Nanopore membrane chip-based isolation method for metabolomic analysis of plasma small extracellular vesicles from COVID-19 survivors.

Multiple studies showed that metabolic disorders play a critical role in respiratory infectious diseases, including COVID-19. Metabolites contained in small extracellular vesicles (sEVs) are different from those in plasma at the acute stage, while the metabolic features of plasma sEVs of COVID-19 survivors remain unknown. Here, we used a nanopore membrane-based microfluidic chip for plasma sEVs separation, termed ExoSEC, and compared the sEVs obtained by UC, REG, and ExoSEC in terms the time, cost, purity, and metabolic features. The results indicated the ExoSEC was much less costly, provided higher purity by particles/proteins ratio, and achieved 205-fold and 2-fold higher sEVs yield, than UC and REG, respectively. Moreover, more metabolites were identified and several signaling pathways were significantly enriched in ExoSEC-sEVs compared to UC-sEVs and REG-sEVs. Furthermore, we detected 306 metabolites in plasma sEVs using ExoSEC from recovered asymptomatic (RA), moderate (RM), and severe/critical COVID-19 (RS) patients without underlying diseases 3 months after discharge. Our study demonstrated that COVID-19 survivors, especially RS, experienced significant metabolic alteration and the dysregulated pathways mainly involved fatty acid biosynthesis, phenylalanine metabolism, etc. Metabolites of the fatty acid biosynthesis pathway bore a significantly negative association with red blood cell counts and hemoglobin, which might be ascribed to hypoxia or respiratory failure in RM and RS but not in RA at the acute stage. Our study confirmed that ExoSEC could provide a practical and economical alternative for high throughput sEVs metabolomic study.

Predictive Risk Factors at Admission and a "Burning Point" During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19.

Background: We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods: We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results: Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028; 95% confidence interval (CI), 1.004-1.052], sequential organ failure assessment (SOFA) score (OR, 4.367; 95% CI, 3.230-5.903), neutrophil-to-lymphocyte ratio (NLR; OR, 1.094; 95% CI, 1.024-1.168), D-dimer (OR, 1.476; 95% CI, 1.107-1.968), lactate dehydrogenase (LDH; OR, 1.004; 95% CI, 1.001-1.006), international normalised ratio (INR; OR, 1.027; 95% CI, 0.999-1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358; 95% CI, 2.188-8.678], and large vs. small [OR, 9.567; 95% CI, 3.982-22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941-0.972) in the training set and an AUC of 0.958 (95% CI, 0.936-0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2; increase per day [I/d], +0.49), NLR (value, 10.61; I/d, +2.07), C-reactive protein (CRP; value, 46.9 mg/L; I/d, +4.95), glucose (value, 7.83 mmol/L; I/d, +0.2), D-dimer (value, 6.08 µg/L; I/d, +0.28), LDH (value, 461 U/L; I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L; I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion: The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

Predictive Risk Factors at Admission and a “Burning Point” During Hospitalization Serve as Sequential Alerts for Critical Illness in Patients With COVID-19

Background We intended to establish a novel critical illness prediction system combining baseline risk factors with dynamic laboratory tests for patients with coronavirus disease 2019 (COVID-19). Methods We evaluated patients with COVID-19 admitted to Wuhan West Union Hospital between 12 January and 25 February 2020. The data of patients were collected, and the illness severity was assessed. Results Among 1,150 enrolled patients, 296 (25.7%) patients developed into critical illness. A baseline nomogram model consists of seven variables including age [odds ratio (OR), 1.028;95% confidence interval (CI), 1.004–1.052], sequential organ failure assessment (SOFA) score (OR, 4.367;95% CI, 3.230–5.903), neutrophil-to-lymphocyte ratio (NLR;OR, 1.094;95% CI, 1.024–1.168), D-dimer (OR, 1.476;95% CI, 1.107–1.968), lactate dehydrogenase (LDH;OR, 1.004;95% CI, 1.001–1.006), international normalised ratio (INR;OR, 1.027;95% CI, 0.999–1.055), and pneumonia area interpreted from computed tomography (CT) images (medium vs. small [OR, 4.358;95% CI, 2.188–8.678], and large vs. small [OR, 9.567;95% CI, 3.982–22.986]) were established to predict the risk for critical illness at admission. The differentiating power of this nomogram scoring system was perfect with an area under the curve (AUC) of 0.960 (95% CI, 0.941–0.972) in the training set and an AUC of 0.958 (95% CI, 0.936–0.980) in the testing set. In addition, a linear mixed model (LMM) based on dynamic change of seven variables consisting of SOFA score (value, 2;increase per day [I/d], +0.49), NLR (value, 10.61;I/d, +2.07), C-reactive protein (CRP;value, 46.9 mg/L;I/d, +4.95), glucose (value, 7.83 mmol/L;I/d, +0.2), D-dimer (value, 6.08 μg/L;I/d, +0.28), LDH (value, 461 U/L;I/d, +13.95), and blood urea nitrogen (BUN value, 6.51 mmol/L;I/d, +0.55) were established to assist in predicting occurrence time of critical illness onset during hospitalization. Conclusion The two-checkpoint system could assist in accurately and dynamically predicting critical illness and timely adjusting the treatment regimen for patients with COVID-19.

Comparison of clinical characteristics among younger and elderly deceased patients with COVID-19: a retrospective study.

We aimed to compare the age-related clinical characteristics between younger and elderly deceased COVID-19 patients. This single-center retrospective study included 163 adult deceased COVID-19 patients who were admitted to Wuhan Union Hospital West Campus from January 12, 2020, to March 30, 2020. Demographic and clinical features were collected by reviewing the medical records. The median age of the 163 deceased patients was 69 (interquartile range [IQR], 62-78) years. They were classified as younger (age 18-69 years; 86/163, 52.8%) and elderly (≥70 years; 77/163, 47.2%) subjects. Younger deceased patients were more likely to develop fever (72/86 vs 54/77, P=0.039) than elderly deceased patients were while anorexia was (29/77 vs 19/86, P=0.029) more common in elderly deceased patients than in younger deceased patients. In multivariate analyses, age was a protective factor for acute cardiac injury of deceased COVID-19 patients (odds ratio [OR] 0.968, [95% confidence interval (CI), 0.940-0.997]; P=0.033) while chronic cardiac disease was a risk factor for acute cardiac injury of deceased COVID-19 patients (OR 2.660 [95%CI, 1.034-6.843]; P=0.042). Our study described the clinical characteristics of younger and elderly deceased COVID-19 patients and demonstrated that younger deceased patients were more likely to develop an acute cardiac injury.

Clinical Characteristics and Outcomes of Severe or Critical COVID-19 Patients Presenting No Respiratory Symptoms or Fever at Onset.

It is difficult to identify suspected cases of atypical patients with coronavirus disease 2019 (COVID-19), and data on severe or critical patients are scanty. This retrospective study presents the clinical, laboratory, and radiological profiles, treatments, and outcomes of atypical COVID-19 patients without respiratory symptoms or fever at onset. The study examined ten atypical patients out of 909 severe or critical patients diagnosed with COVID-19 in Wuhan Union Hospital West Campus between 25 January 2020 and 10 February 2020. Data were obtained from the electronic medical records of severe or critical patients without respiratory symptoms or fever at onset. Outcomes were followed up to discharge or death. Among 943 COVID-19 patients, 909 (96.4%) were severe or critical type. Of the severe or critical patients, ten (1.1%) presented without respiratory symptoms or fever at admission. The median age of the ten participants was 63 years (interquartile range (IQR): 57-72), and seven participants were men. The median time from symptom onset to admission was 14 d (IQR: 7-20). Eight of the ten patients had chronic diseases. The patients had fatigue (n = 5), headache or dizziness (n = 4), diarrhea (n = 5), anorexia (n = 3), nausea or vomiting (n = 3), and eye discomfort (n = 1). Four patients were found to have lymphopenia. Imaging examination revealed that nine patients had bilateral pneumonia and one had unilateral pneumonia. Eventually, two patients died and eight were discharged. In the discharged patients, the median time from admission to discharge lasted 24 d (IQR: 13-43). In summary, some severe or critical COVID-19 patients were found to have no respiratory symptoms or fever at onset. All such atypical cases should be identified and quarantined as early as possible, since they tend to have a prolonged hospital stay or fatal outcomes. Chest computed tomography (CT) scan and nucleic acid detection should be performed immediately on close contacts of COVID-19 patients to screen out those with atypical infections, even if the contacts present without respiratory symptoms or fever at onset.

Factors associated with asymptomatic infection in health-care workers with severe acute respiratory syndrome coronavirus 2 infection in Wuhan, China: a multicentre retrospective cohort study.

OBJECTIVES: To describe the fraction of asymptomatic health-care workers (HCWs) in two designated hospitals for coronavirus disease 2019 (COVID-19) treatment in Wuhan and explore the factors associated with asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. METHODS: All HCWs in Wuhan Union Hospital and Wuhan Red Cross Hospital with either positive SARS-CoV-2 nucleic acid or positive antibody test before 18 April 2020 were included. Exposure, epidemiological and demographic information were retrospectively collected by a structured questionnaire. Medical records were also reviewed for clinical characteristics and CT images of HCWs. RESULTS: As of 18 April 2020, a total of 424 HCWs were identified. Among them, 276 (65.1%) were symptomatic and 148 (34.9%) were asymptomatic. Fifty-five (19.9%) families of the symptomatic HCWs and 16 (10.8%) families of the asymptomatic HCWs were infected with SARS-CoV-2. HCWs with infected family members tended to be symptomatic (OR 2.053, 95% CI 1.130-3.730; p 0.018). Multivariable logistic regression analysis exhibited that performing tracheal intubation or extubation (OR 4.057, 95% CI 1.183-13.909; p 0.026) was associated with an increased likelihood of symptomatic SARS-CoV-2 infection, whereas consistent use of N95 respirators (OR 0.369, 95% CI 0.201-0.680; p 0.001) and eye protection (OR 0.217, 95% CI 0.116-0.404; p < 0.001) were associated with an increased likelihood of asymptomatic SARS-CoV-2 infection. CONCLUSIONS: Asymptomatic SARS-CoV-2 infection in HCWs comprised a considerable proportion of HCW infections during the pandemic of COVID-19. Those who performed tracheal intubation or extubation were most likely to develop related symptoms, whereas those taking aggressive measures, including consistent use of N95 masks and eye protection, tended to be asymptomatic cases.

Is oseltamivir suitable for fighting against COVID-19: In silico assessment, in vitro and retrospective study.

BACKGROUND: Oseltamivir is a first-line antiviral drug, especially in primary hospitals. During the ongoing outbreak of coronavirus disease 2019 (COVID-19), most patients with COVID-19 who are symptomatic have used oseltamivir. Considering its popular and important role as an antiviral drug, it is necessary to evaluate oseltamivir in the treatment of COVID-19. OBJECTIVE: To evaluate the effect of oseltamivir against COVID-19. METHODS: Swiss-model was used to construct the structure of the N-terminal RNA-binding domain (NRBD) of the nucleoprotein (NC), papain-like protease (PLpro), and RNA-directed RNA polymerase (RdRp) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). TM-align program was performed to compare the structure of the viral proteins with the structure of the neuraminidase of influenza A. Molecular docking was used to analyze the theoretical possibility of effective binding of oseltamivir with the active centers of the viral proteins. In vitro study was used to evaluate the antiviral efficiency of oseltamivir against SARS-CoV-2. By clinical case analysis, we statistically evaluated whether the history of oseltamivir use influenced the progression of the disease. RESULTS: The structures of NRBD, PLpro, and RdRp were built successfully. The results from TM-align suggested that the S protein, NRBD, 3C-like protease (3CLpro), PLPrO, and RdRp were structurally similar to the influenza A neuraminidase, with TM-scores of 0.30077, 0.19254, 0.28766, 0.30666, and 0.34047, respectively. Interestingly, the active center of 3CL pro was found to be similar to the active center from the neuraminidase of influenza A. Through an analysis of molecular docking, we discovered that oseltamivir carboxylic acid was more favorable to bind to the active site of 3CLpro effectively, but its inhibitory effect was not strong compared with the positive group. Finally, we used in vitro study and retrospective case analysis to verify our speculations. We found that oseltamivir is ineffective against SARS-CoV-2 in vitro study and the clinical use of oseltamivir did not improve the patients' symptoms and signs and did not slow the disease progression. CONCLUSIONS: We consider that oseltamivir isn't suitable for the treatment of COVID-19. During the outbreak of novel coronavirus, when oseltamivir is not effective for the patients after they take it, health workers should be highly vigilant about the possibility of COVID-19.

The Correlation Between Clinical Features and Viral RNA Shedding in Outpatients With COVID-19.

BACKGROUND: Patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can shed virus, thereby causing human-to-human transmission, and the viral RNA shedding is commonly used as a proxy measure for infectivity. METHODS: We retrospectively reviewed confirmed cases of COVID-19 who attended the fever clinic of Wuhan Union Hospital from January 14 to February 24. In terms of the viral RNA shedding (median values) at first visit, patients were divided into a high-viral RNA shedding group and a low-viral RNA shedding group. Univariate and multivariate logistic regression analysis were performed to investigate the correlation between viral RNA shedding and clinical features. RESULTS: A total of 918 consecutive COVID-19 patients were enrolled, and severe patients made up 26.1%. After univariate and multivariate logistic regression, advanced age (odds ratio [OR], 1.02; 95% CI, 1.01-1.03; P = .001), having severe chronic diseases (OR, 1.44; 95% CI, 1.03-2.01; P = .04), and severe illness (OR, 1.60; 95% CI, 1.12-2.28; P = .01) were independent risk factors for high viral RNA shedding. Shorter time interval from symptom onset to viral detection was a protective factor for viral RNA shedding (OR, 0.97; 95% CI, 0.94-0.99; P = .01). Compared with mild patients, severe patients have higher virus shedding over a long period of time after symptom onset (P = .01). CONCLUSIONS: Outpatients who were old, had severe illness, and had severe underlying diseases had high viral RNA shedding.

Development and validation of a risk factor-based system to predict short-term survival in adult hospitalized patients with COVID-19: a multicenter, retrospective, cohort study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has become a public health emergency of global concern. We aimed to explore the risk factors of 14-day and 28-day mortality and develop a model for predicting 14-day and 28-day survival probability among adult hospitalized patients with COVID-19. METHODS: In this multicenter, retrospective, cohort study, we examined 828 hospitalized patients with confirmed COVID-19 hospitalized in Wuhan Union Hospital and Central Hospital of Wuhan between January 12 and February 9, 2020. Among the 828 patients, 516 and 186 consecutive patients admitted in Wuhan Union Hospital were enrolled in the training cohort and the validation cohort, respectively. A total of 126 patients hospitalized in Central Hospital of Wuhan were enrolled in a second external validation cohort. Demographic, clinical, radiographic, and laboratory measures; treatment; proximate causes of death; and 14-day and 28-day mortality are described. Patients' data were collected by reviewing the medical records, and their 14-day and 28-day outcomes were followed up. RESULTS: Of the 828 patients, 146 deaths were recorded until May 18, 2020. In the training set, multivariate Cox regression indicated that older age, lactate dehydrogenase level over 360 U/L, neutrophil-to-lymphocyte ratio higher than 8.0, and direct bilirubin higher than 5.0 µmol/L were independent predictors of 28-day mortality. Nomogram scoring systems for predicting the 14-day and 28-day survival probability of patients with COVID-19 were developed and exhibited strong discrimination and calibration power in the two external validation cohorts (C-index, 0.878 and 0.839). CONCLUSION: Older age, high lactate dehydrogenase level, evaluated neutrophil-to-lymphocyte ratio, and high direct bilirubin level were independent predictors of 28-day mortality in adult hospitalized patients with confirmed COVID-19. The nomogram system based on the four factors revealed good discrimination and calibration, suggesting good clinical utility.

Fasting blood glucose at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes: a multi-centre retrospective study.

AIMS/HYPOTHESIS: Hyperglycaemia is associated with an elevated risk of mortality in community-acquired pneumonia, stroke, acute myocardial infarction, trauma and surgery, among other conditions. In this study, we examined the relationship between fasting blood glucose (FBG) and 28-day mortality in coronavirus disease 2019 (COVID-19) patients not previously diagnosed as having diabetes. METHODS: We conducted a retrospective study involving all consecutive COVID-19 patients with a definitive 28-day outcome and FBG measurement at admission from 24 January 2020 to 10 February 2020 in two hospitals based in Wuhan, China. Demographic and clinical data, 28-day outcomes, in-hospital complications and CRB-65 scores of COVID-19 patients in the two hospitals were analysed. CRB-65 is an effective measure for assessing the severity of pneumonia and is based on four indicators, i.e. confusion, respiratory rate (>30/min), systolic blood pressure (≤90 mmHg) or diastolic blood pressure (≤60 mmHg), and age (≥65 years). RESULTS: Six hundred and five COVID-19 patients were enrolled, including 114 who died in hospital. Multivariable Cox regression analysis showed that age (HR 1.02 [95% CI 1.00, 1.04]), male sex (HR 1.75 [95% CI 1.17, 2.60]), CRB-65 score 1-2 (HR 2.68 [95% CI 1.56, 4.59]), CRB-65 score 3-4 (HR 5.25 [95% CI 2.05, 13.43]) and FBG ≥7.0 mmol/l (HR 2.30 [95% CI 1.49, 3.55]) were independent predictors for 28-day mortality. The OR for 28-day in-hospital complications in those with FBG ≥7.0 mmol/l and 6.1-6.9 mmol/l vs <6.1 mmol/l was 3.99 (95% CI 2.71, 5.88) or 2.61 (95% CI 1.64, 4.41), respectively. CONCLUSIONS/INTERPRETATION: FBG ≥7.0 mmol/l at admission is an independent predictor for 28-day mortality in patients with COVID-19 without previous diagnosis of diabetes. Glycaemic testing and control are important to all COVID-19 patients even where they have no pre-existing diabetes, as most COVID-19 patients are prone to glucose metabolic disorders. Graphical abstract.