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 Patients with severe COVID‐19 are more likely to develop adverse outcomes with a huge medical burden. We aimed to investigate whether a shorter symptom onset to admission time (SOAT) could improve outcomes of COVID‐19 patients. Methods A single‐center retrospective study combined with a meta‐analysis was performed. The meta‐analysis identified studies published between 1 December 2019 and 15 April 2020. Additionally, clinical data of COVID‐19 patients diagnosed between January 20 and February 20, 2020, at the First Affiliated Hospital of the University of Science and Technology of China were retrospectively analyzed. SOAT and severity of illness in patients with COVID‐19 were used as effect measures. The random‐effects model was used to analyze the heterogeneity across studies. Propensity score matching was applied to adjust for confounding factors in the retrospective study. Categorical data were compared using Fisher's exact test. We compared the differences in laboratory characteristic varied times using a two‐way nonparametric, Scheirer–Ray–Hare test. Results In a meta‐analysis, we found that patients with adverse outcomes had a longer SOAT ( I 2 = 39%, mean difference 0.88, 95% confidence interval = 0.47–1.30). After adjusting for confounding factors, such as age, complications, and treatment options, the retrospective analysis results also showed that severe patients had longer SOAT (mean difference 1.13 [1.00, 1.27], p = 0.046). Besides, most biochemical marker levels improved as the hospitalization time lengthened without the effect of disease severity or associated treatment ( p < 0.001). Conclusion Shortening the SOAT may help reduce the possibility of mild patients with COVID‐19 progressing to severe illness.

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.

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