2 positivity to the day of SARS-CoV-2 negativity. The extreme gradient boosting (XGBoost) machine learning method was employed to establish a prediction model for prolonged SARS-CoV-2 shedding and analyze significant risk factors. Filtering features retraining and Shapley Additive Explanations (SHAP) techniques were followed to demonstrate and further explain the risk factors for long-term SARS-CoV-2 infection.

RESULTS

We conducted an assessment of ten different features, including vaccination, hypertension, diabetes, admission cycle threshold (Ct) value, cardio-cerebrovascular disease, gender, age, occupation, symptom, and family accompaniment, to determine their impact on the prolonged SARS-CoV-2 shedding. This study involved a large cohort of 56,878 hospitalized patients, and we leveraged the XGBoost algorithm to establish a predictive model based on these features. Upon analysis, six of these ten features were significantly associated with the prolonged SARS-CoV-2 shedding, as determined by both the importance order of the model and our results obtained through model reconstruction. Specifically, vaccination, hypertension, admission Ct value, gender, age, and family accompaniment were identified as the key features associated with prolonged viral shedding.

CONCLUSIONS

We developed a predictive model and identified six risk factors associated with prolonged SARS-CoV-2 viral shedding. Our study contributes to identifying and screening individuals with potential long-term SARS-CoV-2 infections. Moreover, our research also provides a reference for future preventive control, optimizing medical resource allocation and guiding epidemiological prevention, and guidelines for personal protection against SARS-CoV-2.

A retrospective analysis of the influencing factors of nucleic acid CT value fluctuation in COVID-19 patients infected with Omicron variant virus in Changchun city

Objective

This study aimed to determine the risk factors associated with fluctuations in nucleic acid CT values in patients infected with the Omicron variant during an outbreak at a hospital in Changchun city.

Methods

A retrospective analysis was conducted on general information, medical history, vaccination history, and laboratory test data of COVID-19 patients infected with the Omicron variant and admitted to the hospital in Changchun from March 2022 to April 2022. The study aimed to explore the factors influencing nucleic acid CT value fluctuations in COVID-19 patients infected with the Omicron variant in Changchun city.

Results

Fluctuations in nucleic acid CT values were significantly correlated with occupation composition (p = 0.030), hospital stay duration (p = 0.000), heart rate (p = 0.026), creatinine (p = 0.011), platelet count (p = 0.000), glutamic-pyruvic transaminase (p = 0.045), and glutamic oxaloacetic transaminase (p = 0.017). Binary logistic regression analysis revealed significant correlations between hospital stay duration (p = 0.000), platelet count (p = 0.019), heart rate (p = 0.036), and nucleic acid CT value fluctuations (p < 0.05), indicating that they were independent risk factors. Red blood cell count was identified as a factor influencing nucleic acid CT value fluctuations in Group A patients. Occupation composition, direct bilirubin, and platelet count were identified as factors influencing nucleic acid CT value fluctuations in Group B patients. Further binary logistic regression analysis indicated that occupational composition and direct bilirubin are significant independent factors for nucleic acid CT value fluctuations in Group B patients, positively correlated with occupational risk and negatively correlated with direct bilirubin.

Conclusion

Therefore, enhancing patients' immunity, increasing physical exercise to improve myocardial oxygen consumption, reducing the length of hospital stays, and closely monitoring liver function at the onset of hospitalization to prevent liver function abnormalities are effective measures to control fluctuations in nucleic acid CT values.

Efficacy and Safety of Huashi Baidu Granules in Treating Patients with SARS-CoV-2 Omicron Variant: A Single-Center Retrospective Cohort Study

OBJECTIVE

To evaluate the efficacy and safety of Huashi Baidu Granules (HSBD) in treating patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant.

METHODS

A single-center retrospective cohort study was conducted during COVID-19 Omicron epidemic in the Mobile Cabin Hospital of Shanghai New International Expo Center from April 1st to May 23rd, 2022. All COVID-19 patients with asymptomatic or mild infection were assigned to the treatment group (HSBD users) and the control group (non-HSBD users). After propensity score matching in a 1:1 ratio, 496 HSBD users of treatment group were matched by propensity score to 496 non-HSBD users. Patients in the treatment group were administrated HSBD (5 g/bag) orally for 1 bag twice a day for 7 consecutive days. Patients in the control group received standard care and routine treatment. The primary outcomes were the negative conversion time of nucleic acid and negative conversion rate at day 7. Secondary outcomes included the hospitalized days, the time of the first nucleic acid negative conversion, and new-onset symptoms in asymptomatic patients. Adverse events (AEs) that occurred during the study were recorded. Further subgroup analysis was conducted in vaccinated (378 HSBD users and 390 non-HSBD users) and unvaccinated patients (118 HSBD users and 106 non-HSBD users).

RESULTS

The median negative conversion time of nucleic acid in the treatment group was significantly shortened than the control group [3 days (IQR: 2-5 days) vs. 5 days (IQR: 4-6 days); P<0.01]. The negative conversion rate of nucleic acid in the treatment group were significantly higher than those in the control group at day 7 (91.73% vs. 86.90%, P=0.014). Compared with the control group, the hospitalized days in the treatment group were significantly reduced [10 days (IQR: 8-11 days) vs. 11 days (IQR: 10.25-12 days); P<0.01]. The time of the first nucleic acid negative conversion had significant differences between the treatment and control groups [3 days (IQR: 2-4 days) vs. 5 days (IQR: 4-6 days); P<0.01]. The incidence of new-onset symptoms including cough, pharyngalgia, expectoration and fever in the treatment group were lower than the control group (P<0.05 or P<0.01). In the vaccinated patients, the median negative conversion time and hospitalized days were significantly shorter than the control group after HSDB treatment [3 days (IQR: 2-5 days) vs. 5 days (IQR: 4-6 days), P<0.01; 10 days (IQR: 8-11 days) vs. 11 days (IQR: 10-12 days), P<0.01]. In the unvaccinated patients, HSBD treatment efficiently shorten the median negative conversion time and hospitalized days [4 days (IQR: 2-6 days) vs. 5 days (IQR: 4-7 days), P<0.01; 10.5 days (IQR: 8.75-11 days) vs. 11.0 days (IQR: 10.75-13 days); P<0.01]. No serious AEs were reported during the study.

CONCLUSION

HSBD treatment significantly shortened the negative conversion time of nuclear acid, the length of hospitalization, and the time of the first nucleic acid negative conversion in patients infected with SARS-COV-2 Omicron variant (Trial registry No. ChiCTR2200060472).

A Model for Predicting the Duration of Viral Shedding in Patients Who Had Been Hospitalized with Mild COVID-19: A Single-Center Retrospective Study

Background

Clinical decision-making is enhanced by the development of a mathematical model for prognosis prediction. Screening criteria associated with viral shedding time and developing a prediction model facilitate clinical decision-making and are, thus, of great medical value.

Methods

This study comprised 631 patients who were hospitalized with mild COVID-19 from a single center and 30 independent variables included. The data set was randomly divided into the training set (80%) and the validation set (20%). The outcome variable included viral shedding time and whether the viral shedding time >14 days, LASSO was used to screen the influencing factors.

Results

There were 321 males and 310 females among the 631 cases, with an average age of 62.1 years; the median viral shedding time was 12 days, and 68.8% of patients experienced viral shedding within 14 days, with fever (50.9%) and cough (44.2%) being the most common clinical manifestations. Using LASSO with viral shedding time as the outcome variable, the model with lambda as 0.1592 (λ = 0.1592) and 13 variables (eg the time from diagnosis to admission, constipation, cough, hs-CRP, IL-8, IL-1β, etc.) was more accurate. Factors were screened by LASSO and multivariable logistic regression with whether the viral shedding time >14 days as the outcome variable, five variables, including the time from diagnosis to admission, CD4 cell count, Ct value of ORF1ab, constipation, and IL-8, were included, and a nomogram was drawn; after model validation, the consistency index was 0.888, the AUC was 0.847, the sensitivity was 0.744, and the specificity was 0.830.

Conclusion

A clinical model developed after LASSO regression was used to identify the factors that influence the viral shedding time. The predicted performance of the model was good, and it was useful for the allocation of medical resources.

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

Purpose

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.

A retrospective study investigating the anxiety and depression level of novel coronavirus Omicron patients in 2022

INTRODUCTION

The novel coronavirus disease 2019 continues to spread widely, not only causing physical disorders in patients but also impairing mental health, bringing a heavy burden on global public health. This study aimed to evaluate the anxiety and depression status of patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) omicron variant in Shanghai.

METHODS/DESIGN

This study aimed to retrospectively analyze 2000 patients infected with the SARS-CoV-2 Omicron variant. Data from patients assessed with demographic information, anxiety and depressive symptoms were collected using a questionnaire. Clinical and laboratory data were collected using electronic medical system. Anxiety and depression were assessed using the Self-Rating Anxiety Scale, the Generalized Anxiety Disorder Scale, and the Patient Health Questionnaire. Clinical information and laboratory indicators included age, sex, blood pressure, blood glucose, basic disease, time of diagnosis onset, duration of hospitalization, vaccination status of novel coronavirus disease 2019, and virus-negative conversion time.

DISCUSSION

This study will provide evidence-based suggestions for early psychological intervention in patients infected with the SARS-CoV-2 Omicron Variant.