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1.
Heliyon ; 9(5): e16017, 2023 May.
Article in English | MEDLINE | ID: covidwho-2320691

ABSTRACT

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.

2.
Front Cell Infect Microbiol ; 12: 1009894, 2022.
Article in English | MEDLINE | ID: covidwho-2119886

ABSTRACT

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.


Subject(s)
COVID-19 , Humans , Male , Middle Aged , Female , Retrospective Studies , COVID-19/epidemiology , SARS-CoV-2 , Cough , China/epidemiology , Risk Factors , Hospitals , Taste Disorders , Fatigue , Disease Progression
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