Comorbidities prolonged viral shedding of patients infected with SARS-CoV-2 omicron variant in Shanghai: A multi-center, retrospective, observational study.

BACKGROUND: As the omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surges amid the coronavirus disease 2019 (COVID-19) pandemic, there is limited comorbidities data associated with viral shedding time (VST). We aimed to investigate the effect of comorbidities on VST in asymptomatic and mild patients with omicron. METHODS: A multi-center, retrospective, observational study was conducted from March 12, 2022 to May 24, 2022 in Shanghai. The analysis was adjusted for patients' baseline demographic, using log-rank test and logistic regression model. RESULTS: The study enrolled 198,262 subjects. The median duration of viral shedding time (VST) was 8.29 days. The number of cumulative viral shedding events was significantly lower in the chronic obstructive pulmonary disease (COPD), hyperlipidemia, diabetes, urinary system disease, and cardiocerebrovascular disease than in the no corresponding comorbidities group. Patients with comorbidities had a lower incidence of viral shedding, and the most significant independent risk factor is COPD (aOR 1.78, 95% CI: 1.53-2.08, p < 0.001). Across different age ranges, the comorbidities affecting viral shedding also differ, with the greatest risk factors for viral shedding being hyperlipidemia (aOR 2.23, 95% CI: 1.50-3.31, p < 0.001) and COPD (aOR 1.85, 95% CI: 1.50-2.28, p < 0.001) between ages of 18-39 and 40-64, and thyroid dysfunction (aOR 2.36, 95% CI: 1.60-3.47, p < 0.001) above age 64. CONCLUSIONS: Omicron-infected patients with comorbidities might prolong the VST. The independent risk factors also differ across age ranges, suggesting that providing targeted effective prevention and control guidance and allocating appropriate resources to different populations should be a crucial strategy.

Application of CT quantitative detection of pulmonary lesions in diagnosis and treatment of COVID

OBJECTIVE: To explore the value of CT quantitative detection of pulmonary lesions in diagnosis and treatment of COVID-19. METHODS: A total of 14 patients with COVID-19 who were treated in Quzhou People's Hospital from Jan 2020 to Apr 2020 were enrolled in the study and received chest scanning examination at the admission, progression stage of disease, recovery stage and absorption stage, the CT thin-slice scan data were imported into Toshiba Vitrea FX workstation, and the total volume, maximum diameter, maximum density and average density of pulmonary lesions were measured by using the quantitative detection function of lung lesions, and the distribution and scope of lesions were displayed in three dimensions by means of visualization technology. RESULTS: The results of the four times of CT examination showed that there were between-group significant differences in the volume of lesions, maximum density and maximum diameter during the different time periods. The volume of lesions, maximum density and maximum diameter of the patients who received the second CT examination were significantly higher than those of the patients who received other three times of CT examination;the volume of lesions, maximum density and maximum diameter of the patients who received the fourth CT examination were significantly lower than those of the patients who received other three times of CT examination(P < 0.05). CONCLUSION: The CT quantitative detection technology of lung lesions can quantify the information of lung lesions such as the total volume, maximum diameter, density, distribution and scope, continuously observe the course of disease and indicate the stage of lesions for clinicians so as to adjust the treatment program in a timely manner.

Antiviral agents, glucocorticoids, antibiotics, and intravenous immunoglobulin in 1142 patients with coronavirus disease 2019: a systematic review and meta-analysis.

INTRODUCTION: The treatment effects of antiviral agents, glucocorticoids, antibiotics, and intravenous immunoglobulin are controversial in patients with coronavirus disease 2019 (COVID­19). OBJECTIVES: This study aimed to evaluate the impact of drug therapy on the risk of death in patients with COVID­19. PATIENTS AND METHODS: The PubMed, Embase, Web of Science, Cochrane Library, and major preprint platforms were searched to retrieve articles published until April 7, 2020. Subsequently, the effects of specific drug interventions on mortality of patients with COVID­19 were assessed. Odds ratios (ORs) and relative risks (RRs) with corresponding 95% CIs were pooled using random effects models. RESULTS: Of 3421 references, 6 studies were included. Pooled results from retrospective studies revealed that antiviral agents may contribute to survival benefit (OR, 0.42; 95% CI, 0.17-0.99; P = 0.048; I2 = 82.8%), whereas a single randomized controlled trial found no effects of an antiviral agent on mortality (RR, 0.77; 95% CI, 0.45-1.3; P = 0.33). Glucocorticoid use led to an increased risk of death (OR, 2.43; 95% CI, 1.44-4.1; P = 0.001; I2 = 61.9%). Antibiotics did not significantly affect mortality (OR, 1.13; 95% CI, 0.67-1.89; P = 0.64; I2 = 0%). Similarly, intravenous immunoglobulin had a nonsignificant effect on mortality (OR, 2.66; 95% CI, 0.72-9.89; P = 0.14; I2 = 93.1%). CONCLUSIONS: With the varied heterogeneities across interventions, the current evidence indicated a probable survival benefit from antiviral agent use and a harmful effect of glucocorticoids in patients with COVID­19. Neither any of antibiotics nor intravenous immunoglobulin were associated with survival benefit in this population.

Estimation of the reproductive number of novel coronavirus (COVID-19) and the probable outbreak size on the Diamond Princess cruise ship: A data-driven analysis.

BACKGROUNDS: Up to February 16, 2020, 355 cases have been confirmed as having COVID-19 infection on the Diamond Princess cruise ship. It is of crucial importance to estimate the reproductive number (R0) of the novel virus in the early stage of outbreak and make a prediction of daily new cases on the ship. METHOD: We fitted the reported serial interval (mean and standard deviation) with a gamma distribution and applied "earlyR" package in R to estimate the R0 in the early stage of COVID-19 outbreak. We applied "projections" package in R to simulate the plausible cumulative epidemic trajectories and future daily incidence by fitting the data of existing daily incidence, a serial interval distribution, and the estimated R0 into a model based on the assumption that daily incidence obeys approximately Poisson distribution determined by daily infectiousness. RESULTS: The Maximum-Likelihood (ML) value of R0 was 2.28 for COVID-19 outbreak at the early stage on the ship. The median with 95% confidence interval (CI) of R0 values was 2.28 (2.06-2.52) estimated by the bootstrap resampling method. The probable number of new cases for the next ten days would gradually increase, and the estimated cumulative cases would reach 1514 (1384-1656) at the tenth day in the future. However, if R0 value was reduced by 25% and 50%, the estimated total number of cumulative cases would be reduced to 1081 (981-1177) and 758 (697-817), respectively. CONCLUSION: The median with 95% CI of R0 of COVID-19 was about 2.28 (2.06-2.52) during the early stage experienced on the Diamond Princess cruise ship. The future daily incidence and probable outbreak size is largely dependent on the change of R0. Unless strict infection management and control are taken, our findings indicate the potential of COVID-19 to cause greater outbreak on the ship.