Unique epidemiological and clinical features of the emerging 2019 novel coronavirus pneumonia (COVID-19) implicate special control measures

By 27 February 2020, the outbreak of coronavirus disease 2019 (COVID-19) caused 82 623 confirmed cases and 2858 deaths globally, more than severe acute respiratory syndrome (SARS) (8273 cases, 775 deaths) and Middle East respiratory syndrome (MERS) (1139 cases, 431 deaths) caused in 2003 and 2013, respectively. COVID-19 has spread to 46 countries internationally. Total fatality rate of COVID-19 is estimated at 3.46% by far based on published data from the Chinese Center for Disease Control and Prevention (China CDC). Average incubation period of COVID-19 is around 6.4 days, ranges from 0 to 24 days. The basic reproductive number (R₀) of COVID-19 ranges from 2 to 3.5 at the early phase regardless of different prediction models, which is higher than SARS and MERS. A study from China CDC showed majority of patients (80.9%) were considered asymptomatic or mild pneumonia but released large amounts of viruses at the early phase of infection, which posed enormous challenges for containing the spread of COVID-19. Nosocomial transmission was another severe problem. A total of 3019 health workers were infected by 12 February 2020, which accounted for 3.83% of total number of infections, and extremely burdened the health system, especially in Wuhan. Limited epidemiological and clinical data suggest that the disease spectrum of COVID-19 may differ from SARS or MERS. We summarize latest literatures on genetic, epidemiological, and clinical features of COVID-19 in comparison to SARS and MERS and emphasize special measures on diagnosis and potential interventions. This review will improve our understanding of the unique features of COVID-19 and enhance our control measures in the future.     

Epidemiological Features of 105 Patients Infected with the COVID-19

ObjectiveTo investigate and evaluate the clinical features of patients infected with the 2019 novel coronavirus (COVID-19) outside of Wuhan.Methods105 patients admitted to our hospital with clinical- and laboratory-confirmed COVID-19 infection were studied. Data were collected from January 17, 2020 to March 5, 2020.Results105 patients (57 male and 48 female) were confirmed to have COVID-19 infection. Among the 105 patients, 55 (52%) had made short trips to Wuhan during the two weeks before the onset of illness, and these were the first-generation confirmed cases. An exact date of close contact with someone in Wenzhou with confirmed or suspected COVID-19 infection from Wuhan (the second-generation confirmed cases) could be provided by 38 (36%) patients. Of the remaining patients, six (6%; the third-generation confirmed cases) were familial clusters of the second-generation confirmed cases, three (3%) had no definite epidemiological features, and 16 (15%) were from the same location as for the case report.ConclusionDue to the infectiousness of COVID-19, patients with infections should be diagnosed and treated as early as possible after developing fever symptoms or showing other clinical characteristics or imaging features. With respect to high-risk cases, we must focus on any complications that arise and take effective measures to treat them immediately. This will significantly improve the prognosis of patients with severe infections.     

2019 novel coronavirus disease (COVID-19) in Taiwan: Reports of two cases from Wuhan,China

We reported two cases with community-acquired pneumonia caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who returned from Wuhan, China in January, 2020. The reported cases highlight non-specific clinical presentations of 2019 novel coronavirus disease (COVID-19) as well as the importance of rapid laboratory-based diagnosis.     

Using different machine learning models to classify patients into mild and severe cases of COVID-19 based on multivariate blood testing

COVID-19 is a serious respiratory disease. The ever-increasing number of cases is causing heavier loads on the health service system. Using 38 blood test indicators on the first day of admission for the 422 patients diagnosed with COVID-19 (from January 2020 to June 2021) to construct different machine learning (ML) models to classify patients into either mild or severe cases of COVID-19. All models show good performance in the classification between COVID-19 patients into mild and severe disease. The area under the curve (AUC) of the random forest model is 0.89, the AUC of the naive Bayes model is 0.90, the AUC of the support vector machine model is 0.86, and the AUC of the KNN model is 0.78, the AUC of the Logistic regression model is 0.84, and the AUC of the artificial neural network model is 0.87, among which the naive Bayes model has the best performance. Different ML models can classify patients into mild and severe cases based on 38 blood test indicators taken on the first day of admission for patients diagnosed with COVID-19.     

Risk factors for disease severity,unimprovement, and mortality in COVID-19 patients in Wuhan,China

ObjectiveIn December 2019, coronavirus disease (COVID-19) emerged in Wuhan. However, the characteristics and risk factors associated with disease severity, unimprovement and mortality are unclear and our objective is to throw some light on these.MethodsAll consecutive patients diagnosed with COVID-19 admitted to the Renmin Hospital of Wuhan University from January 11 to February 6, 2020, were enrolled in this retrospective cohort study.ResultsA total of 663 COVID-19 patients were included in this study. Among these, 247 (37.3%) had at least one kind of chronic disease; 0.5% of the patients (n = 3) were diagnosed with mild COVID-19, while 37.8% (251/663), 47.5% (315/663), and 14.2% (94/663) were in moderate, severe, and critical conditions, respectively. In our hospital, during follow-up 251 of 663 patients (37.9%) improved and 25 patients died, a mortality rate of 3.77%. Older patients (>60 years old) and those with chronic diseases were prone to have a severe to critical COVID-19 condition, to show unimprovement, and to die (p <0.001, <0.001). Multivariate logistic regression analysis identified being male (OR = 0.486, 95%CI 0.311–0.758; p 0.001), having a severe COVID-19 condition (OR = 0.129, 95%CI 0.082–0.201; p <0.001), expectoration (OR = 1.796, 95%CI 1.062–3.036; p 0.029), muscle ache (OR = 0.309, 95%CI 0.153–0.626; p 0.001), and decreased albumin (OR = 1.929, 95%CI 1.199–3.104; p 0.007) as being associated with unimprovement in COVID-19 patients.ConclusionMale sex, a severe COVID-19 condition, expectoration, muscle ache, and decreased albumin were independent risk factors which influence the improvement of COVID-19 patients.     

Correlation between the variables collected at admission and progression to severe cases during hospitalization among patients with COVID-19 in Chongqing

Mortality is high among severe patients with 2019 novel coronavirus-infected disease (COVID-19). Early prediction of progression to severe cases is needed. We retrospectively collected patients with COVID-19 in two hospital of Chongqing from 1st January to 29th February 2020. At admission, we collected the demographics and laboratory tests to predict whether the patient would progress to severe cases in hospitalization. Severe case was confirmed when one of the following criteria occurred: (a) dyspnea, respiratory rate ≥30 breaths/min, (b) blood oxygen saturation ≤93%, and (c) PaO₂/FiO₂ ≤ 300 mm Hg. At admission, 348 mild cases were enrolled in this study. Of them, 20 (5.7%) patients progressed to severe cases after median 4.0 days (interquartile range: 2.3-6.0). Pulmonary inflammation index, platelet counts, sodium, C-reactive protein, prealbumin, and PaCO₂ showed good distinguishing power to predict progression to severe cases (each area under the curve of receiver operating characteristics [AUC] ≥ 0.8). Age, heart rate, chlorine, alanine aminotransferase, aspartate aminotransferase, procalcitonin, creatine kinase, pH, CD3 counts, and CD4 counts showed moderate distinguishing power (each AUC between 0.7-0.8). And potassium, creatinine, temperature, and D-dimer showed mild distinguishing power (each AUC between 0.6-0.7). In addition, higher C-reactive protein was associated with shorter time to progress to severe cases (r = −0.62). Several easily obtained variables at admission are associated with progression to severe cases during hospitalization. These variables provide a reference for the medical staffs when they manage the patients with COVID-19.     

Unbiased identification of clinical characteristics predictive of COVID-19 severity

There is currently limited clinical ability to identify COVID-19 patients at risk for severe outcomes. To unbiasedly identify metrics associated with severe outcomes in COVID-19 patients, we conducted a retrospective study of 835 COVID-19 positive patients at a single academic medical center between March 10, 2020 and October 13, 2020. As of December 1, 2020, 656 (79%) patients required hospitalization and 149 (18%) died. Unbiased comparisons of all clinical characteristics and mortality revealed that abnormal pH (OR 8.54, 95% CI 5.34–13.6), abnormal creatinine (OR 6.94, 95% CI 4.22–11.4), and abnormal PTT (OR 4.78, 95% CI 3.11–7.33) were most significantly associated with mortality. Correlation with ordinal severity scores confirmed these associations, in addition to associations between respiratory rate (Spearman’s rho? = ?0.56), absolute neutrophil count (Spearman’s rho ?= ?0.5), and C-reactive protein (Spearman’s rho ?=? 0.59) with disease severity. Unsupervised principal component analysis and machine learning model classification of patient demographics, laboratory results, medications, comorbidities, signs and symptoms, and vitals are capable of separating patients on the basis of COVID-19 mortality (AUC 0.82). This retrospective analysis identifies laboratory and clinical metrics most relevant to predict COVID-19 severity.

     

Understanding of COVID-19 based on current evidence

Since December 2019, a series of unexplained pneumonia cases have been reported in Wuhan, China. On 12 January 2020, the World Health Organization (WHO) temporarily named this new virus as the 2019 novel coronavirus (2019-nCoV). On 11 February 2020, the WHO officially named the disease caused by the 2019-nCoV as coronavirus disease (COVID-19). The COVID-19 epidemic is spreading all over the world, especially in China. Based on the published evidence, we systematically discuss the characteristics of COVID-19 in the hope of providing a reference for future studies and help for the prevention and control of the COVID-19 epidemic.     

Impact of COVID-19 on Pregnancy

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is an emerging disease. There has been a rapid increase in cases and deaths since it was identified in Wuhan, China, in early December 2019, with over 4,000,000 cases of COVID-19 including at least 250,000 deaths worldwide as of May 2020. However, limited data about the clinical characteristics of pregnant women with COVID-19 have been reported. Given the maternal physiologic and immune function changes during pregnancy, pregnant women may be at a higher risk of being infected with SARS-CoV-2 and developing more complicated clinical events. Information on severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) may provide insights into the effects of COVID-19''s during pregnancy. Even though SARS and MERS have been associated with miscarriage, intrauterine death, fetal growth restriction and high case fatality rates, the clinical course of COVID-19 pneumonia in pregnant women has been reported to be similar to that in non-pregnant women. In addition, pregnant women do not appear to be at a higher risk of catching COVID-19 or suffering from more severe disease than other adults of similar age.Moreover, there is currently no evidence that the virus can be transmitted to the fetus during pregnancy or during childbirth. Babies and young children are also known to only experience mild forms of COVID-19. The aims of this systematic review were to summarize the possible symptoms, treatments, and pregnancy outcomes of women infected with COVID-19 during pregnancy.     

COVID-19 patients benefit from early antiviral treatment: A comparative,retrospective study

The outbreak of COVID-19, caused by severe acute respiratory syndrome coronavirus 2, started in December 2019, Wuhan, China. We aimed to figure out the time-point and duration of using antiviral drugs for receiving the maximal effects in patients with COVID-19. In this study, we enrolled 129 confirmed COVID-19 mild to moderate patients who had been treated with antiviral drugs during their hospitalization in Wuhan Union Hospital China. The patients were divided into an early antiviral treatment group and late antiviral treatment group. The demographic data, laboratory tests, the virus clearance time, chest computed tomography scans, and so forth were extracted, calculated, and compared between two groups. Our data showed that the median time from illness onset to initiation of antiviral treatment was 6 days in all patients. The group with early antiviral treatment demonstrated 7 days shorter in the virus clearance time when compared to the group with late antiviral treatment. After virus clearance, the group with early antiviral treatment showed milder illness than the group with late antiviral treatment. Early antiviral treatment could effectively shorten the virus clearance time, and prevent the rapid progression of COVID-19. Therefore, the COVID-19 patients should receive combined therapies with antiviral treatment at an early stage.     

Featuring COVID-19 cases via screening symptomatic patients with epidemiologic link during flu season in a medical center of central Taiwan

BackgroundCoronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CO-V-2), was first reported in Wuhan, Hubei province, China has now rapidly spread over 50 countries. For the prevention and control of infection, Taiwan Centers for Disease Control initiated testing of SARS-CoV-2 on January 24th 2020 for persons suspected with this disease. Until February 28th, 43 flu-like symptomatic patients were screened in China Medical University Hospital.MethodsTwo patients were confirmed positive for SARS-CoV-2 infection by rRT-PCR as COVID-19 patients A and B. Causative pathogens for included patients were detected using FilmArray™ Respiratory Panel. We retrospectively analyzed the clinical presentations, laboratory data, radiologic findings, and travel and exposure contact histories, of the COVID-19 patients in comparison to those with other respiratory infections.ResultsThrough contact with Taiwan No. 19 case patient on 27th January, COVID-19 patients A and B were infected. Both patients had no identified comorbidities and developed mild illness with temporal fever, persistent cough, and lung interstitial infiltrates. Owing to the persistence of positive SARS-CoV-2 in respiratory specimen, the two COVID-19 patients are still in the isolation rooms despite recovery until 10th of March. The results of FilmArrayTM Respiratory Panel revealed 22 of the 41 non-COVID-19 patients were infected by particular pathogens. In general, seasonal respiratory pathogens are more prevalent than SARS-CoV-2 in symptomatic patients in non- COVID-19 endemic area during the flu season. Since all patients shared similar clinical and laboratory findings, expanded surveillance of detailed exposure history for suspected patients and application of rapid detection tools are highly recommended.     

COVID-19 gone bad: A new character in the spectrum of the hyperferritinemic syndrome?

The severe form of COVID-19 share several clinical and laboratory features with four entities gathered under the term “hyperferritinemic syndromes” and including macrophage activation syndrome (MAS), adult-onset Still's disease (AOSD), catastrophic anti-phospholipid syndrome (CAPS) and septic shock. COVID-19 systemic inflammatory reaction and “hyperferritinemic syndromes” are all characterized by high serum ferritin and a life-threatening hyper-inflammation sustained by a cytokines storm which eventually leads to multi-organ failure. In this review, we analyze the possible epidemiological and molecular mechanisms responsible for hyper-inflammation in patients with severe COVID-19 and we underline the similarities between this condition and “hyperferritinemic syndromes” which would allow considering severe COVID-19 as a fifth member of this spectrum of inflammatory conditions.     

Internationally lost COVID-19 cases

BackgroundWith its epicenter in Wuhan, China, the COVID-19 outbreak was declared a pandemic by the World Health Organization (WHO). While many countries have implemented flight restrictions to China, an increasing number of cases with or without travel background to China are confirmed daily. These developments support concerns on possible unidentified and unreported international COVID-19 cases, which could lead to new local disease epicenters.MethodsWe have analyzed all available data on the development of international COVID-19 cases from January 20th, 2020 until February 18th, 2020. COVID-19 cases with and without travel history to China were divided into cohorts according to the Healthcare Access and Quality Index (HAQ-Index) of each country. Chi-square and Post-hoc testing were performed.ResultsWhile COVID-19 cases with travel history to China seem to peak for each HAQ-cohort, the number of non-travel related COVID-19 cases seem to continuously increase in the HAQ-cohort of countries with higher medical standards. Further analyses demonstrate a significantly lower proportion of reported COVID-19 cases without travel history to China in countries with lower HAQ (HAQ I vs. HAQ II, posthoc p < 0.01).ConclusionsOur data indicate that countries with lower HAQ-index may either underreport COVID-19 cases or are unable to adequately detect them. Although our data may be incomplete and must be interpreted with caution, inconsistencies in reporting COVID-19 cases is a serious problem which might sabotage efforts to contain the virus.     

Risk factors for disease progression in patients with mild to moderate coronavirus disease 2019—a multi-centre observational study

ObjectivesSince December 2019, the novel coronavirus disease 2019 (COVID-19) that emerged in Wuhan city has spread rapidly around the world. The risk for poor outcome dramatically increases once a patient progresses to the severe or critical stage. The present study aims to investigate the risk factors for disease progression in individuals with mild to moderate COVID-19.MethodsWe conducted a cohort study that included 1007 individuals with mild to moderate COVID-19 from three hospitals in Wuhan. Clinical characteristics and baseline laboratory findings were collected. Patients were followed up for 28 days for observation of disease progression. The end point was the progression to a more severe disease stage.ResultsDuring a follow up of 28 days, 720 patients (71.50%) had recovered or were symptomatically stable, 222 patients (22.05%) had progressed to severe disease, 22 patients (2.18%) had progressed to the critically ill stage and 43 patients (4.27%) had died. Multivariate Cox proportional hazards models identified that increased age (hazard ratio (HR) 2.56, 95% CI 1.97–3.33), male sex (HR 1.79, 95% CI 1.41–2.28), presence of hypertension (HR 1.44, 95% CI 1.11–1.88), diabetes (HR 1.82, 95% CI 1.35–2.44), chronic obstructive pulmonary disease (HR 2.01, 95% CI 1.38–2.93) and coronary artery disease (HR 1.83, 95% CI 1.26–2.66) were risk factors for disease progression. History of smoking was protective against disease progression (HR 0.56, 95% CI 0.34–0.91). Elevated procalcitonin (HR 1.72, 95% CI 1.02–2.90), urea nitrogen (HR 1.72, 95% CI 1.21–2.43), α-hydroxybutyrate dehydrogenase (HR 3.02, 95% CI 1.26–7.21) and D-dimer (HR 2.01, 95% CI 1.12–3.58) at baseline were also associated with risk for disease progression.ConclusionsThis study identified a panel of risk factors for disease progression in individuals with mild to moderate COVID-19.     

The impact of COPD and smoking history on the severity of COVID-19: A systemic review and meta-analysis

Comorbidities are associated with the severity of coronavirus disease 2019 (COVID-19). This meta-analysis aimed to explore the risk of severe COVID-19 in patients with pre-existing chronic obstructive pulmonary disease (COPD) and ongoing smoking history. A comprehensive systematic literature search was carried out to find studies published from December 2019 to 22 March 2020 from five databases. The languages of literature included English and Chinese. The point prevalence of severe COVID-19 in patients with pre-existing COPD and those with ongoing smoking was evaluated with this meta-analysis. Overall 11 case series, published either in Chinese or English language with a total of 2002 cases, were included in this study. The pooled OR of COPD and the development of severe COVID-19 was 4.38 (fixed-effects model; 95% CI: 2.34-8.20), while the OR of ongoing smoking was 1.98 (fixed-effects model; 95% CI: 1.29-3.05). There was no publication bias as examined by the funnel plot and Egger's test (P = not significant). The heterogeneity of included studies was moderate for both COPD and ongoing smoking history on the severity of COVID-19. COPD and ongoing smoking history attribute to the worse progression and outcome of COVID-19.     

CCR2 and DPP9 expression in the peripheral blood of COVID-19 patients: Influences of the disease severity and gender

IntroductionHyper-inflammatory reactions play a crucial role in the pathogenesis of the severe forms of COVID-19. However, clarification of the molecular basis of the inflammatory-related factors needs more consideration. The aim was to evaluate the gene expression of two fundamental molecules contributing to the induction of inflammatory like CCR2 and DPP9 in cells from peripheral blood samples from patients with various patterns of COVID-19.MethodsPeripheral blood samples were collected from 470 patients (235 male and 235 female) with RT-qPCR-confirmed COVID-19 test exhibiting moderate, severe, and critical symptoms based on WHO criteria. 100 healthy subjects (50 male and 50 female) were also enrolled in the study as a control group. The gene expression of DPP-9 and CCR-2 was assessed in the blood samples using real-time PCR method.ResultsThe COVID-19 patients in severe stage expressed higher levels of CCR2 and DPP9 compared with healthy controls. In male and female patients, the levels of CCR2 and DDP9 expression significantly differed between moderate, severe, and critical patterns (p < 0.0001) as well as between each COVID-19 form and control group (p < 0.0001). The male patients with severe COVID-19 expressed greater levels of CCR2 and DPP-9 than female with same disease form. The female patients with moderate and critical COVID-19 expressed greater levels of CCR2 and DPP-9 than male patients with same disease stage.ConclusionWe demonstrated that the expression of DPP-9 and CCR-2 was substantially increased in COVID-19 patients with different forms of disease. Considerable differences were also demonstrated between male and female with different patterns of disease. Therefore, we suggest to consider the gender of patients and disease severity for management of COVID-19.     

National surveillance of bacterial and fungal coinfection and secondary infection in COVID-19 patients in England: lessons from the first wave

ObjectivesThe impact of bacterial/fungal infections on the morbidity and mortality of persons with coronavirus disease 2019 (COVID-19) remains unclear. We have investigated the incidence and impact of key bacterial/fungal infections in persons with COVID-19 in England.MethodsWe extracted laboratory-confirmed cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (1st January 2020 to 2nd June 2020) and blood and lower-respiratory specimens positive for 24 genera/species of clinical relevance (1st January 2020 to 30th June 2020) from Public Health England's national laboratory surveillance system. We defined coinfection and secondary infection as a culture-positive key organism isolated within 1 day or 2–27 days, respectively, of the SARS-CoV-2-positive date. We described the incidence and timing of bacterial/fungal infections and compared characteristics of COVID-19 patients with and without bacterial/fungal infection.Results1% of persons with COVID-19 (2279/223413) in England had coinfection/secondary infection, of which >65% were bloodstream infections. The most common causative organisms were Escherichia coli, Staphylococcus aureus and Klebsiella pneumoniae. Cases with coinfection/secondary infections were older than those without (median 70 years (IQR 58–81) versus 55 years (IQR 38–77)), and a higher percentage of cases with secondary infection were of Black or Asian ethnicity than cases without (6.7% versus 4.1%, and 9.9% versus 8.2%, respectively, p < 0.001). Age-sex-adjusted case fatality rates were higher in COVID-19 cases with a coinfection (23.0% (95%CI 18.8–27.6%)) or secondary infection (26.5% (95%CI 14.5–39.4%)) than in those without (7.6% (95%CI 7.5–7.7%)) (p < 0.005).ConclusionsCoinfection/secondary bacterial/fungal infections were rare in non-hospitalized and hospitalized persons with COVID-19, varied by ethnicity and age, and were associated with higher mortality. However, the inclusion of non-hospitalized persons with asymptomatic/mild COVID-19 likely underestimated the rate of secondary bacterial/fungal infections. This should inform diagnostic testing and antibiotic prescribing strategy.     

Initial clinical features of suspected coronavirus disease 2019 in two emergency departments outside of Hubei,China

With an increasing number of Coronavirus Disease 2019 (COVID-19) cases outside of Hubei, emergency departments (EDs) and fever clinics are facing challenges posed by the large number of admissions of patients suspected to have COVID-19. Therefore, it is of crucial importance to study the initial clinical features of patients, to better differentiate between infected and uninfected patients outside Hubei. A total of 116 patients suspected of having COVID-19 who presented to two emergency departments in Anhui for the first time between 24 January 2020 and 20 February 2020 were enrolled in the study. The initial clinical data of these patients, such as epidemiological features, symptoms, laboratory results, and chest computed tomography (CT) findings were collected using a standard case report form on admission. Thirty-two patients were diagnosed with COVID-19; the remaining 84 patients were referred to as negative cases. The median age of the diagnosed patients was 46 years, but only 35 years for negative cases. History of exposure to Wuhan or COVID-19 patients in the previous 2 weeks was observed in 63% of the diagnosed and 44% of negative cases. Median time from illness onset to ED admission was 5 days for all patients, diagnosed patients, and negative cases, respectively. Fever was observed in 27 (84%) and 57 (68%) diagnosed and negative cases, respectively. Nineteen (59%) diagnosed and 24 (29%) negative cases had lymphopenia on admission in ED. A chest CT scan on admission revealed the presence of pneumonia in the majority of the diagnosed patients (30 out of 32, 94%) and in 56 (67%) negative cases. Bilateral involvement and ground-glass opacity (GGO) were present in 91% and 47% of the diagnosed patients. Thirty-two patients were diagnosed with COVID-19; the remaining 84 patients were referred to as negative cases. The median age of the diagnosed patients was 46 years, but only 35 years for negative cases. History of exposure to Wuhan or COVID-19 patients in the previous 2 weeks was observed in 63% of the diagnosed and 44% of negative cases. Median time from illness onset to ED admission was 5 days for all patients, diagnosed patients, and negative cases, respectively. Fever was observed in 27 (84%) and 57 (68%) diagnosed and negative cases, respectively. Nineteen (59%) diagnosed and 24 (29%) negative cases had lymphopenia on admission in ED. A chest CT scan on admission revealed the presence of pneumonia in the majority of the diagnosed patients (30 out of 32, 94%) and in 56 (67%) negative cases. Bilateral involvement and GGO were present in 91% and 47% of the diagnosed patients.     

Clinical course of patients on maintenance hemodialysis and COVID-19: a retrospective longitudinal study

Coronavirus Disease 2019 (COVID-19) emerges as a global pandemic and there is a lack of evidence about the clinical course and outcome of patients on maintenance hemodialysis (MHD). Here we conducted a retrospective longitudinal study aimed to analyze the clinical features and outcome of MHD patients hospitalized with COVID-19. Of 3126 inpatients with COVID-19 at 3 Branches of Wuhan Tongji Hospital from Jan 18th to Mar 9th, 2020, 19 patients were undergoing maintenance hemodialysis. Among the 19 MHD patients with COVID-19, 6 patients (31.6%) died, and 13 patients (68.4%) were able to be discharged. Baseline characteristics, clinical courses, laboratory findings, and dynamic trajectories of major laboratory markers were compared between survivors and nonsurvivors. According to our findings, MHD patients with COVID-19 who experienced non-surviving outcome had more elevated CRP, IL6 and procalcitonin as well as fibrinogen levels at various points compared to survivors. Thus the dysregulation of immune response as well as coagulation abnormalities might be highly involved in the pathological process of COVID-19, contributing to the poor prognosis in MHD patients.     

Asthma in patients with suspected and diagnosed coronavirus disease 2019

BackgroundPatients with asthma are comparatively susceptible to respiratory viral infections and more likely to develop severe symptoms than people without asthma. During the coronavirus disease 2019 (COVID-19) pandemic, it is necessary to adequately evaluate the characteristics and outcomes of the population with asthma in the population tested for and diagnosed as having COVID-19.ObjectiveTo perform a study to assess the impact of asthma on COVID-19 diagnosis, presenting symptoms, disease severity, and cytokine profiles.MethodsThis was an analysis of a prospectively collected cohort of patients suspected of having COVID-19 who presented for COVID-19 testing at a tertiary medical center in Missouri between March 2020 and September 2020. We classified and analyzed patients according to their pre-existing asthma diagnosis and subsequent COVID-19 testing results.ResultsPatients suspected of having COVID-19 (N = 435) were enrolled in this study. The proportions of patients testing positive for COVID-19 were 69.2% and 81.9% in the groups with asthma and without asthma, respectively. The frequencies of relevant symptoms were similar between the groups with asthma with positive and negative COVID-19 test results. In the population diagnosed as having COVID-19 (n = 343), asthma was not associated with several indicators of COVID-19 severity, including hospitalization, admission to an intensive care unit, mechanical ventilation, death due to COVID-19, and in-hospital mortality after multivariate adjustment. Patients with COVID-19 with asthma exhibited significantly lower levels of plasma interleukin-8 than patients without asthma (adjusted P = .02).ConclusionThe population with asthma is facing a challenge in preliminary COVID-19 evaluation owing to an overlap in the symptoms of COVID-19 and asthma. However, asthma does not increase the risk of COVID-19 severity if infected.