Objective To investigate the blood coagulation function in COVID-19 patients, and the correlation between coagulopathy and disease severity. Methods We retrospectively collected 147 clinically diagnosed COVID-19 patients at Wuhan Leishenshan Hospital of Hubei, China. We analyzed the coagulation function in COVID-19 patients through the data including thrombin-antithrombin complex (TAT), α2-plasmininhibitor-plasmin Complex (PIC), thrombomodulin (TM), t-PA/PAI-1 Complex (t-PAIC), prothrombin time (PT), international normalized ratio (INR), activated partial thromboplastin time (APTT), fibrinogen (FIB), thrombin time (TT), D-Dimer (DD), and platelet (PLT). Result The levels of TAT, PIC, TM, t-PAIC, PT, INR, FIB, and DD in COVID-19 patients were higher than health controls (p<0.05), and also higher in the patients with thrombotic disease than without thrombotic disease (p<0.05). What’s more, the patients with thrombotic disease had a higher case-fatality (p<0.05). TAT, PIC, TM, t-PAIC, PT, INR, APTT, FIB, DD, and PLT were also found correlated with disease severity. Meanwhile, we found that there were significant difference in TAT, TM, t-PAIC, PT, INR, APTT, DD, and PLT in the death and survival group. Further using univariate and multivariate logistic regression analysis also found that t-PAIC and DD were independent risk factors for death in patients and are excellent predicting the mortality risk of COVID-19. Conclusion Most COVID-19 patients with inordinate coagulation systems, dynamic monitoring of coagulation parameters might be a key in the control of COVID-19 death.

Objective: To investigate the blood coagulation function in COVID-19 patients, and the correlation between coagulopathy and disease severity.

As a crucial biophysical property, red blood cell (RBC) deformability is pathologically altered in numerous disease states, and biochemical and structural changes occur over time in stored samples of otherwise normal RBCs. However, there is still a gap in applying it further to point-of-care blood devices due to the large external equipment (high-resolution microscope and microfluidic pump), associated operational difficulties, and professional analysis. Herein, we revolutionarily propose a smart optofluidic system to provide a differential diagnosis for blood testing via precise cell biophysics property recognition both mechanically and morphologically. Deformation of the RBC population is caused by pressing the hydrogel via an integrated mechanical transfer device. The biophysical properties of the cell population are obtained by the designed smartphone algorithm. Artificial intelligence-based modeling of cell biophysics properties related to blood diseases and quality was developed for online testing. We currently achieve 100% diagnostic accuracy for five typical clinical blood diseases (90 megaloblastic anemia, 78 myelofibrosis, 84 iron deficiency anemia, 48 thrombotic thrombocytopenic purpura, and 48 thalassemias) via real-world prospective implementation; furthermore, personalized blood quality (for transfusion in cardiac surgery) monitoring is achieved with an accuracy of 96.9%. This work suggests a potential basis for next-generation blood smart health care devices.

Cytokines play pleiotropic, antagonistic, and collaborative in viral disease. The high morbidity and mortality of coronavirus disease 2019 (COVID-19) make it a significant threat to global public health. Elucidating its pathogenesis is essential to finding effective therapy. A retrospective study was conducted on 71 patients hospitalized with COVID-19. Data on cytokines, T lymphocytes, and other clinical and laboratory characteristics were collected from patients with variable disease severity. The effects of cytokines on the overall survival (OS) and event-free survival (EFS) of patients were analyzed. The critically severe and severe patients had higher infection indexes and significant multiple organ function abnormalities than the mild patients ( P <0.05). IL-6 and IL-10 were significantly higher in the critically severe patients than in the severe and mild patients ( P <0.05). IL-6 and IL-10 were closely associated with white blood cells, neutrophils, T lymphocyte subsets, D-D dimer, blood urea nitrogen, complement C1q, procalcitonin C-reactive protein. Moreover, the IL-6 and IL-10 levels were closely correlated to dyspnea and dizziness ( P <0.05). The patients with higher IL-10 levels had shorter OS than the group with lower levels ( P <0.05). The older patients with higher levels of single IL-6 or IL-10 tended to have shorter EFS ( P <0.05), while the patients who had more elevated IL-6 and IL-10 had shorter OS ( P <0.05). The Cox proportional hazard model revealed that IL-6 was the independent factor affecting EFS. IL-6 and IL-10 play crucial roles in COVID-19 prognosis.

Severe fever with thrombocytopenia syndrome (SFTS) is a novel tick-borne infectious disease caused by a new type of SFTS virus (SFTSV). Here, a longitudinal sampling study is conducted to explore the differences in transcript levels after SFTSV infection, and to characterize the transcriptomic and epigenetic profiles of hospitalized patients. The results reveal significant changes in the mRNA expression of certain genes from onset to recovery. Moreover, m6A-seq reveals that certain genes related with immune regulation may be regulated by m6A. Besides the routine tests such as platelet counts, serum ALT and AST levels testing, distinct changes in myocardial enzymes, coagulation function, and inflammation are well correlated with the clinical data and sequencing data, suggesting that clinical practitioners should monitor the above indicators to track disease progression and guide personalized treatment. In this study, the transcript changes and RNA modification may lend a fresh perspective to our understanding of the SFTSV and play a significant role in the discovery of drugs for effective treatment of this disease.