Treating patients with COVID-19 is expensive, thus it is essential to identify factors on admission associated with hospital length of stay (LOS) and provide a risk assessment for clinical treatment. To address this, we conduct a retrospective study, which involved patients with laboratory-confirmed COVID-19 infection in Hefei, China and being discharged between January 20 2020 and March 16 2020. Demographic information, clinical treatment, and laboratory data for the participants were extracted from medical records. A prolonged LOS was defined as equal to or greater than the median length of hospitable stay. The median LOS for the 75 patients was 17 days (IQR 13–22). We used univariable and multivariable logistic regressions to explore the risk factors associated with a prolonged hospital LOS. Adjusted odds ratios (aORs) and 95% confidence intervals (CIs) were estimated. The median age of the 75 patients was 47 years. Approximately 75% of the patients had mild or general disease. The univariate logistic regression model showed that female sex and having a fever on admission were significantly associated with longer duration of hospitalization. The multivariate logistic regression model enhances these associations. Odds of a prolonged LOS were associated with male sex (aOR 0.19, 95% CI 0.05–0.63, p = 0.01), having fever on admission (aOR 8.27, 95% CI 1.47–72.16, p = 0.028) and pre-existing chronic kidney or liver disease (aOR 13.73 95% CI 1.95–145.4, p = 0.015) as well as each 1-unit increase in creatinine level (aOR 0.94, 95% CI 0.9–0.98, p = 0.007). We also found that a prolonged LOS was associated with increased creatinine levels in patients with chronic kidney or liver disease (p < 0.001). In conclusion, female sex, fever, chronic kidney or liver disease before admission and increasing creatinine levels were associated with prolonged LOS in patients with COVID-19.

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Background The sudden outbreaking of COVID-19 worldwide has brought into sharp increased burden of economic and treatment in worldwide. All confirmed patients with different severity not only share the limited healthcare systems simultaneously but increase the risk of cross-infection among patients and health care workers. Hence, effective separation of critical COVID-19 patients from the common COVID-19 will be the key to success for ensuring critical patients to obtain treatment priorities and avoiding cross-infections in the hospital. Methods: A total of 105 patients with complete medical records were collected, including 84 blood samples of patients who confirmed in the First Affiliated Hospital of the University of Science and Technology at Anhui and 25 blood samples of patients in two hospitals at Shantou. Series of machine learning tools were introduced to explore and validate the most significant laboratory characteristics. Meanwhile, we compared it to three current popular assessment systems for pneumonia by using three methods, including the AUC index, NRI index and the net benefit. Results: We identified four significant potential laboratory characteristics for the classification of critical patients, including C-reactive protein, albumin, globulin, and sodium levels. The results also suggested the accurate and prediction efficacy of these selected indicators are the highest. Conclusions In conclusion, four easily available and low-cost laboratory characteristics appear to be import predictors of classification in critical patients after hospital admission. They guide therapeutic options and help clinicians make clinical decisions. Hence, we believe that such classification is essential for a more rational allocation scarce medical resource.

To report the rate of symptomatic catheter-related venous thrombosis (CRVT) in surgical intensive care unit patients receiving central venous catheters (CVC) and analyze the disease-related risk factors for symptomatic CRVT in SICU patients. A retrospective analysis was performed on 1643 critically ill patients admitted to the SICU from January 2015 to December 2019. Cases were divided into two groups based on the presence of symptomatic CRVT, and the variables of interest were extracted from the electronic medical record system. Logistic univariate and multivariate regression analyses were used to determine the risk factors of SCRVT. A total of 209 symptomatic CRVT events occurred among 2114 catheters. Multivariate analysis showed that trauma (odds ratio [OR], 2.046; 95% confidence interval [CI] [1.325-3.160], P = 0.001), major surgery (OR, 2.457; 95% CI [1.641-3.679], P = 0.000), and heart failure (OR, 2.087; 95% CI [1.401-3.111], P = 0.000) were independent risk factors for symptomatic CRVT in SICU. The AUROC for this model was 0.610 (95% CI [0.569-0.651], P=0.000). The incidence rate was 9.89%. For patients hospitalized in the SICU, especially those admitted with these three conditions, thromboprophylaxis and/or mechanical prophylaxis should be actively provided to reduce the occurrence of symptomatic CRVT.