Role of angiotensin-converting enzyme 2 (ACE2) in COVID-19.

An outbreak of pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that started in Wuhan, China, at the end of 2019 has become a global pandemic. Both SARS-CoV-2 and SARS-CoV enter host cells via the angiotensin-converting enzyme 2 (ACE2) receptor, which is expressed in various human organs. We have reviewed previously published studies on SARS and recent studies on SARS-CoV-2 infection, named coronavirus disease 2019 (COVID-19) by the World Health Organization (WHO), confirming that many other organs besides the lungs are vulnerable to the virus. ACE2 catalyzes angiotensin II conversion to angiotensin-(1-7), and the ACE2/angiotensin-(1-7)/MAS axis counteracts the negative effects of the renin-angiotensin system (RAS), which plays important roles in maintaining the physiological and pathophysiological balance of the body. In addition to the direct viral effects and inflammatory and immune factors associated with COVID-19 pathogenesis, ACE2 downregulation and the imbalance between the RAS and ACE2/angiotensin-(1-7)/MAS after infection may also contribute to multiple organ injury in COVID-19. The SARS-CoV-2 spike glycoprotein, which binds to ACE2, is a potential target for developing specific drugs, antibodies, and vaccines. Restoring the balance between the RAS and ACE2/angiotensin-(1-7)/MAS may help attenuate organ injuries. SARS-CoV-2 enters lung cells via the ACE2 receptor. The cell-free and macrophage-phagocytosed virus can spread to other organs and infect ACE2-expressing cells at local sites, causing multi-organ injury.

Prognostic Assessment of COVID-19 in the Intensive Care Unit by Machine Learning Methods: Model Development and Validation.

BACKGROUND: Patients with COVID-19 in the intensive care unit (ICU) have a high mortality rate, and methods to assess patients' prognosis early and administer precise treatment are of great significance. OBJECTIVE: The aim of this study was to use machine learning to construct a model for the analysis of risk factors and prediction of mortality among ICU patients with COVID-19. METHODS: In this study, 123 patients with COVID-19 in the ICU of Vulcan Hill Hospital were retrospectively selected from the database, and the data were randomly divided into a training data set (n=98) and test data set (n=25) with a 4:1 ratio. Significance tests, correlation analysis, and factor analysis were used to screen 100 potential risk factors individually. Conventional logistic regression methods and four machine learning algorithms were used to construct the risk prediction model for the prognosis of patients with COVID-19 in the ICU. The performance of these machine learning models was measured by the area under the receiver operating characteristic curve (AUC). Interpretation and evaluation of the risk prediction model were performed using calibration curves, SHapley Additive exPlanations (SHAP), Local Interpretable Model-Agnostic Explanations (LIME), etc, to ensure its stability and reliability. The outcome was based on the ICU deaths recorded from the database. RESULTS: Layer-by-layer screening of 100 potential risk factors finally revealed 8 important risk factors that were included in the risk prediction model: lymphocyte percentage, prothrombin time, lactate dehydrogenase, total bilirubin, eosinophil percentage, creatinine, neutrophil percentage, and albumin level. Finally, an eXtreme Gradient Boosting (XGBoost) model established with the 8 important risk factors showed the best recognition ability in the training set of 5-fold cross validation (AUC=0.86) and the verification queue (AUC=0.92). The calibration curve showed that the risk predicted by the model was in good agreement with the actual risk. In addition, using the SHAP and LIME algorithms, feature interpretation and sample prediction interpretation algorithms of the XGBoost black box model were implemented. Additionally, the model was translated into a web-based risk calculator that is freely available for public usage. CONCLUSIONS: The 8-factor XGBoost model predicts risk of death in ICU patients with COVID-19 well; it initially demonstrates stability and can be used effectively to predict COVID-19 prognosis in ICU patients.

Serum Inflammatory Markers in Patients with Adenovirus Respiratory Infection.

BACKGROUND The aim of this study was to characterize adenovirus-associated acute respiratory infection (ARI) and observe correlations between inflammatory markers and severity of human adenovirus type 7 (HAdV-7) infection, and to evaluate the potential of inflammatory markers to predict progression from upper-respiratory infection (URI) to adenovirus pneumonia (AdP). MATERIAL AND METHODS A total of 81 patients with adenovirus-associated ARI and confirmed HAdV-7 infection were enrolled. Cases were classified according to severity, as AdP and URI. Demographic and clinical data were collected retrospectively. Clinical features and serum inflammatory markers were evaluated and compared according to the severity of adenoviral infection. RESULTS We observed high-grade fever and strong inflammatory response in patients with HAdV-7-associated ARI. Procalcitonin (PCT), interleukin 6 (IL-6), and C-reactive protein concentrations were higher in patients with AdP than in those with URI. The mean erythrocyte sedimentation rate (ESR) was significantly higher in patients with AdP (p=0.008). Reduced serum prealbumin levels were observed in patients with HAdV-7 infection. In the analysis of URI to AdP prediction ability, areas under the curve (AUCs) for all inflammatory markers were <0.9. We found that 35.9% of pneumonia had ≥2 lobars of lung infiltrate and bilateral lung infiltrate, and 20% of patients with SP had pleural effusion and atelectasis. CONCLUSIONS IL-6 and ESR were associated with the severity of HAdV-7 respiratory infection. No inflammatory marker in our study predicted URI-to-AdP progression accurately. Lung infiltration and consolidation are common in HRCT in AdP. Multiple- or single-lobar/segment consolidation was most common in SP. SP progressed very quickly after onset.

Effects of traditional Chinese medicine on treatment outcomes in severe COVID-19 patients: a single-centre study.

As the search for effective treatments for COVID-19 continues, the high mortality rate among critically ill patients in Intensive Care Units (ICU) presents a profound challenge. This study explores the potential benefits of traditional Chinese medicine (TCM) as a supplementary treatment for severe COVID-19. A total of 110 critically ill COVID-19 patients at the Intensive Care Unit (ICU) of Vulcan Hill Hospital between Feb., 2020, and April, 2020 (Wuhan, China) participated in this observational study. All patients received standard supportive care protocols, with a subset of 81 also receiving TCM as an adjunct treatment. Clinical characteristics during the treatment period and the clinical outcome of each patient were closely monitored and analysed. Our findings indicated that the TCM group exhibited a significantly lower mortality rate compared with the non-TCM group (16 of 81 vs 24 of 29; 0.3 vs 2.3 person/month). In the adjusted Cox proportional hazards models, TCM treatment was associated with improved survival odds (P < 0.001). Furthermore, the analysis also revealed that TCM treatment could partially mitigate inflammatory responses, as evidenced by the reduced levels of proinflammatory cytokines, and contribute to the recovery of multiple organic functions, thereby potentially increasing the survival rate of critically ill COVID-19 patients.

Highly pathogenic coronavirus N protein aggravates inflammation by MASP-2-mediated lectin complement pathway overactivation.

Excessive inflammatory responses contribute to the pathogenesis and lethality of highly pathogenic human coronaviruses, but the underlying mechanism remains unclear. In this study, the N proteins of highly pathogenic human coronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV), middle east respiratory syndrome coronavirus (MERS-CoV) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were found to bind MASP-2, a key serine protease in the lectin pathway of complement activation, resulting in excessive complement activation by potentiating MBL-dependent MASP-2 activation, and the deposition of MASP-2, C4b, activated C3 and C5b-9. Aggravated inflammatory lung injury was observed in mice infected with adenovirus expressing the N protein. Complement hyperactivation was also observed in SARS-CoV-2-infected patients. Either blocking the N protein:MASP-2 interaction, MASP-2 depletion or suppressing complement activation can significantly alleviate N protein-induced complement hyperactivation and lung injury in vitro and in vivo. Altogether, these data suggested that complement suppression may represent a novel therapeutic approach for pneumonia induced by these highly pathogenic coronaviruses.

Diagnostic value of urine sTREM-1 for sepsis and relevant acute kidney injuries: a prospective study.

INTRODUCTION: We explored the diagnostic value of a urine soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) for early sepsis identification, severity and prognosis assessment, and for secondary acute kidney injury (AKI). We compared this with white blood cell (WBC) counts, serum C-reactive protein (CRP), serum procalcitonin (PCT), urine output, creatinine clearance (CCr), serum creatinine (SCr), and blood urea nitrogen (BUN). METHODS: We enrolled 104 subjects admitted to the ICU: 16 cases with systemic inflammatory response syndrome (SIRS); 35 with sepsis and 53 with severe sepsis. Results for urine sTREM-1, WBC, serum CRP and serum PCT were recorded on days 1, 3, 5, 7, 10, and 14. For 17 sepsis cases diagnosed with secondary AKI, comparisons between their urine sTREM-1, urine output, CCr, SCr and BUN at diagnosis and 48 h before diagnosis were made. RESULTS: On the day of admission to the ICU, and compared with the SIRS group, the sepsis group exhibited higher levels of urine sTREM-1 and Acute Physiologic Assessment and Chronic Health Evaluation II (APACHE II) scores (P < 0.05). Areas under the curve (AUC) shaped by the scores were 0.797 (95% CI 0.711 to 0.884) and 0.722 (95% CI 0.586 to 0.858), respectively. On days 1, 3, 5, 7, 10, and 14, urine sTREM-1, serum PCT and WBC levels registered higher in the severe sepsis group in contrast to the sepsis group (P < 0.05). Urine sTREM-1 and serum PCT levels continuously increased among non-survivors, while WBC and serum CRP levels in both groups declined. For 17 patients with AKI, urine sTREM-1, SCr and BUN levels at 48 h before AKI diagnosis were higher, and CCr level was lower than those for non-AKI subjects (P < 0.05). AUC for urine sTREM-1 was 0.922 (95% CI 0.850 to 0.995), the sensitivity was 0.941, and the specificity was 0.76 (based on a cut-off point of 69.04 pg/ml). Logistic regression analysis showed that urine sTREM-1 and severity were risk factors related to AKI occurrence. CONCLUSIONS: Besides being non-invasive, urine sTREM-1 testing is more sensitive than testing WBC, serum CRP, and serum PCT for the early diagnosis of sepsis, as well as for dynamic assessments of severity and prognosis. It can also provide an early warning of possible secondary AKI in sepsis patients. TRIAL REGISTRATION: ClinicalTrial.gov identifier NCT01333657.

[Clinical analysis of value of different modes of respiratory support in the treatment of critical patients].

OBJECTIVE: To investigate the relationship between the successful results with different methods and time of initiation of respiratory support in critically ill patients. METHODS: The clinical data of 458 critical care patients were reviewed and analyzed. Among the patients, there were 47 cases of cardio-pulmonary resuscitation, 105 cases of acute airway obstruction, 156 cases of acute respiratory failure, and 150 cases of chronic respiratory failure. Intubation, or tracheostomy, or non-invasive positive pressure ventilation (NPPV) at different times and occasions were performed in the patients. RESULTS: One hundred and seventeen cases (25.5%) died during the respiratory support treatment, 49 cases gave up the treatment, and 292 patients (63.8%) were cured after mechanical ventilation. As the success rate was the lowest in patients who survived cardio-pulmonary resuscitation (21.3%, 10/47), it was higher in acute respiratory failure (55.1%, 86/156), and the best result (82.8%, 87/105) was obtained in the acute airway obstruction group and patients with chronic respiratory failure (72.7%, 109/150). In the group of patients undergoing early respiratory support, the cure rate was 95.0% (57/60) in patients with invasive method, and 95.5% (21/22) in the NPPV group. The result was significantly different compared with that of later treatment group [81.7% (68/82) in invasive group, and 60.9% (2/29) in NPPV group, both P<0.01]. It demonstrated that the earlier the respiratory support was given the better results. If the respiratory support was delayed, cure rate was significantly reduced [65.6% (63/96) in invasive group and 48.1% (13/27) in NPPV group, both P<0.01]. The cure rate was no difference between different modes of respiratory support between early treatment groups, however, invasive respiratory support was much better than NPPV [44.4% (40/90) and 0 (0/5)] when instituted in the late stages (all P<0.01). CONCLUSION: It is of prime importance to ensure optimal ventilation in the early stage of diseases, the difficulty and risk of establishment of a patent airway are main problems in the treatment of critically ill patients.

Asymptomatic pulmonary tuberculosis mimicking lung cancer on imaging: A retrospective study.

Asymptomatic pulmonary tuberculosis (PTB) mimicking lung cancer is rare and has been documented in few studies. Accurately diagnosing this atypical disease remains an enormous challenge for clinicians. The aim of the present study was to characterize asymptomatic patients with PTB who were initially diagnosed with lung cancer according to their chest computer tomography (CT) or whole-body 18F-fludeoxyglucose-positron emission tomography-computer tomography (PET-CT) presentations. The clinical characteristics and radiographic features of patients with PTB were analyzed and compared to those of patients with lung cancer. In patients with PTB, all lesions exhibited suspected malignant signs on chest CT and the maximum standard uptake value (SUVmax) of PET-CT imaging was between 2.65 and 10.9. Compared with lung cancer, the factors associated with PTB included an age <60 years (82% vs. 46%, P=0.03), being male (77% vs. 51%, P=0.025), the presence of diabetes (55% vs. 16%, P<0.01), spiculated margins (82% vs. 44%, P=0.002) and a lower SUVmax (P=0.036). The optimal cut-off level was SUVmax 8.45 for discriminating between PTB and lung cancer. At this point, the sensitivity and specificity were 63.0 and 88.9%, respectively. The results of the current study revealed methods of distinguishing between the two similar diseases. Furthermore, the results of the current study may increase awareness that although imaging of lesions may resemble lung cancer, a diagnosis of PTB should be considered. Accurate diagnosis of PTB would mean that patients would be able to avoid undergoing unnecessary operations that induce a high financial burden.

A scoring system to effectively evaluate central nervous system tuberculosis in patients with military tuberculosis.

There is currently no convenient way to effectively evaluate whether a miliary tuberculosis patient is complicated with central nervous system (CNS) tuberculosis. We aimed to find such a way by analyzing the clinical data of these patients. Fifty patients with confirmed miliary tuberculosis and 31 patients with confirmed miliary tuberculosis complicated with CNS tuberculosis from 2010 to 2014 were selected. Their general conditions, clinical features and laboratory tests were analyzed. Factors that were significantly different between them were chosen to performed multivariate and univariate logistic regression analyses, and factors with significant P values were used to establish a scoring system. Eight factors, i.e., age, cough, nausea, headache, hemoglobin (HGB), serum albumin (ALB), C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR), were significantly different (P < 0.05). Multivariate logistic regression analysis showed that ALB was the independent risk predictor (HR = 1.29, 95% CI 1.09-1.52, P < 0.01), whereas the others were non-independent predictors except age (P < 0.05). The scoring system was based on a summation of the scores of the assigned values of the seven predictors and had an area under the curve (AUC) of 0.86 to confirm CNS tuberculosis, with a sensitivity of 81.5% and a specificity of 81.4% at a score of 0.75 and with a specificity of 95.3% at a score of 2.75. In contrast, a score below -0.75 excluded CNS tuberculosis, with a sensitivity of 88.9% and a specificity of 62.7%. The scoring system should be useful to evaluate whether a miliary tuberculosis patient is complicated with CNS tuberculosis and could help doctors avoid excessive investigation.

CXCL10/IP-10 Neutralization Can Ameliorate Lipopolysaccharide-Induced Acute Respiratory Distress Syndrome in Rats.

The role of C-X-C motif chemokine 10 (CXCL10), a pro-inflammatory factor, in the development of acute respiratory distress syndrome (ARDS) remains unclear. In this study, we explored the role of CXCL10 and the effect of CXCL10 neutralization in lipopolysaccharide (LPS)-induced ARDS in rats. The expression of CXCL10 and its receptor chemokine receptor 3(CXCR3) increased after LPS induction. Moreover, neutralization of CXCL10 ameliorated the severity of ARDS by reducing pulmonary edema, inhibiting the release of inflammatory mediators (IFN-γ, IL-6 and ICAM-1) and limiting inflammatory cells (neutrophils, macrophages, CD8+ T cells) influx into the lung, with a reduction in CXCR3 expression in neutrophils and macrophages. Therefore, CXCL10 could be a potential therapeutic target in LPS-induced ARDS.

Heliox as a driving gas to atomize inhaled drugs on acute exacerbation of chronic obstructive pulmonary disease: a prospective clinical study.

BACKGROUND: Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) is a common condition, which affects not only the quality of life of patients but also their prognosis. The purpose of this study was to explore the effects of an inhaled salbutamol sulfate solution and an inhalation suspension of the glucocorticoid budesonide that were atomized with heliox to treat patients with AECOPD. METHODS: Twenty-three patients with AECOPD were divided into a treatment group (He/O2 = 70%/30%) and a control group (N2/O2 = 70%/30%). The salbutamol sulfate and budesonide were administered by inhalation twice a day for 7 days. Vital signs, arterial blood gas levels, pulmonary function and the levels of serum myostatin (sMSTN) were measured and lung vibration imaging was performed. RESULTS: We found that the PaO2 and PaCO2 values were not significantly different between the two groups at the various time points (P > 0.05). There were also no significant differences in any of the parameters of pulmonary function between the two groups. However, after baseline correction, the increase rate of the forced expiratory volume in one second (FEV1), the forced vital capacity (FVC), and the maximum minute ventilation (MVV) appeared to be significantly increased at some time points compared with the baseline (before treatment) in both groups (P < 0.05). Although the values of quantitative lung distribution (QLD) for different regions and the levels of sMSTN were slightly different between the two groups, the repeated measures analysis of variance (ANOVA) revealed that there were no significant differences between the two groups or within any group (P > 0.05). CONCLUSION: Although the use of heliox as a driving gas can improve symptoms and benefit patients with AECOPD, the heliox treatment group did not have significant differences in arterial blood gases, lung function, lung vibration response imaging or the levels of sMSTN compared with the control group. (Chinese Clinical Trial Register Center ChiCTRTRC-00000273).