3044 Cases reveal important prognosis signatures of COVID-19 patients.

Critical patients and intensive care unit (ICU) patients are the main population of COVID-19 deaths. Therefore, establishing a reliable method is necessary for COVID-19 patients to distinguish patients who may have critical symptoms from other patients. In this retrospective study, we firstly evaluated the effects of 54 laboratory indicators on critical illness and death in 3044 COVID-19 patients from the Huoshenshan hospital in Wuhan, China. Secondly, we identify the eight most important prognostic indicators (neutrophil percentage, procalcitonin, neutrophil absolute value, C-reactive protein, albumin, interleukin-6, lymphocyte absolute value and myoglobin) by using the random forest algorithm, and find that dynamic changes of the eight prognostic indicators present significantly distinct within differently clinical severities. Thirdly, our study reveals that a model containing age and these eight prognostic indicators can accurately predict which patients may develop serious illness or death. Fourthly, our results demonstrate that different genders have different critical illness rates compared with different ages, in particular the mortality is more likely to be attributed to some key genes (e.g. ACE2, TMPRSS2 and FURIN) by combining the analysis of public lung single cells and bulk transcriptome data. Taken together, we urge that the prognostic model and first-hand clinical trial data generated in this study have important clinical practical significance for predicting and exploring the disease progression of COVID-19 patients.

Upregulated IL-6 Indicates a Poor COVID-19 Prognosis: A Call for Tocilizumab and Convalescent Plasma Treatment.

A comprehensive understanding of the dynamic changes in interleukin-6 (IL-6) levels is essential for monitoring and treating patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). By analyzing the correlations between IL-6 levels and health conditions, underlying diseases, several key laboratory detection indices, and the prognosis of 1,473 patients with the coronavirus disease 2019 (COVID-19), the role of IL-6 during SARS-CoV-2 infection was demonstrated. Our results indicated that IL-6 levels were closely related to age, sex, body temperature, oxygen saturation (SpO2) of blood, and underlying diseases. As a stable indicator, the changes in IL-6 levels could indicate the inflammatory conditions during a viral infection. Two specific treatments, namely, tocilizumab and convalescent plasma therapy (CPT), decreased the level of IL-6 and relieved inflammation. CPT has an important role in the therapy for patients with critical COVID-19. We also found that patients with IL-6 levels, which were 30-fold higher than the normal level, had a poor prognosis compared to patients with lower levels of IL-6.

Potential False-Positive and False-Negative Results for COVID-19 IgG/IgM Antibody Testing After Heat-Inactivation.

Objectives: With the worldwide spread of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), various antibody detection kits have been developed to test for SARS-CoV-2- specific IgG, IgM, and total antibody. However, the use of different testing methods under various heat-inactivation conditions might affect the COVID-19 detection results. Methods: Seven different antibody detection kits produced by four manufacturers for detection of SARS-CoV-2 IgG, IgM, and total antibody were tested at Wuhan Huoshenshan Hospital, China. Most of the kits used the indirect immunity, capture, and double-antigen sandwich methods. The effects of various heat-inactivation conditions on SARS-CoV-2-specific IgG, IgM, and total antibody detection were analyzed for the different test methods. Results: Using the indirect immunity method, values for SARS-CoV-2 IgG antibody significantly increased and those for IgM antibody decreased with increasing temperature of heat-inactivation using indirect immunity method. However, values for SARS-CoV-2 IgM and total antibody showed no change when the capture and double-antigen sandwich methods were used. The changes in IgG and IgM antibody values with the indirect immunity method indicated that heat-inactivation could affect COVID-19 detection results obtained using this method. In particular, 18 (22.2%) SARS-CoV-2 IgM positive samples were detected as negative with heat-inactivation at 65°C for 30 min, and one (25%) IgG negative sample was detected as positive after heat-inactivation at 56°C for 60 min and 60°C for 30 min. Conclusions: Heat-inactivation could increase SARS-CoV-2 IgG antibody values, and decrease IgM antibody values, causing potential false-positive or false-negative results for COVID-19 antibody detection using the indirect immunity method. Thus, before conducting antibody testing, the testing platforms should be evaluated in accordance with the relevant requirements to ensure accurate COVID-19 detection results.