Characteristics of immune and inflammatory responses among different age groups of pediatric patients with COVID-19 in China.

BACKGROUND: Severe cases of coronavirus disease 2019 (COVID-19) among pediatric patients are more common in children less than 1 year of age. Our aim is to address the underlying role of immunity and inflammation conditions among different age groups of pediatric patients. METHODS: We recruited pediatric patients confirmed of moderate COVID-19 symptoms, admitted to Wuhan Children's Hospital from January 28th to April 1st in 2020. Patients were divided into four age groups (≤ 1, 1-6, 7-10, and 11-15 years). Demographic information, clinical characteristics, laboratory results of lymphocyte subsets test, immune and inflammation related markers were all evaluated. RESULTS: Analysis included 217/241 (90.0%) of patients with moderate clinical stage disease. Average recovery time of children more than 6 years old was significantly shorter than of children younger than 6 years (P = 0.001). Reduced neutrophils and increased lymphocytes were significantly most observed among patients under 1 year old (P < 0.01). CD19+ B cells were the only significantly elevated immune cells, especially among patients under 1 year old (cell proportion: n = 12, 30.0%, P < 0.001; cell count: n = 13, 32.5%, P < 0.001). While, low levels of immune related makers, such as immunoglobulin (Ig) G (P < 0.001), IgA (P < 0.001), IgM (P < 0.001) and serum complement C3c (P < 0.001), were also mostly found among patients under 1 year old, together with elevated levels of inflammation related markers, such as tumor necrosis factor γ (P = 0.007), interleukin (IL)-10 (P = 0.011), IL-6 (P = 0.008), lactate dehydrogenase (P < 0.001), and procalcitonin (P = 0.007). CONCLUSION: The higher rate of severe cases and long course of COVID-19 among children under 1 year old may be due to the lower production of antibodies and serum complements of in this age group.

Management of immune checkpoint therapy for patients with cancer in the face of COVID-19.

The COVID-19 outbreak caused by SARS-CoV-2 challenges the medical system by interfering with routine therapies for many patients with chronic diseases. In patients with cancer receiving immune checkpoint inhibitors (ICIs), difficulties also arise from the incomplete understanding of the intricate interplay between their routine treatment and pathogenesis of the novel virus. By referring to previous ICI-based investigations, we speculate that ICIs themselves are not linked to high-infection risks of respiratory diseases or inflammation-related adverse effects in patients with cancer. Moreover, ICI treatment may even enhance coronavirus clearance in some patients with malignant tumor by boosting antiviral T-cell responsiveness. However, the 'explosive' inflammation during COVID-19 in some ICI-treated patients with cancer was illustrated as exuberant immunopathological damage or even death. In case of the COVID-19 immunopathogenesis fueled by ICIs, we propose a regular monitor of pathogenic T-cell subsets and their exhaustion marker expression (eg, Th17 and interleukin (IL)-6-producing Th1 subsets with surface programmed death 1 expression) to guide the usage of ICI. Here we aimed to address these considerations, based on available literature and experience from our practice, that may assist with the decision-making of ICI administration during the pandemic.

Tracing asymptomatic SARS-CoV-2 carriers among 3674 hospital staff:a cross-sectional survey.

BACKGROUND: Asymptomatic carriers were positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) without developing symptoms, which might be a potential source of infection outbreak. Here, we aim to clarify the epidemiologic and influencing factors of asymptomatic carriers in the general population. METHODS: In our hospital, all hospital staff have received throat swab RT-PCR test, plasma COVID-19 IgM/IgG antibodies test and chest CT examination. We analyzed the correlation between infection rates and gender, age, job position, work place and COVID-19 knowledge training of the staff. After that, all asymptomatic staff were re-examined weekly for 3 weeks. FINDINGS: A total of 3764 hospital staff were included in this single-center cross-sectional study. Among them, 126 hospital staff had abnormal findings, and the proportion of asymptomatic infection accounted for 0.76% (28/3674). There were 26 staff with IgM+, 73 with IgG+, and 40 with ground glass shadow of chest CT. Of all staff with abnormal findings, the older they are, the more likely they are to be the staff with abnormal results, regardless of their gender. Of 3674 hospital staff, the positive rate of labor staff is obviously higher than that of health care workers (HCWs) and administrative staff (P<0.05). In the course of participating in the treatment of COVID-19, there was no statistically significant difference in positive rates between high-risk departments and low-risk departments (P>0.05). The positive rate of HCWs who participated in the COVID-19 knowledge training was lower than those did not participate in early training (P <0.01). Importantly, it was found that there was no statistical difference between the titers of IgM antibody of asymptomatic infections and confirmed patients with COVID-19 in recovery period (P>0.05). During 3 weeks follow-up, all asymptomatic patients did not present the development of clinical symptoms or radiographic abnormalities after active intervention in isolation point. INTERPRETATION: To ensure the safety of resumption of work, institutions should conduct COVID-19 prevention training for staff and screening for asymptomatic patients, and take quarantine measures as soon as possible in areas with high density of population. FUNDING: The Key Project for Anti-2019 novel Coronavirus Pneumonia from the Ministry of Science and Technology, China; Wuhan Emergency Technology Project of COVID-19 epidemic, China.

Prominent Hypercoagulability Associated With Inflammatory State Among Cancer Patients With SARS-CoV-2 Infection.

Abnormal coagulation parameters and potential benefits of anticoagulant therapy in general population with novel coronavirus pneumonia (COVID-19) have been reported. However, limited data are available on cancer patients. Coagulation indexes and inflammation parameters in 57 cancer patients with SARS-CoV-2 infection with different severity were retrospectively analyzed. We found that D-dimer levels were increased in 33 patients (57.9%, median: 790 ng/mL). Compared with ordinary type patients, severe and critical ill patients had decreased MPV values (P = 0.006), prolonged PT (median: 13.3 vs. 11.5 vs. 11.4 s, P < 0.001), significant higher D-dimer levels (median: 2,400 vs. 940 vs. 280 ng/mL, P < 0.001), higher PCT levels (median: 0.17 vs. 0.055 vs. 0.045 ng/mL, P = 0.002), higher IL-6 (median: 20.6 vs. 2.3 vs. 3.0 pg/mL, P = 0.040), and decreased PaO2 (median: 68 vs. 84 vs. 96 mm Hg, P < 0.001). Importantly, three patients, one severe and two critical ill type, with increased D-dimer survived after anticoagulant therapy with continuous heparin infusion. Increased D-dimer levels positively correlated with increased PCT levels (r = 0.456, P = 0.002) and IL-6 levels (r = 0.501, P = 0.045). A negative correlation between D-dimer levels and PaO2 levels (r = -0.654, P = 0.021) were also existed. Cancer patients with COVID-19 showed prominent hypercoagulability associated with severe inflammation, anticoagulation therapy might be useful to improve the prognosis and should be immediately used after the onset of hypercoagulability.

Scoring systems for predicting mortality for severe patients with COVID-19.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been widely spread and caused tens of thousands of deaths, especially in patients with severe COVID-19. This analysis aimed to explore risk factors for mortality of severe COVID-19, and establish a scoring system to predict in-hospital deaths. METHODS: Patients with COVID-19 were retrospectively analyzed and clinical characteristics were compared. LASSO regression as well as multivariable analysis were used to screen variables and establish prediction model. FINDINGS: A total of 2529 patients with COVID-19 was retrospectively analyzed, and 452 eligible severe COVID-19 were used for finally analysis. In training cohort, the median age was 66•0 years while it was 73•0 years in non-survivors. Patients aged 60-75 years accounted for the largest proportion of infected populations and mortality toll. Anti-SARS-CoV-2 antibodies were monitored up to 54 days, and IgG levels reached the highest during 20-30 days. No differences were observed of antibody levels between severe and non-severe patients. About 60.2% of severe patients had complications. Among acute myocardial injury (AMI), acute kidney injury (AKI) and acute liver injury (ALI), the heart was the earliest injured organ, whereas the time from AKI to death was the shortest. Age, diabetes, coronary heart disease (CHD), percentage of lymphocytes (LYM%), procalcitonin (PCT), serum urea, C reactive protein and D-dimer (DD), were identified associated with mortality by LASSO binary logistic regression. Then multivariable analysis was performed to conclude that old age, CHD, LYM%, PCT and DD remained independent risk factors for mortality. Based on the above variables, a scoring system of COVID-19 (CSS) was established to divide patients into low-risk and high-risk groups. This model displayed good discrimination (AUC=0·919) and calibration (P=0·264). Complications in low-risk and high-risk groups were significantly different (P<0·05). Use of corticosteroids in low-risk groups increased hospital stays by 4·5 days (P=0·036) and durations of disease by 7·5 days (P=0·012) compared with no corticosteroids. INTERPRETATION: Old age, CHD, LYM%, PCT and DD were independently related to mortality. CSS was useful for predicting in-hospital mortality and complications, and it could help clinicians to identify high-risk patients with poor prognosis. FUNDING: This work was supported by the Key Project for Anti-2019 novel Coronavirus Pneumonia from the Ministry of Science and Technology, China (grant number 2020YFC0845500).