Exploration on the influencing factors and establishment of a risk model for the time of virus turning negative of asymptomatic or mild Covid-19 (preprint)

Background: Patients are allowed to be released from quarantine after virus turns negative for asymptomatic or mild covid-19. Factors affecting the negative conversion of nucleic acid are unknown. Methods. This study included asymptomatic or mild covid-19 patients quarantined in Shanghai shelter hospital from April to May 2022. They were tested daily for SARS-CoV-2 nucleic acid. The clinical characteristics were collected. Univariate and multivariate Cox regression were used to explore the relationship between clinical characteristics and the time of virus turning negative (TTN), finally a risk model was established. Results. A total of 7836 patients enrolled were divided into training or validation set randomly. In training set, age (≥40 Y), symptoms (yes) , diabetes (yes) and vaccination status(yes) were correlated with TTN. We used HR values of the above factors in multivariate Cox regression as risk coefficients to build a risk model for predicting TTN. TTN of patients with high risk score was longer than with low risk score. This risk model has been well validated in the validation set and the complete set. Conclusions. Our study found that age, symptoms, diabetes and vaccination status were correlated with the TTN,and we first build a risk model to predict TTN in asymptomatic or mild Covid-19.

Risk factors of mortality for intensive care COVID-19 patients: A retrospective cohort study. (preprint)

Aims: To identify the risk factors of mortality for coronavirus disease 19 (COVID-19) patients admitted to intensive care units (ICU), we conducted a retrospective analysis.Methods: The demographic characteristics, laboratory findings and chest X-ray data of COVID-19 patients admitted to ICU of Huoshenshan Hospital from February 10 to April 10, 2020 were retrospectively analyzed. Student's t test and chi-square test were used to compare continuous variables, categorical variables respectively. Logistic regression model was used to seek risk factors of mortality.Results: A total of 57 patients (38 males and 19 females) were included in this retrospective study, including 20 patients in deceased group and 37 patients in surviving group. Leukocyte count, neutrophil count, lymphocyte count, eosinophil count, neutrophil-to-lymphocyte ratio (NLR), urea nitrogen, lactate dehydrogenase (LDH), interleukin-6 (IL-6), C-reactive protein (CRP), arterial partial pressure of oxygen/oxygen concentration (PaO2/FiO2) and imaging findings were statistically different between the two groups. The multivariate logistic regression analysis identified IL-6 and PaO2/FiO2 as independent risk factors of mortality. The area of under curves (AUC) of IL-6 and PaO2/FiO2 were 0.9 (95%CI:0.823-0.977, p<0.0001) and 0.865 (95%CI:0.774-0.956, p<0.0001) respectively. The cut-off value of IL-6 was 25.69 pg/mL, the sensitivity was 95% and the specificity was 75.7%, while the cut-off value of PaO2/FiO2 was 167.79 mmHg, the sensitivity was 75.7% and the specificity was 85%.Conclusion: Clinicians should pay enough attention to IL-6 and PaO2/FiO2, especially when IL-6>25.69 pg/ml and PaO2/FiO2<167.79 mmHg, and take active intervention measures as early as possible.