Ginsenosides, potential TMPRSS2 inhibitors, a trade-off between the therapeutic combination for anti-PD-1 immunotherapy and the treatment of COVID-19 infection of LUAD patients.

Background: Acting as a viral entry for coronavirus to invade human cells, TMPRSS2 has become a target for the prevention and treatment of COVID-19 infection. Before this, TMPRSS2 has presented biological functions in cancer, but the roles remain controversial and the mechanism remains unelucidated. Some chemicals have been reported to be inhibitors of TMPRSS2 and also demonstrated other pharmacological properties. At this stage, it is important to discover more new compounds targeting TMPRSS2, especially from natural products, for the prevention and treatment of COVID-19 infection. Methods: We analyzed the correlation between TMPRSS2 expression, methylation level, overall survival rate, clinical parameters, biological process, and determined the correlation between TMPRSS2 and tumor-infiltrating lymphocytes in the tumor and adjacent normal tissue of adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively by using various types of bioinformatics approaches. Moreover, we determined the correlation between TMPRSS2 protein level and the prognosis of LUAD and LUSC cohorts by immunohistochemistry assay. Furthermore, the cancer immunome atlas (TCIA) database was used to predict the relationship between the expression of TMPRSS2 and response to programmed cell death protein 1 (PD-1) blocker immunotherapy in lung cancer patients. Finally, the putative binding site of ginsenosides bound to TMPRSS2 protein was built from homology modeling to screen high-potency TMPRSS2 inhibitors. Results: We found that TMPRSS2 recruits various types of immunocytes, including CD8+, CD4+ T cells, B cells and DCs both in LUAD and LUSC patients, and the correlation between TMPRSS2 expression and CD8+ and CD4+ T cells are stronger in LUAD rather than in LUSC, but excludes macrophages and neutrophils in LUAD patient cohorts. These might be the reason that higher mRNA and protein levels of TMPRSS2 are associated with better prognosis in LUAD cohorts rather than in LUSC cohorts. Furthermore, we found that TMPRSS2 was positively correlated with the prognosis in patient nonresponse to anti-PD-1 therapy. Therefore, we made an inference that increasing the expression level of TMPRSS2 may improve the anti-PD-1 immunotherapy efficacy. Finally, five ginsenosides candidates with high inhibition potency were screened from the natural chemical library to be used as TMPRSS2 inhibitors. Conclusion: All these may imply that TMPRSS2 might be a novel prognostic biomarker and serve as a potential immunomodulator target of immunotherapy combination therapies in LUAD patients nonresponse to anti-PD-1 therapy. Also, these findings may suggest we should pay more attention to LUAD patients, especially those infected with COVID-19, who should avoid medicating TMPRSS2 inhibitors, such as ginsenosides to gain prophylactic and therapeutic benefits against COVID-19.

Identification of COVID-19 severity biomarkers based on feature selection on single-cell RNA-Seq data of CD8+ T cells.

The global outbreak of the COVID-19 epidemic has become a major public health problem. COVID-19 virus infection triggers a complex immune response. CD8+ T cells, in particular, play an essential role in controlling the severity of the disease. However, the mechanism of the regulatory role of CD8+ T cells on COVID-19 remains poorly investigated. In this study, single-cell gene expression profiles from three CD8+ T cell subtypes (effector, memory, and naive T cells) were downloaded. Each cell subtype included three disease states, namely, acute COVID-19, convalescent COVID-19, and unexposed individuals. The profiles on each cell subtype were individually analyzed in the same way. Irrelevant features in the profiles were first excluded by the Boruta method. The remaining features for each CD8+ T cells subtype were further analyzed by Max-Relevance and Min-Redundancy, Monte Carlo feature selection, and light gradient boosting machine methods to obtain three feature lists. These lists were then brought into the incremental feature selection method to determine the optimal features for each cell subtype. Their corresponding genes may be latent biomarkers to determine COVID-19 severity. Genes, such as ZFP36, DUSP1, TCR, and IL7R, can be confirmed to play an immune regulatory role in COVID-19 infection and recovery. The results of functional enrichment analysis revealed that these important genes may be associated with immune functions, such as response to cAMP, response to virus, T cell receptor complex, T cell activation, and T cell differentiation. This study further set up different gene expression pattens, represented by classification rules, on three states of COVID-19 and constructed several efficient classifiers to distinguish COVID-19 severity. The findings of this study provided new insights into the biological processes of CD8+ T cells in regulating the immune response.

Corticosteroid treatment in severe patients with SARS-CoV-2 and chronic HBV co-infection: a retrospective multicenter study.

BACKGROUND: The impact of corticosteroids on patients with severe coronavirus disease 2019 (COVID-19)/chronic hepatitis B virus (HBV) co-infection is currently unknown. We aimed to investigate the association of corticosteroids on these patients. METHODS: This retrospective multicenter study screened 5447 confirmed COVID-19 patients hospitalized between Jan 1, 2020 to Apr 18, 2020 in seven centers in China, where the prevalence of chronic HBV infection is moderate to high. Severe patients who had chronic HBV and acute SARS-cov-2 infection were potentially eligible. The diagnosis of chronic HBV infection was based on positive testing for hepatitis B surface antigen (HBsAg) or HBV DNA during hospitalization and a medical history of chronic HBV infection. Severe patients (meeting one of following criteria: respiratory rate > 30 breaths/min; severe respiratory distress; or SpO2 ≤ 93% on room air; or oxygen index < 300 mmHg) with COVID-19/HBV co-infection were identified. The bias of confounding variables on corticosteroids effects was minimized using multivariable logistic regression model and inverse probability of treatment weighting (IPTW) based on propensity score. RESULTS: The prevalence of HBV co-infection in COVID-19 patients was 4.1%. There were 105 patients with severe COVID-19/HBV co-infections (median age 62 years, 57.1% male). Fifty-five patients received corticosteroid treatment and 50 patients did not. In the multivariable analysis, corticosteroid therapy (OR, 6.32, 95% CI 1.17-34.24, P = 0.033) was identified as an independent risk factor for 28-day mortality. With IPTW analysis, corticosteroid treatment was associated with delayed SARS-CoV-2 viral RNA clearance (OR, 2.95, 95% CI 1.63-5.32, P < 0.001), increased risk of 28-day and in-hospital mortality (OR, 4.90, 95% CI 1.68-14.28, P = 0.004; OR, 5.64, 95% CI 1.95-16.30, P = 0.001, respectively), and acute liver injury (OR, 4.50, 95% CI 2.57-7.85, P < 0.001). Methylprednisolone dose per day and cumulative dose in non-survivors were significantly higher than in survivors. CONCLUSIONS: In patients with severe COVID-19/HBV co-infection, corticosteroid treatment may be associated with increased risk of 28-day and in-hospital mortality.

Identification of methylation signatures and rules for predicting the severity of SARS-CoV-2 infection with machine learning methods.

Patients infected with SARS-CoV-2 at various severities have different clinical manifestations and treatments. Mild or moderate patients usually recover with conventional medical treatment, but severe patients require prompt professional treatment. Thus, stratifying infected patients for targeted treatment is meaningful. A computational workflow was designed in this study to identify key blood methylation features and rules that can distinguish the severity of SARS-CoV-2 infection. First, the methylation features in the expression profile were deeply analyzed by a Monte Carlo feature selection method. A feature list was generated. Next, this ranked feature list was fed into the incremental feature selection method to determine the optimal features for different classification algorithms, thereby further building optimal classifiers. These selected key features were analyzed by functional enrichment to detect their biofunctional information. Furthermore, a set of rules were set up by a white-box algorithm, decision tree, to uncover different methylation patterns on various severity of SARS-CoV-2 infection. Some genes (PARP9, MX1, IRF7), corresponding to essential methylation sites, and rules were validated by published academic literature. Overall, this study contributes to revealing potential expression features and provides a reference for patient stratification. The physicians can prioritize and allocate health and medical resources for COVID-19 patients based on their predicted severe clinical outcomes.

COVID-19 associated EBV reactivation and effects of ganciclovir treatment.

BACKGROUND: Systemic reactivation of Epstein-Barr virus (EBV) may occur in novel coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). However, the clinical consequences of EBV reactivation remain uncertain. METHODS: In this retrospective study, we screened 1314 patients with confirmed COVID-19 who died or were discharged between January 1, 2020 and March 12, 2020, in Wuhan Infectious Disease Hospital, Wuhan, China. Patients who had complete data for EBV serology and cytomegalovirus (CMV) serology were eligible. Serum levels of viral capsid antigen (VCA)-immunoglobulin G (IgG), Epstein-Barr nuclear antigen-IgG, VCA-IgM, early antigen (EA)-IgG, CMV-IgG, and CMV-IgM were compared between survivors and nonsurvivors. Dynamic changes of laboratory tests and outcomes were compared in patients with and without ganciclovir treatment. We used 1:1 matching based on age, gender, and illness severity to balance baseline characteristics. RESULTS: EBV reactivation was present in 55 of 217 patients. EBV reactivation was associated with age (57.91 [13.19] vs. 50.28 [12.66] years, p < .001), female gender (31 [56%] vs. 60 [37%], p = .02). Patients with EBV reactivation have statistically nonsignificant higher mortality rate (12 [22%] vs. 18 [11%], p = .08). EA-IgG levels were significantly higher in nonsurvivors than in survivors (median difference: -0.00005, 95% confidence interval, CI [-3.10, 0.00], p = .05). As compared to patients with COVID-19 who did not receive ganciclovir therapy, ganciclovir-treated patients had improved survival rate (0.98, 95% CI [0.95, 1.00] vs. 0.88, 95% CI [0.81, 0.95], p = .01). Hemoglobin (p < .001) and prealbumin (p = .02) levels were significantly higher in ganciclovir-treated patients. CONCLUSION: A high proportion of COVID-19 patients had EBV reactivation that may be associated with an increased risk of death. Whether treatment with ganciclovir may decrease the mortality of COVID-19 patients complicated with EBV reactivation warrants to be addressed in a placebo-controlled randomized trial in the future.

Chronic colchicine poisoning with neuromyopathy, gastric ulcers and myelosuppression in a gout patient: A case report.

BACKGROUND: Colchicine has been widely used as an anti-gout medication over the past decades. However, it is less commonly used due to its narrow therapeutic range, meaning that its lethal dose is close to its therapeutic dose. The lethal dose of colchicine is considered to be 0.8 mg/kg. As chronic colchicine poisoning has multiple manifestations, it poses a challenge in the clinician's differential diagnosis. Historically, the drug was important in treating gout; however, clinical studies are currently underway regarding the use of colchicine in patients with coronavirus disease 2019 as well as its use in coronary artery disease, making this drug more important in clinical practice. CASE SUMMARY: A 61-year-old male with a history of gout and chronic colchicine intake was admitted to our Emergency Department due to numbness and weakness of the lower limbs. The patient reported a history of colchicine intake for 23 years. After thorough examination, he was diagnosed with colchicine poisoning, manifesting as neuromyopathy, multiple gastric ulcers and myelosuppression. We advised him to stop taking colchicine and drinking alcohol. We also provided a prescription of lansoprazole and mecobalamin, and then asked him to return to the clinic for re-examination. The patient was followed up for 3-mo during which time his gout symptoms were controlled to the point where he was asymptomatic. CONCLUSION: Colchicine overdose can mimic the clinical manifestations of several conditions. Physicians easily pay attention to the disease while ignoring the cause of the disease. Thus, the patient's medication history should never be ignored.

Risk factors for secondary hemophagocytic lymphohistiocytosis in severe coronavirus disease 2019 adult patients.

BACKGROUND: Secondary hemophagocytic lymphohistiocytosis (sHLH) is a life-threatening hyperinflammatory event and a fatal complication of viral infections. Whether sHLH may also be observed in patients with a cytokine storm induced by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is still uncertain. We aimed to determine the incidence of sHLH in severe COVID-19 patients and evaluate the underlying risk factors. METHOD: Four hundred fifteen severe COVID-19 adult patients were retrospectively assessed for hemophagocytosis score (HScore). A subset of 7 patients were unable to be conclusively scored due to insufficient patient data. RESULTS: In 408 patients, 41 (10.04%) had an HScore ≥169 and were characterized as "suspected sHLH positive". Compared with patients below a HScore threshold of 98, the suspected sHLH positive group had higher D-dimer, total bilirubin, alanine aminotransferase, aspartate aminotransferase, blood urea nitrogen, serum creatinine, triglycerides, ferritin, interleukin-6, C-reactive protein, procalcitonin, lactate dehydrogenase, creatine kinase isoenzyme, troponin, Sequential Organ Failure Assessment (SOFA) score, while leukocyte, hemoglobin, platelets, lymphocyte, fibrinogen, pre-albumin, albumin levels were significantly lower (all P < 0.05). Multivariable logistic regression revealed that high ferritin (>1922.58 ng/mL), low platelets (<101 × 109/L) and high triglycerides (>2.28 mmol/L) were independent risk factors for suspected sHLH in COVID-19 patients. Importantly, COVID-19 patients that were suspected sHLH positive had significantly more multi-organ failure. Additionally, a high HScore (>98) was an independent predictor for mortality in COVID-19. CONCLUSIONS: HScore should be measured as a prognostic biomarker in COVID-19 patients. In particular, it is important that HScore is assessed in patients with high ferritin, triglycerides and low platelets to improve the detection of suspected sHLH.

Construction of a Human Cell Landscape of COVID-19 Infection at Single-cell Level.

COVID-19 is now causing a global pandemic, there is a demand to explain the different clinical patterns between children and adults. To clarify the organs/cell types vulnerable to COVID-19 infection and the potential age-depended expression patterns of five factors (ACE2, TMPRSS2, MTHFD1, CTSL, CTSB) associated with clinical symptoms. In this study, we analyzed expression levels of five COVID-19 host dependency factors in multiple adult and fetal human organs. The results allowed us to grade organs at risk and also pointed towards the target cell types in each organ mentioned above. Based on these results we constructed an organ- and cell type-specific vulnerability map of the expression levels of the five COVID-19 factors in the human body, providing insight into the mechanisms behind the symptoms, including the non-respiratory symptoms of COVID-19 infection and injury. Also, the different expression patterns of the COVID-19 factors well demonstrate an explanation that the different clinical patterns between adult and children/infants.

[Practical procedure of prone position ventilation in critical coronavirus disease 2019 patients].

Prone position ventilation has become an important part of lung protective ventilation in acute respiratory distress syndrome (ARDS) patients. Timely and appropriate implementation can improve the mortality of such patients. The same is true for patients with critical coronavirus disease 2019 (COVID-19) patients, but safety assessment, control of implementation details and prevention of complications still need to be further standardized during the practical procedure of prone position ventilation. The purpose of this paper is to explain the specific requirements and key points of prone position ventilation in critical COVID-19 patients, in order to promote the application of prone position ventilation in the treatment of patients with critical COVID-19 and reduce the occurrence of related complications.

Identification and validation of prognostic factors in patients with COVID-19: A retrospective study based on artificial intelligence algorithms.

Background: Novel coronavirus disease 2019 (COVID-19) is an ongoing global pandemic with high mortality. Although several studies have reported different risk factors for mortality in patients based on traditional analytics, few studies have used artificial intelligence (AI) algorithms. This study investigated prognostic factors for COVID-19 patients using AI methods. Methods: COVID-19 patients who were admitted in Wuhan Infectious Diseases Hospital from December 29, 2019 to March 2, 2020 were included. The whole cohort was randomly divided into training and testing sets at a 6:4 ratio. Demographic and clinical data were analyzed to identify predictors of mortality using least absolute shrinkage and selection operator (LASSO) regression and LASSO-based artificial neural network (ANN) models. The predictive performance of the models was evaluated using receiver operating characteristic (ROC) curve analysis. Results: A total of 1145 patients (610 male, 53.3%) were included in the study. Of the 1145 patients, 704 were assigned to the training set and 441 were assigned to the testing set. The median age of the patients was 57 years (range: 47-66 years). Severity of illness, age, platelet count, leukocyte count, prealbumin, C-reactive protein (CRP), total bilirubin, Acute Physiology and Chronic Health Evaluation (APACHE) II score, and Sequential Organ Failure Assessment (SOFA) score were identified as independent prognostic factors for mortality. Incorporating these nine factors into the LASSO regression model yielded a correct classification rate of 0.98, with area under the ROC curve (AUC) values of 0.980 and 0.990 in the training and testing cohorts, respectively. Incorporating the same factors into the LASSO-based ANN model yielded a correct classification rate of 0.990, with an AUC of 0.980 in both the training and testing cohorts. Conclusions: Both the LASSO regression and LASSO-based ANN model accurately predicted the clinical outcome of patients with COVID-19. Severity of illness, age, platelet count, leukocyte count, prealbumin, CRP, total bilirubin, APACHE II score, and SOFA score were identified as prognostic factors for mortality in patients with COVID-19.

Sex Differences on Clinical Characteristics, Severity, and Mortality in Adult Patients With COVID-19: A Multicentre Retrospective Study.

Background: Coronavirus disease-2019 (COVID-19) epidemic is spreading globally. Sex differences in the severity and mortality of COVID-19 emerged. This study aims to describe the impact of sex on outcomes in COVOD-19 with a special focus on the effect of estrogen. Methods: We performed a retrospective cohort study which included 413 patients (230 males and 183 females) with COVID-19 from three designated hospitals in China with a follow up time from January 31, 2020, to April 17, 2020. Women over 55 were considered as postmenopausal patients according to the previous epidemiological data from China. The interaction between age and sex on in-hospital mortality was determined through Cox regression analysis. In addition, multivariate Cox regression models were performed to explore risk factors associated with in-hospital mortality of COVID-19. Results: Age and sex had significant interaction for the in-hospital mortality (P < 0.001). Multivariate Cox regression showed that age (HR 1.041, 95% CI 1.009-1.073, P = 0.012), male sex (HR 2.033, 95% CI 1.007-2.098, P = 0.010), the interaction between age and sex (HR 1.118, 95% CI 1.003-1.232, P = 0.018), and comorbidities (HR 9.845, 95% CI 2.280-42.520, P = 0.002) were independently associated with in-hospital mortality of COVID-19 patients. In this multicentre study, female experienced a lower fatality for COVID-19 than male (4.4 vs. 10.0%, P = 0.031). Interestingly, stratification by age group revealed no difference in-hospital mortality was noted in women under 55 compared with women over 55 (3.8 vs. 5.2%, P = 0.144), as well as in women under 55 compared with the same age men (3.8 vs. 4.0%, P = 0.918). However, there was significantly difference in women over 55 with men of the same age group (5.2 vs. 21.0%, P = 0.007). Compared with male patients, female patients had higher lymphocyte (P < 0.001) and high-density lipoprotein (P < 0.001), lower high sensitive c reaction protein level (P < 0.001), and lower incidence rate of acute cardiac injury (6.6 vs. 13.5%, P = 0.022). Conclusion: Male sex is an independent risk factor for COVID-19 in-hospital mortality. Although female mortality in COVID-19 is lower than male, it might not be directly related to the effect of estrogen. Further study is warranted to identify the sex difference in COVID-19 and mechanisms involved.

Risk factors for severe COVID-19 in middle-aged patients without comorbidities: a multicentre retrospective study.

BACKGROUND: Information regarding characteristics and risk factors of COVID-19 amongst middle-aged (40-59 years) patients without comorbidities is scarce. METHODS: We therefore conducted this multicentre retrospective study and collected data of middle-aged COVID-19 patients without comorbidities at admission from three designated hospitals in China. RESULTS: Among 119 middle-aged patients without comorbidities, 18 (15.1%) developed into severe illness and 5 (3.9%) died in hospital. ARDS (26, 21.8%) and elevated D-dimer (36, 31.3%) were the most common complications, while other organ complications were relatively rare. Multivariable regression showed increasing odds of severe illness associated with neutrophil to lymphocyte ratio (NLR, OR, 11.238; 95% CI 1.110-1.382; p < 0.001) and D-dimer greater than 1 µg/ml (OR, 16.079; 95% CI 3.162-81.775; p = 0.001) on admission. The AUCs for the NLR, D-dimer greater than 1 µg/ml and combined NLR and D-dimer index were 0.862 (95% CI, 0.751-0.973), 0.800 (95% CI 0.684-0.915) and 0.916 (95% CI, 0.855-0.977), respectively. SOFA yielded an AUC of 0.750 (95% CI 0.602-0.987). There was significant difference in the AUC between SOFA and combined index (z = 2.574, p = 0.010). CONCLUSIONS: More attention should be paid to the monitoring and early treatment of respiratory and coagulation abnormalities in middle-aged COVID-19 patients without comorbidities. In addition, the combined NLR and D-dimer higher than 1 µg/ml index might be a potential and reliable predictor for the incidence of severe illness in this specific patient with COVID-19, which could guide clinicians on early classification and management of patients, thereby relieving the shortage of medical resource. However, it is warranted to validate the reliability of the predictor in larger sample COVID-19 patients.

Abnormal immunity of non-survivors with COVID-19: predictors for mortality.

BACKGROUND: The number of coronavirus disease 2019 (COVID-19) cases has rapidly increased all over the world. Specific information about immunity in non-survivors with COVID-19 is scarce. This study aimed to analyse the clinical characteristics and abnormal immunity of the confirmed COVID-19 non-survivors. METHODS: In this single-centered, retrospective, observational study, we enrolled 125 patients with COVID-19 who were died between January 13 and March 4, 2020 in Renmin Hospital of Wuhan University. A total of 414 randomly recruited patients with confirmed COVID-19 who were discharged from the same hospital during the same period served as control. The demographic, clinical characteristics and laboratory findings at admission, and treatment used in these patients were collected. The immunity-related risk factors associated with in-hospital death were tested by logistic regression models and Receiver Operating Characteristic (ROC) curve. RESULTS: Non-survivors (70 years, IQR: 61.5-80) were significantly older than survivors (54 years, IQR: 37-65) (P <  0.001). 56.8% of non-survivors was male. Nearly half of the patients (44.9%) had chronic medical illness. In non-survivors, hypertension (49.6%) was the most common comorbidity, followed by diabetes (20.0%) and coronary heart disease (16.0%). The common signs and symptoms at admission of non-survivors were fever (88%), followed by cough (64.8%), dyspnea (62.4%), fatigue (62.4%) and chest tightness (58.4%). Compared with survivors, non-survivors had higher white blood cell (WBC) count (7.85 vs 5.07 × 109/L), more elevated neutrophil count (6.41 vs 3.08 × 109/L), smaller lymphocyte count (0.69 vs 1.20 × 109/L) and lower platelet count (172 vs 211 × 109/L), raised concentrations of procalcitonin (0.21 vs 0.06 ng/mL) and CRP (70.5 vs 7.2 mg/L) (P < 0.001). This was accompanied with significantly decreased levels of CD3+ T cells (277 vs 814 cells/µl), CD4+ T cells (172 vs 473 cells/µl), CD8+ T cells (84 vs 262.5 cells/µl, P < 0.001), CD19+ T cells (88 vs 141 cells/µl) and CD16+ 56+ T cells (79 vs 128.5 cells/µl) (P < 0.001). The concentrations of immunoglobulins (Ig) G (13.30 vs 11.95 g/L), IgA (2.54 vs 2.21 g/L), and IgE (71.30 vs 42.25 IU/ml) were increased, whereas the levels of complement proteins (C)3 (0.89 vs 0.99 g/L) and C4 (0.22 vs 0.24 g/L) were decreased in non-survivors when compared with survivors (all P < 0.05). The non-survivors presented lower levels of oximetry saturation (90 vs 97%) at rest and lactate (2.40 vs 1.90 mmol/L) (P < 0.001). Old age, comorbidity of malignant tumor, neutrophilia, lymphocytopenia, low CD4+ T cells, decreased C3, and low oximetry saturation were the risk factors of death in patients with confirmed COVID-19. The frequency of CD4+ T cells positively correlated with the numbers of lymphocytes (r = 0.787) and the level of oximetry saturation (r = 0.295), Whereas CD4+ T cells were negatively correlated with age (r =-0.323) and the numbers of neutrophils (r = - 0.244) (all P < 0.001). CONCLUSIONS: Abnormal cellular immunity and humoral immunity were key features of non-survivors with COVID-19. Neutrophilia, lymphocytopenia, low CD4+ T cells, and decreased C3 were immunity-related risk factors predicting mortality of patients with COVID-19.

A retrospective study of risk factors for severe acute respiratory syndrome coronavirus 2 infections in hospitalized adult patients.

INTRODUCTION: Coronavirus disease 2019 (COVID­19) caused by severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) infection spread worldwide. OBJECTIVES: The aim of the study was to identify the clinical characteristics and risk factors associated with severe incidence of SARS ­CoV­2 infection. PATIENTS AND METHODS: All adult patients (median [IQR] age, 52 [37-58] years) consecutively admitted to the Dabieshan Medical Center from January 30, 2020 to February 11, 2020 were collected and reviewed. Only patients diagnosed with COVID­19  according to the World Health Organization interim guidance were included in this retrospective cohort study. RESULTS: A total of 108 patients with COVID­19 were retrospectively analyzed. Twenty­five patients (23.1%) developed severe disease, and of those 12 patients (48%) died. Advanced age, comorbidities (most commonly hypertension), higher blood leukocyte count, neutrophil count, higher C­reactive protein level, D­dimer level, Acute Physiology and Chronic Health Evaluation II (APACHE II) score, and Sequential Organ Failure Assessment (SOFA) score were associated with greater risk of COVID­19, and so were lower lymphocyte count and albumin level. Multivariable regress ion showed increasing odds of severe COVID­19 associated with higher SOFA score (odds ratio [OR], 2.45; 95% CI, 1.302-4.608; P = 0.005), and lymphocyte count less than 0.8 × 109/l (OR, 9.017; 95% CI, 2.808-28.857; P <0.001) on admission. Higher SOFA score (OR, 2.402; 95% CI, 1.313-4.395; P = 0.004) on admission was identified as risk factor for in­hospital death. CONCLUSIONS: Lymphocytopenia and a higher SOFA score on admission could help clinicians to identify patients at high risk for developing severe COVID­19. More related studies are needed in the future.