Different effects of vaccine on VST in critical and non-critical COVID-19 patients: A retrospective study of 363 cases.

Aim: To explore the risk factors of prolonged viral shedding time (VST) in critical/non-critical COVID-19 patients during hospitalization. Methods: In this retrospective study, we enrolled 363 patients with SARS-CoV-2 infection admitted in a designated hospital during the COVID-19 outbreak in Nanjing Lukou International Airport. Patients were divided into critical (n = 54) and non-critical (n = 309) groups. We analyzed the relationship between the VST and demographics, clinical characteristics, medications, and vaccination histories, respectively. Results: The median duration of VST was 24 d (IQR, 20-29) of all patients. The VST of critical cases was longer than non-critical cases (27 d, IQR, 22.0-30.0 vs. 23 d, IQR 20-28, P < 0.05). Cox proportional hazards model showed that ALT (HR = 1.610, 95%CI 1.186-2.184, P = 0.002) and EO% (HR = 1.276, 95%CI 1.042-1.563, P = 0.018) were independent factors of prolonged VST in total cases; HGB (HR = 0.343, 95%CI 0.162-0.728, P = 0.005) and ALP (HR = 0.358, 95%CI 0.133-0.968, P = 0.043) were independent factors of prolonged VST in critical cases, while EO% (HR = 1.251, 95%CI 1.015-1.541, P = 0.036) was the independent factor of prolonged VST in non-critical cases. Vaccinated critical cases showed higher levels of SARS-CoV-2-IgG (1.725 S/CO, IQR 0.3975-28.7925 vs 0.07 S/CO, IQR 0.05-0.16, P < 0.001) and longer VSTs (32.5 d, IQR 20.0-35.25 vs 23 d, IQR 18.0-30.0, P = 0.011) compared with unvaccinated critical patients. Fully vaccinated non-critical cases, however, presented higher levels of SARS-CoV-2-IgG (8.09 S/CO, IQR 1.6975-55.7825 vs 0.13 S/CO IQR 0.06-0.41, P < 0.001) and shorter VSTs (21 d, IQR 19.0-28.0 vs 24 d, IQR 21.0-28.5, P = 0.013) compared with unvaccinated non-critical patients. Conclusions: Our results suggested that risk factors of prolonged VST were different between critical and non-critical COVID-19 patients. Increased level of SARS-CoV-2-IgG and vaccination did not shorten the VST and hospital stay in critical COVID-19 patients.

Clinical characteristics and analysis of risk factors for disease progression of patients with SARS-CoV-2 Omicron variant infection: A retrospective study of 25207 cases in a Fangcang hospital.

Objectives: To summarize the clinical characteristics of patients infected by SARS-CoV-2 omicron variant and explore the risk factors affecting the progression in a Fangcang hospital, Shanghai, China. Methods: A total of 25,207 patients were retrospectively enrolled. We described the clinical characteristics and performed univariate and multivariate logistic regression analysis to identify the risk factors for non-severe to severe COVID-19 or death. Results: According to the outcomes, there were 39 severe patients (including 1 death) and 25,168 non-severe patients enrolled in this study. Among the 25,207 cases, the median age was 45 years (IQR 33-54), and 65% patients were male. Cough (44.5%) and expectoration (38.4%) were the most two common symptoms. Hypertension (10.4%) and diabetes (3.5%) were most two common comorbidities. Most patients (81.1%) were fully vaccinated. The unvaccinated and partially vaccinated patients were 15.1% and 3.9%, respectively. The length of viral shedding time was six days (IQR 4-9) in non-severe patients. Multivariate logistic regression analysis suggested that age (OR=1.062, 95%CI 1.034-1.090, p<0.001), fever (OR=2.603, 95%CI 1.061-6.384, p=0.037), cough (OR=0.276, 95%CI 0.119-0.637, p=0.003), fatigue (OR=4.677, 95%CI 1.976-11.068, p<0.001), taste disorders (OR=14.917, 95%CI 1.884-118.095, p=0.010), and comorbidity (OR=2.134, 95%CI 1.059-4.302, p=0.034) were predictive factors for deterioration of SARS-CoV-2 omicron variant infection. Conclusions: Non-critical patients have different clinical characteristics from critical patients. Age, fever, cough, fatigue, taste disorders, and comorbidity are predictors for the deterioration of SARS-CoV-2 omicron variant infection.

Effect of SSA1 on biological behavior of gastric cancer cells and its application in diagnosis of gastric cancer / 医学研究生学报

Objective Currently, there is a lack of clinical precise methods in the early diagnosis of gastric cancer. The article aimed to investigate the effect of serum amyloid A1 (SAA1) on the biological behavior of gastric cancer cells and its role in the early diagnosis of gastric cancer. Methods We collected 82 specimens of gastric cancer patients and 30 specimens of healthy controls. Cultured human gastric cancer SGC-7901 cells were randomly divided into SAA1-siRNA group, NC-siRNA group and blank control group. SAA1-siRNA, NC-siRNA and transfection reagent were transfected into the SGC-7901, and the expression of SAA1 protein in each group was detected by western blot 48 h later. Cell viability in each group was detected by CCK8 and cell invasion ability was measured by Transwell chamber. The ROC curve was used to analyze the efficacy of SAA1 in the diagnosis of gastric cancer. The expression of SAA1 was detected by ELISA, and the correlation between SAA1 and clinicopathological factors was analyzed. Results The SAA1 protein expression in SAA1-siRNA group [(1.12±0.12)μg] was significantly lower than those in NC-siRNA group[(1.97±0.13)μg] and blank control group[(2.09±0.28)μg] (P<0.05). The cell viability of CCK8 assay showed that the cell viability of SAA1-siRNA group(52.44±12.30) was significantly lower than those of NC-siRNA group(77.16±7.70) and blank control group (97.78±11.80). Transwell test results showed that the migration ability of SAA1-siRNA group(22.21±6.53) was significantly lower than those of NC-siRNA group(52.02±4.29) and blank control group(54.10±5.40)(P<0.05). The expression of SAA1 in patients with gastric cancer was (50.03 ± 20.89μg / mL) significantly higher than those of healthy controls (24.06 ± 10.72μg / mL), and the difference was statistically significant (P <0.05). ROC curve analysis showed that the AUC of SAA1 diagnosis of gastric cancer was 0.791 (95% CI: 0.701~0.880), the detection threshold was 31.97μg, and the diagnostic sensitivity and specificity were 0.659 and 0.833, respectively. There was no significant correlation between the expression of SAA1 and gender, age and tumor metastasis of gastric cancer (P> 0.05), while it was correlated with tumor maximum diameter and invasion degree, and increased with tumor invasion degree (P< 0.05). Conclusion The expression of SAA1 in gastric cancer patients increases significantly, which can be used as a new potential marker for the diagnosis of gastric cancer.