An early novel prognostic model for predicting 80-day survival of patients with COVID-19.

The outbreak of the novel coronavirus disease 2019 (COVID-19) has had an unprecedented impact worldwide, and it is of great significance to predict the prognosis of patients for guiding clinical management. This study aimed to construct a nomogram to predict the prognosis of COVID-19 patients. Clinical records and laboratory results were retrospectively reviewed for 331 patients with laboratory-confirmed COVID-19 from Huangshi Hospital of Traditional Chinese Medicine (TCM) (Infectious Disease Hospital) and Third Affiliated Hospital of Sun Yat-sen University. All COVID-19 patients were followed up for 80 days, and the primary outcome was defined as patient death. Cases were randomly divided into training (n=199) and validation (n=132) groups. Based on baseline data, we used statistically significant prognostic factors to construct a nomogram and assessed its performance. The patients were divided into Death (n=23) and Survival (n=308) groups. Analysis of clinical characteristics showed that these patients presented with fever (n=271, 81.9%), diarrhea (n=20, 6.0%) and had comorbidities (n=89, 26.9.0%). Multivariate Cox regression analysis showed that age, UREA and LDH were independent risk factors for predicting 80-day survival of COVID-19 patients. We constructed a qualitative nomogram with high C-indexes (0.933 and 0.894 in the training and validation groups, respectively). The calibration curve for 80-day survival showed optimal agreement between the predicted and actual outcomes. Decision curve analysis revealed the high clinical net benefit of the nomogram. Overall, our nomogram could effectively predict the 80-day survival of COVID-19 patients and hence assist in providing optimal treatment and decreasing mortality rates.

Comparative global B cell receptor repertoire difference induced by SARS-CoV-2 infection or vaccination via single-cell V(D)J sequencing.

Dynamic changes of the paired heavy and light chain B cell receptor (BCR) repertoire provide an essential insight into understanding the humoral immune response post-SARS-CoV-2 infection and vaccination. However, differences between the endogenous paired BCR repertoire kinetics in SARS-CoV-2 infection and previously recovered/naïve subjects treated with the inactivated vaccine remain largely unknown. We performed single-cell V(D)J sequencing of B cells from six healthy donors with three shots of inactivated SARS-CoV-2 vaccine (BBIBP-CorV), five people who received the BBIBP-CorV vaccine after having recovered from COVID-19, five unvaccinated COVID-19 recovered patients and then integrated with public data of B cells from four SARS-CoV-2-infected subjects. We discovered that BCR variable (V) genes were more prominently used in the SARS-CoV-2 exposed groups (both in the group with active infection and in the group that had recovered) than in the vaccinated groups. The VH gene that expanded the most after SARS-CoV-2 infection was IGHV3-33, while IGHV3-23 in the vaccinated groups. SARS-CoV-2-infected group enhanced more BCR clonal expansion and somatic hypermutation than the vaccinated healthy group. A small proportion of public clonotypes were shared between the SARS-CoV-2 infected, vaccinated healthy, and recovered groups. Moreover, several public antibodies had been identified against SARS-CoV-2 spike protein. We comprehensively characterize the paired heavy and light chain BCR repertoire from SARS-CoV-2 infection to vaccination, providing further guidance for the development of the next-generation precision vaccine.

U-Shaped Relationship of Low-Density Lipoprotein Cholesterol With Risk of Severe COVID-19 From a Multicenter Pooled Analysis.

Low-density lipoprotein cholesterol (LDL-C) is a well-known risk factor for coronary heart disease but protects against infection and sepsis. We aimed to disclose the exact association between LDL-C and severe 2019 novel coronavirus disease (COVID-19). Baseline data were retrospectively collected for 601 non-severe COVID-19 patients from two centers in Guangzhou and one center in Shenzhen, and patients on admission were medically observed for at least 15 days to determine the final outcome, including the non-severe group (n = 460) and the severe group (severe and critical cases) (n = 141). Among 601 cases, 76 (12.65%) received lipid-lowering therapy; the proportion of patients taking lipid-lowering drugs in the severe group was higher than that in the non-severe group (22.7 vs. 9.6%). We found a U-shaped association between LDL-C level and risk of severe COVID-19 using restricted cubic splines. Using univariate logistic regression analysis, odds ratios for severe COVID-19 for patients with LDL-C ≤1.6 mmol/L (61.9 mg/dL) and above 3.4 mmol/L (131.4 mg/dL) were 2.29 (95% confidence interval 1.12-4.68; p = 0.023) and 2.02 (1.04-3.94; p = 0.039), respectively, compared to those with LDL-C of 2.81-3.40 mmol/L (108.6-131.4 mg/dL); following multifactorial adjustment, odds ratios were 2.61 (1.07-6.37; p = 0.035) and 2.36 (1.09-5.14; p = 0.030). Similar results were yielded using 0.3 and 0.5 mmol/L categories of LDL-C and sensitivity analyses. Both low and high LDL-C levels were significantly associated with higher risk of severe COVID-19. Although our findings do not necessarily imply causality, they suggest that clinicians should pay more attention to lipid-lowering therapy in COVID-19 patients to improve clinical prognosis.

Research on Influencing Factors and Classification of Patients With Mild and Severe COVID-19 Symptoms.

Objective: To analyze the epidemiological history, clinical symptoms, laboratory testing parameters of patients with mild and severe COVID-19 infection, and provide a reference for timely judgment of changes in the patients' conditions and the formulation of epidemic prevention and control strategies. Methods: A retrospective study was conducted in this research, a total of 90 patients with COVID-19 infection who received treatment from January 21 to March 31, 2020 in the Ninth People's Hospital of Dongguan City were selected as study subject. We analyzed the clinical characteristics of laboratory-confirmed patients with COVID-19, used the oversampling method (SMOTE) to solve the imbalance of categories, and established Lasso-logistic regression and random forest models. Results: Among the 90 confirmed COVID-19 cases, 79 were mild and 11 were severe. The average age of the patients was 36.1 years old, including 49 males and 41 females. The average age of severe patients is significantly older than that of mild patients (53.2 years old vs 33.7 years old). The average time from illness onset to hospital admission was 4.1 days and the average actual hospital stay was 18.7 days, both of these time actors were longer for severe patients than for mild patients. Forty-eight of the 90 patients (53.3%) had family cluster infections, which was similar among mild and severe patients. Comorbidities of underlying diseases were more common in severe patients, including hypertension, diabetes and other diseases. The most common symptom was cough [45 (50%)], followed by fever [43 (47.8%)], headache [7 (7.8%)], vomiting [3 (3.3%)], diarrhea [3 (3.3%)], and dyspnea [1 (1.1%)]. The laboratory findings of patients also included leukopenia [13(14.4%)] and lymphopenia (17.8%). Severe patients had a low level of creatine kinase (median 40.9) and a high level of D-dimer. The median NLR of severe patients was 2.82, which was higher than that of mild patients. Logistic regression showed that age, phosphocreatine kinase, procalcitonin, the lymphocyte count of the patient on admission, cough, fatigue, and pharynx dryness were independent predictors of COVID-19 severity. The classification of random forest was predicted and the importance of each variable was displayed. The variable importance of random forest indicates that age, D-dimer, NLR (neutrophil to lymphocyte ratio) and other top-ranked variables are risk factors. Conclusion: The clinical symptoms of COVID-19 patients are non-specific and complicated. Age and the time from onset to admission are important factors that determine the severity of the patient's condition. Patients with mild illness should be closely monitored to identify those who may become severe. Variables such as age and creatine phosphate kinase selected by logistic regression can be used as important indicators to assess the disease severity of COVID-19 patients. The importance of variables in the random forest further complements the variable feature information.

Effects of Smoking on ACE2 Expression Pattern: Risk and Severity of SARS-CoV-2 Infection.

BACKGROUND: Respiratory epithelium expressing angiotensin-converting enzyme 2 (ACE2) is the entry for novel coronavirus (SARS-CoV-2), pathogen of the COVID-19 pneumonia outbreak, although a few recent studies have found different ACE2 expression in lung tissue of smokers. The effect of smoking on ACE2 expression and COVID-19 is still not clear. So, we did this research to determine the effect of smoking on ACE2 expression pattern and its relationship with the risk and severity of COVID-19. METHODS: The clinical data of COVID-19 patients with smoking and non-smoking were analyzed, and ACE2 expression of respiratory and digestive mucosa epithelia from smoker and non-smoker patients or healthy subjects were detected by immunohistochemical (IHC) staining. RESULTS: Of all 295 laboratory-confirmed COVID-19 patients, only 24 (8.1%) were current smokers with moderate smoking or above, which accounted for 54.2% of severe cases with higher mortality than non-smokers (8.3% vs. 0.4%, p = 0.018). Data analysis showed the proportion of smokers in COVID-19 patients was lower than that in general population of China (Z = 11.65, P < 0.001). IHC staining showed ACE2 expression in respiratory and digestive epithelia of smokers were generally downregulated. CONCLUSIONS: The proportion of smokers in COVID-19 patients was lower, which may be explained by ACE2 downregulation in respiratory mucosa epithelia. However, smoking COVID-19 patients accounted for a higher proportion in severe cases and higher mortality than for non-smoking COVID-19 patients, which needs to be noted.

Rapid isolation and immune profiling of SARS-CoV-2 specific memory B cell in convalescent COVID-19 patients via LIBRA-seq.

B cell response plays a critical role against SARS-CoV-2 infection. However, little is known about the diversity and frequency of the paired SARS-CoV-2 antigen-specific BCR repertoire after SARS-CoV-2 infection. Here, we performed single-cell RNA sequencing and VDJ sequencing using the memory and plasma B cells isolated from five convalescent COVID-19 patients, and analyzed the spectrum and transcriptional heterogeneity of antibody immune responses. Via linking BCR to antigen specificity through sequencing (LIBRA-seq), we identified a distinct activated memory B cell subgroup (CD11chigh CD95high) had a higher proportion of SARS-CoV-2 antigen-labeled cells compared with memory B cells. Our results revealed the diversity of paired BCR repertoire and the non-stochastic pairing of SARS-CoV-2 antigen-specific immunoglobulin heavy and light chains after SARS-CoV-2 infection. The public antibody clonotypes were shared by distinct convalescent individuals. Moreover, several antibodies isolated by LIBRA-seq showed high binding affinity against SARS-CoV-2 receptor-binding domain (RBD) or nucleoprotein (NP) via ELISA assay. Two RBD-reactive antibodies C14646P3S and C2767P3S isolated by LIBRA-seq exhibited high neutralizing activities against both pseudotyped and authentic SARS-CoV-2 viruses in vitro. Our study provides fundamental insights into B cell response following SARS-CoV-2 infection at the single-cell level.

Clinical Characteristics, Serological and Radiological Longitudinal Changes of Patients with COVID-19.

BACKGROUND: Since December 2019, an outbreak of coronavirus disease 2019 (COVID-19) began in Wuhan and rapidly spread globally. The speed and scope of the spread of COVID-19 makes it urgent to define clinical characteristics, serological and radiological changes of the affected patients. METHODS: Seven patients with laboratory-confirmed COVID-19 who were admitted to the Third Affiliated Hospital of Sun Yat-Sen University Yuedong Hospital from January 2020 to March 2020 were retrospectively enrolled and their clinical features, serological and radiological longitudinal changes were analyzed. RESULTS: Among the 7 patients, all (100%) had a clear epidemiological history. The most common symptoms were respiratory symptoms 6 (85.7%), and only 2 (28.6%) of the patients had fever at their first visit. The cohort included 4 (57.1%) common types and 3 (42.9%) severe types. Two (28.6%) common type patients developed to severe type in a short time. All of the 7 patients (100%) had abnormal liver function, normal renal function, and normal procalcitonin. The detection time of specific antibody in 7 patients was 5 - 13 days after symptoms. Before the specific antibody could be detected, the absolute value of lymphocytes decreased in 2 (28.6%) common type cases transferred to severe type cases accompanied with obvious progress in pulmonary imaging. The phenomenon of decreased albumin and elevated globulin occurred in 6 patients (85.7%). The predominant pattern of lung lesions observed was bilateral (71.4%) and mainly near the pleura at the first diagnosis. Bilateral pulmonary involvement occurred in 6 cases (85.7%) during the course of disease. In 4 cases (57.1%) with obvious pulmonary lesions, the absolute value of lymphocytes decreased, albumin decreased, and globulin increased during the course of the disease. CONCLUSIONS: Serum specific antibodies can be detected within 2 weeks of onset. Close observation of the dynamic changes of absolute value of blood lymphocytes, serum albumin, and globulin which were related to pulmonary imaging changes in patients will contribute to assessment of COVID-19.

A Convalescent of COVID-19 with RT-PCR Test Continues Positive in Stool.

BACKGROUND: Coronavirus disease (COVID-19) has affected more than 100 countries worldwide and the discharge criteria of patients with COVID-19 vary across different countries. In China, patients with two negative respiratory viral RNA tests taken at least one day apart can be discharged with no further quarantine required. Currently, PCR testing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in fecal sample is not routinely performed. METHODS: We present a patient with COVID-19, whose respiratory swabs became negative but fecal sample remained positive for SARS-CoV-2 RNA. RESULTS: Stool sample collected on 27th of February was still positive for SARS-CoV-2 RNA, 24 days after the first negative respiratory swab. CONCLUSIONS: Based on the experience from the 2003 SARS epidemic, we recommend that fecal RNA testing of SARS-CoV-2 should be incorporated into the discharge criteria to minimize the risk of transmission from the gastrointestinal tract.

Upper Respiratory Tract Viral Ribonucleic Acid Load at Hospital Admission Is Associated With Coronavirus Disease 2019 Disease Severity.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has aroused global public health concerns. Multiple clinical features relating to host profile but not for virus have been identified as the risk factors for illness severity and/or the outcomes in COVID-19. METHODS: The clinical features obtained from a cohort of 195 laboratory-confirmed, nasopharynx-sampled patients with COVID-19 in Guangdong, China from January 13 to February 29, 2020 were enrolled to this study. The differences in clinical features among 4 groups (mild, moderate, severe, and critical) and between 2 groups (severe vs nonsevere) were compared using one-way analysis of variance and Student's t test, respectively. Principal component analysis and correlation analysis were performed to identify the major factors that account for illness severity. RESULTS: In addition to the previously described clinical illness severity-related factors, including older age, underlying diseases, higher level of C-reactive protein, D-dimer and aspartate aminotransferase, longer fever days and higher maximum body temperature, larger number of white blood cells and neutrophils but relative less lymphocytes, and higher ratio of neutrophil to lymphocytes, we found that the initial viral load is an independent factor that accounts for illness severity in COVID-19 patients. CONCLUSIONS: The initial viral load of severe acute respiratory syndrome coronavirus 2 is a novel virological predictor for illness severity of COVID-19.

A Tool for Early Prediction of Severe Coronavirus Disease 2019 (COVID-19): A Multicenter Study Using the Risk Nomogram in Wuhan and Guangdong, China.

BACKGROUND: Because there is no reliable risk stratification tool for severe coronavirus disease 2019 (COVID-19) patients at admission, we aimed to construct an effective model for early identification of cases at high risk of progression to severe COVID-19. METHODS: In this retrospective multicenter study, 372 hospitalized patients with nonsevere COVID-19 were followed for > 15 days after admission. Patients who deteriorated to severe or critical COVID-19 and those who maintained a nonsevere state were assigned to the severe and nonsevere groups, respectively. Based on baseline data of the 2 groups, we constructed a risk prediction nomogram for severe COVID-19 and evaluated its performance. RESULTS: The training cohort consisted of 189 patients, and the 2 independent validation cohorts consisted of 165 and 18 patients. Among all cases, 72 (19.4%) patients developed severe COVID-19. Older age; higher serum lactate dehydrogenase, C-reactive protein, coefficient of variation of red blood cell distribution width, blood urea nitrogen, and direct bilirubin; and lower albumin were associated with severe COVID-19. We generated the nomogram for early identifying severe COVID-19 in the training cohort (area under the curve [AUC], 0.912 [95% confidence interval {CI}, .846-.978]; sensitivity 85.7%, specificity 87.6%) and the validation cohort (AUC, 0.853 [95% CI, .790-.916]; sensitivity 77.5%, specificity 78.4%). The calibration curve for probability of severe COVID-19 showed optimal agreement between prediction by nomogram and actual observation. Decision curve and clinical impact curve analyses indicated that nomogram conferred high clinical net benefit. CONCLUSIONS: Our nomogram could help clinicians with early identification of patients who will progress to severe COVID-19, which will enable better centralized management and early treatment of severe disease.

A cross-sectional comparison of epidemiological and clinical features of patients with coronavirus disease (COVID-19) in Wuhan and outside Wuhan, China.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has spread outside the initial epicenter of Wuhan. We compared cases in Guangzhou and Wuhan to illustrate potential changes in pathogenicity and epidemiological characteristics as the epidemic has progressed. METHODS: We studied 20 patients admitted to the Third Affiliated Hospital of Sun Yat-Sen University in Guangzhou, China from January 22 to February 12, 2020. Data were extracted from medical records. These cases were compared with the 99 cases, previously published in Lancet, from Wuhan Jinyintan Hospital from January 1 to January 20, 2020. RESULTS: Guangzhou patients were younger and had better prognosis than Wuhan patients. The Wuhan patients were more likely to be admitted to the ICU (23% vs 5%) and had a higher mortality rate (11% vs 0%). Cases in Guangzhou tended to be more community clustered. Diarrhea and vomiting were more common among Guangzhou patients and SARS-CoV-2 RNA was found in feces. Fecal SARA-CoV-2 RNA remained positive when nasopharyngeal swabs turned negative in some patients. CONCLUSIONS: This study indicates possible diminishing virulence of the virus in the process of transmission. Yet persistent positive RNA in feces after negative nasopharyngeal swabs suggests a possible prolonged transmission period that challenges current quarantine practices.