Background: We aimed to clarify high-risk factors for coronavirus disease 2019 (COVID-19) with multivariate analysis and establish a predictive model of disease progression to help clinicians better choose a therapeutic strategy. Methods: All consecutive patients with COVID-19 admitted to Fuyang Second People’s Hospital or the Fifth Medical Center of Chinese PLA General Hospital between 20 January and 22 February 2020 were enrolled and their clinical data were retrospectively collected. Multivariate Cox regression was used to identify risk factors associated with progression, which were then were incorporated into a nomogram to establish a novel prediction scoring model. ROC was used to assess the performance of the model. Results: Overall, 208 patients were divided into a stable group (n = 168, 80.8%) and a progressive group (n = 40,19.2%) based on whether their conditions worsened during hospitalization. Univariate and multivariate analyses showed that comorbidity, older age, lower lymphocyte count, and higher lactate dehydrogenase at presentation were independent high-risk factors for COVID-19 progression. Incorporating these 4 factors, the nomogram achieved good concordance indexes of .86 (95% confidence interval [CI], .81–.91) and well-fitted calibration curves. A novel scoring model, named as CALL, was established; its area under the ROC was .91 (95% CI, .86–.94). Using a cutoff of 6 points, the positive and negative predictive values were 50.7% (38.9–62.4%) and 98.5% (94.7–99.8%), respectively. Conclusions: Using the CALL score model, clinicians can improve the therapeutic effect and reduce the mortality of COVID-19 with more accurate and efficient use of medical resources.

Previous circular RNA (circRNA) microarray analyses have uncovered an abnormal expression of hsa_circ_0070963 in hepatic stellate cells (HSCs). However, the specific role of hsa_circ_0070963 in liver fibrosis remains unknown. Here, we show that hsa_circ_0070963 inhibits liver fibrosis via regulation of miR-223-3p and LEMD3. Moreover, we demonstrated that hsa_circ_0070963 levels were reduced during liver fibrosis while restoring hsa_circ_0070963 levels abolished HSC activation, with a reduction in α-SMA and type I collagen levels both in vitro and in vivo. Furthermore, hsa_circ_0070963 overexpression suppressed both cell proliferation and the cell cycle of HSCs. MiR-223-3p was confirmed as a target of hsa_circ_0070963 and was shown to be involved in the effects of hsa_circ_0070963 on HSC activation. Furthermore, LEMD3 was confirmed as a target of miR-223-3p and was shown to be responsible for the activation of HSCs. The interactions between hsa_circ_0070963, miR-223-3p, and LEMD3 were validated via bioinformatic analysis, luciferase reporter assays, and rescue experiments. Collectively, hsa_circ_0070963 appeared to function as a miR-223-3p sponge that inhibited HSC activation in liver fibrosis via regulation of miR-223-3p and LEMD3. Therefore, hsa_circ_0070963 may serve as a potential therapeutic target for liver fibrosis.

Clinical and laboratory data were collected and analysed from patients with Ebola virus disease (EVD) in Jui Government Hospital in Freetown, Sierra Leone, where patients with EVD were received and/or treated from October 1, 2014 to March 21, 2015 during the West Africa EVD outbreak. The study admitted 285 patients with confirmed EVD and followed them up till the endpoint (recovery or death). EVD was confirmed by quantitative RT-PCR assays detecting blood Ebola virus (EBOV). Among the 285 lab-confirmed EVD cases in Jui Government Hospital, 146 recovered and 139 died, with an overall survival rate of 51.23 %. Patients under the age of 6 years had a lower survival rate (37.50 %). Most non-survivors (79.86 %) died within 7 days after admission and the mean hospitalization time for non-survivors was 5.56 ± 6.11 days. More than half survivors (63.69 %) turned blood EBOV negative within 3 weeks after admission and the mean hospitalization time for survivors was 20.38 ± 7.58 days. High blood viral load (≥106 copies/ml) was found to be predictive of the non-survival outcome as indicated by the Receiver Operating Characteristic (ROC) curve analysis. The probability of patients’ survival was less than 15 % when blood viral load was greater than 106 copies/ml. Multivariate analyses showed that blood viral load (P = 0.005), confusion (P = 0.010), abdominal pain (P = 0.003), conjunctivitis (P = 0.035), and vomiting (P = 0.004) were factors independently associated with the outcomes of EVD patients. Most death occurred within 1 week after admission, and patients at the age of 6 or younger had a lower survival rate. Most surviving patients turned blood EBOV negative within 1–4 weeks after admission. Factors such as high blood viral load, confusion, abdominal pain, vomiting and conjunctivitis were associated with poor prognosis for EVD patients.