A new coronavirus associated with human respiratory disease in China.

Emerging infectious diseases, such as severe acute respiratory syndrome (SARS) and Zika virus disease, present a major threat to public health1-3. Despite intense research efforts, how, when and where new diseases appear are still a source of considerable uncertainty. A severe respiratory disease was recently reported in Wuhan, Hubei province, China. As of 25 January 2020, at least 1,975 cases had been reported since the first patient was hospitalized on 12 December 2019. Epidemiological investigations have suggested that the outbreak was associated with a seafood market in Wuhan. Here we study a single patient who was a worker at the market and who was admitted to the Central Hospital of Wuhan on 26 December 2019 while experiencing a severe respiratory syndrome that included fever, dizziness and a cough. Metagenomic RNA sequencing4 of a sample of bronchoalveolar lavage fluid from the patient identified a new RNA virus strain from the family Coronaviridae, which is designated here 'WH-Human 1' coronavirus (and has also been referred to as '2019-nCoV'). Phylogenetic analysis of the complete viral genome (29,903 nucleotides) revealed that the virus was most closely related (89.1% nucleotide similarity) to a group of SARS-like coronaviruses (genus Betacoronavirus, subgenus Sarbecovirus) that had previously been found in bats in China5. This outbreak highlights the ongoing ability of viral spill-over from animals to cause severe disease in humans.

DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid radiologists in detecting and quantifying COVID-19-related lung infections. OBJECTIVE: To develop deep learning-based models to classify and quantify COVID-19-related lung infections. METHODS: Initially, Dual Decoder Attention-based Semantic Segmentation Networks (DDA-SSNets) such as Dual Decoder Attention-UNet (DDA-UNet) and Dual Decoder Attention-SegNet (DDA-SegNet) are proposed to facilitate the dual segmentation tasks such as lung lobes and infection segmentation in chest X-ray (CXR) images. The lung lobe and infection segmentations are mapped to grade the severity of COVID-19 infection in both the lungs of CXRs. Later, a Genetic algorithm-based Deep Convolutional Neural Network classifier with the optimum number of layers, namely GADCNet, is proposed to classify the extracted regions of interest (ROI) from the CXR lung lobes into COVID-19 and non-COVID-19. RESULTS: The DDA-SegNet shows better segmentation with an average BCSSDC of 99.53% and 99.97% for lung lobes and infection segmentations, respectively, compared with DDA-UNet with an average BCSSDC of 99.14% and 99.92%. The proposed DDA-SegNet with GADCNet classifier offered excellent classification results with an average BCCAC of 99.98%, followed by the GADCNet with DDA-UNet with an average BCCAC of 99.92% after extensive testing and analysis. CONCLUSIONS: The results show that the proposed DDA-SegNet has superior performance in the segmentation of lung lobes and COVID-19-infected regions in CXRs, along with improved severity grading compared to the DDA-UNet and improved accuracy of the GADCNet classifier in classifying the CXRs into COVID-19, and non-COVID-19.

DKCNN: Improving deep kernel convolutional neural network-based COVID-19 identification from CT images of the chest.

BACKGROUND: An efficient deep convolutional neural network (DeepCNN) is proposed in this article for the classification of Covid-19 disease. OBJECTIVE: A novel structure known as the Pointwise-Temporal-pointwise convolution unit is developed incorporated with the varying kernel-based depth wise temporal convolution before and after the pointwise convolution operations. METHODS: The outcome is optimized by the Slap Swarm algorithm (SSA). The proposed Deep CNN is composed of depth wise temporal convolution and end-to-end automatic detection of disease. First, the datasets SARS-COV-2 Ct-Scan Dataset and CT scan COVID Prediction dataset are preprocessed using the min-max approach and the features are extracted for further processing. RESULTS: The experimental analysis is conducted between the proposed and some state-of-art works and stated that the proposed work effectively classifies the disease than the other approaches. CONCLUSION: The proposed structural unit is used to design the deep CNN with the increasing kernel sizes. The classification process is improved by the inclusion of depth wise temporal convolutions along with the kernel variation. The computational complexity is reduced by the introduction of stride convolutions are used in the residual linkage among the adjacent structural units.

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Objective: To construct a deep learning-based target detection method to help radiologists perform rapid diagnosis of lesions in the CT images of patients with novel coronavirus pneumonia (NCP) by restoring detailed information and mining local information. Methods: We present a deep learning approach that integrates detail upsampling and attention guidance. A linear upsampling algorithm based on bicubic interpolation algorithm was adopted to improve the restoration of detailed information within feature maps during the upsampling phase. Additionally, a visual attention mechanism based on vertical and horizontal spatial dimensions embedded in the feature extraction module to enhance the capability of the object detection algorithm to represent key information related to NCP lesions. Results: Experimental results on the NCP dataset showed that the detection method based on the detail upsampling algorithm improved the recall rate by 1.07% compared with the baseline model, with the AP50 reaching 85.14%. After embedding the attention mechanism in the feature extraction module, 86.13% AP50, 73.92% recall, and 90.37% accuracy were achieved, which were better than those of the popular object detection models. Conclusion: The feature information mining of CT images based on deep learning can further improve the lesion detection ability. The proposed approach helps radiologists rapidly identify NCP lesions on CT images and provides an important clinical basis for early intervention and high-intensity monitoring of NCP patients.

More than what meets the eye in COVID-19 critical illness: A case report of bilateral femoral neuropathy due to psoas hematomas.

Bilateral femoral neuropathy is rare, especially that caused by bilateral compressive iliopsoas, psoas, or iliacus muscle hematomas. We present a case of bilateral femoral neuropathy due to spontaneous psoas hematomas developed during COVID-19 critical illness. A 41-year-old patient developed COVID-19 pneumonia, and his condition deteriorated rapidly. A decrease in the hemoglobin level prompted imaging studies during his intensive care unit (ICU) stay. Bilateral psoas hematomas were identified as the source of bleeding. Thereafter, the patient complained of weakness in both upper and lower limbs and numbness in the lower limb. He was considered to have critical illness neuropathy and was referred to rehabilitation. Electrodiagnostic testing suggested bilateral femoral neuropathy because of compression due to hematomas developed during the course of his ICU stay. The consequences of iliopsoas hematomas occurring in the critically ill can be catastrophic, ranging from hemorrhagic shock to severe weakness, highlighting the importance of recognizing this entity.

A Novel Coronavirus from Patients with Pneumonia in China, 2019.

In December 2019, a cluster of patients with pneumonia of unknown cause was linked to a seafood wholesale market in Wuhan, China. A previously unknown betacoronavirus was discovered through the use of unbiased sequencing in samples from patients with pneumonia. Human airway epithelial cells were used to isolate a novel coronavirus, named 2019-nCoV, which formed a clade within the subgenus sarbecovirus, Orthocoronavirinae subfamily. Different from both MERS-CoV and SARS-CoV, 2019-nCoV is the seventh member of the family of coronaviruses that infect humans. Enhanced surveillance and further investigation are ongoing. (Funded by the National Key Research and Development Program of China and the National Major Project for Control and Prevention of Infectious Disease in China.).

SARS-CoV-2 infection of African green monkeys results in mild respiratory disease discernible by PET/CT imaging and shedding of infectious virus from both respiratory and gastrointestinal tracts.

Vaccines are urgently needed to combat the global coronavirus disease 2019 (COVID-19) pandemic, and testing of candidate vaccines in an appropriate non-human primate (NHP) model is a critical step in the process. Infection of African green monkeys (AGM) with a low passage human isolate of SARS-CoV-2 by aerosol or mucosal exposure resulted in mild clinical infection with a transient decrease in lung tidal volume. Imaging with human clinical-grade 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET) co-registered with computed tomography (CT) revealed pulmonary lesions at 4 days post-infection (dpi) that resolved over time. Infectious virus was shed from both respiratory and gastrointestinal (GI) tracts in all animals in a biphasic manner, first between 2-7 dpi followed by a recrudescence at 14-21 dpi. Viral RNA (vRNA) was found throughout both respiratory and gastrointestinal systems at necropsy with higher levels of vRNA found within the GI tract tissues. All animals seroconverted simultaneously for IgM and IgG, which has also been documented in human COVID-19 cases. Young AGM represent an species to study mild/subclinical COVID-19 disease and with possible insights into live virus shedding. Future vaccine evaluation can be performed in AGM with correlates of efficacy being lung lesions by PET/CT, virus shedding, and tissue viral load.

Direct Observation of Repeated Infections With Endemic Coronaviruses.

BACKGROUND: Although the mechanisms of adaptive immunity to pandemic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are still unknown, the immune response to the widespread endemic coronaviruses HKU1, 229E, NL63, and OC43 provide a useful reference for understanding repeat infection risk. METHODS: Here we used data from proactive sampling carried out in New York City from fall 2016 to spring 2018. We combined weekly nasal swab collection with self-reports of respiratory symptoms from 191 participants to investigate the profile of recurring infections with endemic coronaviruses. RESULTS: During the study, 12 individuals tested positive multiple times for the same coronavirus. We found no significant difference between the probability of testing positive at least once and the probability of a recurrence for the betacoronaviruses HKU1 and OC43 at 34 weeks after enrollment/first infection. We also found no significant association between repeat infections and symptom severity, but found strong association between symptom severity and belonging to the same family. CONCLUSIONS: This study provides evidence that reinfections with the same endemic coronavirus are not atypical in a time window shorter than 1 year and that the genetic basis of innate immune response may be a greater determinant of infection severity than immune memory acquired after a previous infection.

Spectrum of Cardiac Manifestations in COVID-19: A Systematic Echocardiographic Study.

BACKGROUND: Information on the cardiac manifestations of coronavirus disease 2019 (COVID-19) is scarce. We performed a systematic and comprehensive echocardiographic evaluation of consecutive patients hospitalized with COVID-19 infection. METHODS: One hundred consecutive patients diagnosed with COVID-19 infection underwent complete echocardiographic evaluation within 24 hours of admission and were compared with reference values. Echocardiographic studies included left ventricular (LV) systolic and diastolic function and valve hemodynamics and right ventricular (RV) assessment, as well as lung ultrasound. A second examination was performed in case of clinical deterioration. RESULTS: Thirty-two patients (32%) had a normal echocardiogram at baseline. The most common cardiac pathology was RV dilatation and dysfunction (observed in 39% of patients), followed by LV diastolic dysfunction (16%) and LV systolic dysfunction (10%). Patients with elevated troponin (20%) or worse clinical condition did not demonstrate any significant difference in LV systolic function compared with patients with normal troponin or better clinical condition, but they had worse RV function. Clinical deterioration occurred in 20% of patients. In these patients, the most common echocardiographic abnormality at follow-up was RV function deterioration (12 patients), followed by LV systolic and diastolic deterioration (in 5 patients). Femoral deep vein thrombosis was diagnosed in 5 of 12 patients with RV failure. CONCLUSIONS: In COVID-19 infection, LV systolic function is preserved in the majority of patients, but LV diastolic function and RV function are impaired. Elevated troponin and poorer clinical grade are associated with worse RV function. In patients presenting with clinical deterioration at follow-up, acute RV dysfunction, with or without deep vein thrombosis, is more common, but acute LV systolic dysfunction was noted in ≈20%.

Cerebrovascular disease in patients with COVID-19: neuroimaging, histological and clinical description.

Since the appearance of the first case of coronavirus disease 2019 (COVID-19) a pandemic has emerged affecting millions of individuals worldwide. Although the main clinical manifestations are respiratory, an increase in neurological conditions, specifically acute cerebrovascular disease, has been detected. We present cerebrovascular disease case incidence in hospitalized patients with SARS-CoV-2 infection. Patients were confirmed by microbiological/serological testing, or on chest CT semiology. Available data on co-morbidity, laboratory parameters, treatment administered, neuroimaging, neuropathological studies and clinical evolution during hospitalization, measured by the modified Rankin scale, were analysed. A bivariate study was also designed to identify differences between ischaemic and haemorrhagic subtypes. A statistical model of binary logistic regression and sensitivity analysis was designed to study the influence of independent variables over prognosis. In our centre, there were 1683 admissions of patients with COVID-19 over 50 days, of which 23 (1.4%) developed cerebrovascular disease. Within this group of patients, cerebral and chest CT scans were performed in all cases, and MRI in six (26.1%). Histological samples were obtained in 6/23 cases (two brain biopsies, and four arterial thrombi). Seventeen patients were classified as cerebral ischaemia (73.9%, with two arterial dissections), five as intracerebral haemorrhage (21.7%), and one leukoencephalopathy of posterior reversible encephalopathy type. Haemorrhagic patients had higher ferritin levels at the time of stroke (1554.3 versus 519.2, P = 0.004). Ischaemic strokes were unexpectedly frequent in the vertebrobasilar territory (6/17, 35.3%). In the haemorrhagic group, a characteristic radiological pattern was identified showing subarachnoid haemorrhage, parieto-occipital leukoencephalopathy, microbleeds and single or multiple focal haematomas. Brain biopsies performed showed signs of thrombotic microangiopathy and endothelial injury, with no evidence of vasculitis or necrotizing encephalitis. The functional prognosis during the hospital period was unfavourable in 73.9% (17/23 modified Rankin scale 4-6), and age was the main predictive variable (odds ratio = 1.5; 95% confidence interval 1.012-2.225; P = 0.043). Our series shows cerebrovascular disease incidence of 1.4% in patients with COVID-19 with high morbidity and mortality. We describe pathological and radiological data consistent with thrombotic microangiopathy caused by endotheliopathy with a haemorrhagic predisposition.

A novel cell-based assay for dynamically detecting neutrophil extracellular traps-induced lung epithelial injuries.

Acute lung injury (ALI) and its more severe form, acute respiratory distress syndrome (ARDS) are common lung disorders characterized by alveolar-capillary barrier disruption and dyspnea, which can cause substantial morbidity and mortality. Currently, a cluster of acute respiratory illnesses, known as novel coronavirus (2019-nCoV)-infected pneumonia (NCIP), which allegedly originally occurred in Wuhan, China, has increased rapidly worldwide. The critically ill patients with ARDS have high mortality in subjects with comorbidities. Previously, the excessive recruitment and activation of neutrophils (polymorphonuclear leukocytes [PMNs]), accompanied by neutrophil extracellular traps (NETs) formation were reported being implicated in the pathogenesis of ALI/ARDS. However, the direct visualization of lung epithelial injuries caused by NETs, and the qualitative and quantitative evaluations of this damage are still lacking. Additionally, those already reported methods are limited for their neglect of the pathological role exerted by NETs and focusing only on the morphological features of NETosis. Therefore, we established a cell-based assay for detecting NETs during lung epithelial cells-neutrophils co-culture using the xCELLigence system, a recognized real-time, dynamic, label-free, sensitive, and high-throughput apparatus. Our results demonstrated that lung epithelial injuries, reflected by declines in cell index (CI) values, could be induced by lipopolysaccharide (LPS)-activated PMNs, or NETs in a time and dose-dependent manner. NETs generation was verified to be the major contributor to the cytotoxicity of activated PMNs; protein components of NETs were the prevailing cytotoxic mediators. Moreover, this cell-based assay identified that PMNs from severe pneumonia patients had a high NETs formative potential. Additionally, acetylsalicylic acid (ASA) and acetaminophen (APAP) were discovered alleviating NETs formation. Thus, this study not only presents a new methodology for detecting the pathophysiologic role of NETs but also lays down a foundation for exploring therapeutic interventions in an effort to cure ALI/ARDS in the clinical setting of severe pneumonia, including the emerging of NCIP.

Comparison of COVID-19 disease between young and elderly patients: Hidden viral shedding of COVID-19.

OBJECTIVES: The symptoms of Coronavirus disease 2019 (COVID-19) vary among patients. The aim of this study was to investigate the clinical manifestation and disease duration in young versus elderly patients. METHODS: We retrospectively analyzed 187 patients (87 elderly and 100 young patients) with confirmed COVID-19. The clinical characteristics and chest computed tomography (CT) extent as defined by a score were compared between the two groups. RESULTS: The numbers of asymptomatic cases and severe cases were significantly higher in the elderly group (elderly group vs. young group; asymptomatic cases, 31 [35.6%] vs. 10 [10%], p < 0.0001; severe cases, 25 [28.7%] vs. 8 [8.0%], p = 0.0002). The proportion of asymptomatic patients and severe patients increased across the 10-year age groups. There was no significant difference in the total CT score and number of abnormal cases. A significant positive correlation between the disease duration and patient age was observed in asymptomatic patients (ρ = 0.4570, 95% CI 0.1198-0.6491, p = 0.0034). CONCLUSIONS: Although the extent of lung involvement did not have a significant difference between the young and elderly patients, elderly patients were more likely to have severe clinical manifestations. Elderly patients were also more likely to be asymptomatic and a source of COVID-19 viral shedding.

Neuroimaging and neurologic findings in COVID-19 and other coronavirus infections: A systematic review in 116 patients.

Various neurologic syndromes have been described in patients with COVID-19 and other coronavirus infections. In this paper, we systematically reviewed the available imaging findings of patients diagnosed with neurological symptoms associated with coronavirus infections. Diverse radiologic results in the context of different neurologic presentations have been demonstrated using CT and MRI. While many patients have normal imaging evaluations, some patients present with intra-axial and extra-axial abnormalities. Stroke (both ischemic and hemorrhagic), encephalomyelitis, meningitis, demyelinating disorders such as acute disseminated encephalomyelitis (ADEM), and encephalopathy have been reported. Familiarity with these radiologic patterns will guide radiologists and referring clinicians to consider coronavirus infections in patients with worsening or progressive neurologic findings, particularly during the current COVID-19 pandemic. As data on this topic is very limited, further research and investigation are required.

Clinical Characteristics of Patients With Coronavirus Disease 2019 in Japan: A Single-Center Case Series.

We report a case series of 6 patients with confirmed coronavirus disease 2019 (COVID-19) in Wakayama prefecture, Japan. All 6 of the patients tested positive via pharyngeal swab polymerase chain reaction (PCR) tests, and 2 of the 6 were still positive at 3 weeks after onset. All of the patients exhibited bilateral ground glass opacities on computed tomography (CT). This article also reports narrative information on the spectrum of symptoms collected directly from the patients. It would be difficult to triage patients with COVID-19 based on the typical symptoms of fever and/or cough, although PCR and CT are definitive in diagnosis.

Epidemiological and Clinical Characteristics of 26 Asymptomatic Severe Acute Respiratory Syndrome Coronavirus 2 Carriers.

BACKGROUND: We retrospectively analyzed 26 persistently asymptomatic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) carriers. METHODS: Epidemiological and clinical characteristics from the 26 asymptomatic patients with positive results for SARS-CoV-2 ribonucleic acid testing were obtained. RESULTS: Twenty-two patients (84.6%) correlated with clustering occurrence. The median period from contact to diagnosis and the last positive nucleic acid test was 19 (8-24 days) and 21.5 days (10-36 days), respectively. The median period from diagnosis to negative nucleic acid test was significantly different between patients with normal or atypical chest computed tomography (CT) findings (n = 16, 61.5%; 7.5 days [2-20 days]) and patients with typical ground-glass or patchy opacities on CT (n = 10, 38.5%; 12.5 days [8-22 days]; P < .01). Seven patients (70.0%) with initial positive nucleic acid test results had a negative result simultaneously with improved CT findings. Obvious improvement in CT findings was observed in 3 patients (30.0%) despite positive nucleic acid test results. CONCLUSIONS: In asymptomatic patients, changes in biochemical and inflammatory variables are small and changes on chest CT can occur. It is worth noting that the long existence of SARS-CoV-2 in some asymptomatic patients and false-negative results need to be considered in SARS-CoV-2 nucleic acid test.

Cerebral Microbleeds and Leukoencephalopathy in Critically Ill Patients With COVID-19.

BACKGROUND AND PURPOSE: We conducted this study to investigate the prevalence and distribution of cerebral microbleeds and leukoencephalopathy in hospitalized patients with coronavirus disease 2019 (COVID-19) and correlate with clinical, laboratory, and functional outcomes. METHODS: We performed a retrospective chart review of 4131 COVID-19 positive adult patients who were admitted to 3 tertiary care hospitals of an academic medical center at the epicenter of the COVID-19 pandemic in New York City from March 1, 2020, to May 10, 2020, to identify patients who had magnetic resonance imaging (MRI) of the brain. We evaluated the MRIs in detail, and identified a subset of patients with leukoencephalopathy and/or cerebral microbleeds. We compared clinical, laboratory, and functional outcomes for these patients to patients who had a brain MRI that did not show these findings. RESULTS: Of 115 patients who had an MRI of the brain performed, 35 (30.4%) patients had leukoencephalopathy and/or cerebral microbleeds. Patients with leukoencephalopathy and/or cerebral microbleeds had neuroimaging performed later during the hospitalization course (27 versus 10.6 days; P<0.001), were clinically sicker at the time of brain MRI (median GCS 6 versus 14; P<0.001), and had higher peak D-dimer levels (8018±6677 versus 3183±3482; P<0.001), lower nadir platelet count (116.9±62.2 versus 158.3±76.2; P=0.03), higher peak international normalized ratio (2.2 versus 1.57; P<0.001) values when compared with patients who had a brain MRI that did not show these findings. They required longer ventilator support (34.6 versus 9.1 days; P<0.001) and were more likely to have moderate and severe acute respiratory distress syndrome score (88.6% versus 23.8%, P<0.001). These patients had longer hospitalizations (42.1 versus 20.9 days; P<0.001), overall worse functional status on discharge (mRS 5 versus 4; P=0.001), and higher mortality (20% versus 9%; P=0.144). CONCLUSIONS: The presence of leukoencephalopathy and/or cerebral microbleeds is associated with a critical illness, increased mortality, and worse functional outcome in patients with COVID-19.

Characteristics and Outcomes in Patients With COVID-19 and Acute Ischemic Stroke: The Global COVID-19 Stroke Registry.

Recent case-series of small size implied a pathophysiological association between coronavirus disease 2019 (COVID-19) and severe large-vessel acute ischemic stroke. Given that severe strokes are typically associated with poor prognosis and can be very efficiently treated with recanalization techniques, confirmation of this putative association is urgently warranted in a large representative patient cohort to alert stroke clinicians, and inform pre- and in-hospital acute stroke patient pathways. We pooled all consecutive patients hospitalized with laboratory-confirmed COVID-19 and acute ischemic stroke in 28 sites from 16 countries. To assess whether stroke severity and outcomes (assessed at discharge or at the latest assessment for those patients still hospitalized) in patients with acute ischemic stroke are different between patients with COVID-19 and non-COVID-19, we performed 1:1 propensity score matching analyses of our COVID-19 patients with non-COVID-19 patients registered in the Acute Stroke Registry and Analysis of Lausanne Registry between 2003 and 2019. Between January 27, 2020, and May 19, 2020, 174 patients (median age 71.2 years; 37.9% females) with COVID-19 and acute ischemic stroke were hospitalized (median of 12 patients per site). The median National Institutes of Health Stroke Scale was 10 (interquartile range [IQR], 4-18). In the 1:1 matched sample of 336 patients with COVID-19 and non-COVID-19, the median National Institutes of Health Stroke Scale was higher in patients with COVID-19 (10 [IQR, 4-18] versus 6 [IQR, 3-14]), P=0.03; (odds ratio, 1.69 [95% CI, 1.08-2.65] for higher National Institutes of Health Stroke Scale score). There were 48 (27.6%) deaths, of which 22 were attributed to COVID-19 and 26 to stroke. Among 96 survivors with available information about disability status, 49 (51%) had severe disability at discharge. In the propensity score-matched population (n=330), patients with COVID-19 had higher risk for severe disability (median mRS 4 [IQR, 2-6] versus 2 [IQR, 1-4], P<0.001) and death (odds ratio, 4.3 [95% CI, 2.22-8.30]) compared with patients without COVID-19. Our findings suggest that COVID-19 associated ischemic strokes are more severe with worse functional outcome and higher mortality than non-COVID-19 ischemic strokes.

Relative Bradycardia in Patients with Mild-to-Moderate Coronavirus Disease, Japan.

Coronavirus disease is reported to affect the cardiovascular system. We showed that relative bradycardia was a common characteristic for 54 patients with PCR-confirmed mild-to-moderate coronavirus disease in Japan. This clinical sign could help clinicians to diagnose this disease.

Abdominal Visceral Infarction in 3 Patients with COVID-19.

A high incidence of thrombotic events has been reported in patients with coronavirus disease (COVID-19), which is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. We report 3 clinical cases of patients in Italy with COVID-19 who developed abdominal viscera infarction, demonstrated by computed tomography.

Clinical and epidemiological characteristics of pediatric SARS-CoV-2 infections in China: A multicenter case series.

BACKGROUND: As of April 18, 2020, over 2,000,000 patients had been diagnosed with coronavirus disease-2019 (COVID-19) globally, and more than 140,000 deaths had been reported. The clinical and epidemiological characteristics of adult patients have been documented recently. However, information on pediatric patients is limited. We describe the clinical and epidemiological characteristics of pediatric patients to provide valuable insight into the early diagnosis and assessment of COVID-19 in children. METHODS AND FINDINGS: This retrospective, observational study involves a case series performed at 4 hospitals in West China. Thirty-four pediatric patients with COVID-19 were included from January 27 to February 23, 2020. The final follow-up visit was completed by March 16, 2020. Clinical and epidemiological characteristics were analyzed on the basis of demographic data, medical history, laboratory tests, radiological findings, and treatment information. Data analysis was performed for 34 pediatrics patients with COVID-19 aged from 1 to 144 months (median 33.00, interquartile range 10.00-94.25), among whom 14 males (41%) were included. All the patients in the current study presented mild (18%) or moderate (82%) forms of COVID-19. A total of 48% of patients were noted to be without a history of exposure to an identified source. Mixed infections of other respiratory pathogens were reported in 16 patients (47%). Comorbidities were reported in 6 patients (18%). The most common initial symptoms were fever (76%) and cough (62%). Expectoration (21%), vomiting (12%), and diarrhea (12%) were also reported in a considerable portion of cases. A substantial increase was detected in serum amyloid A for 17 patients (among 20 patients with available data; 85%) and in high-sensitivity C-reactive protein for 17 patients (among 29 patients with available data; 59%), whereas a decrease in prealbumin was noticed in 25 patients (among 32 patients with available data; 78%). In addition, significant increases in the levels of lactate dehydrogenase and α-hydroxybutyrate dehydrogenase were detected in 28 patients (among 34 patients with available data; 82%) and 25 patients (among 34 patients with available data; 74%), respectively. Patchy lesions in lobules were detected by chest computed tomographic scans in 28 patients (82%). Ground-glass opacities, which were a typical feature in adults, were rare in pediatric patients (3%). Rapid radiologic progression and a late-onset pattern of lesions in the lobules were also noticed. Lesions in lobules still existed in 24 (among 32 patients with lesions; 75%) patients that were discharged, although the main symptoms disappeared a few days after treatment. All patients were discharged, and the median duration of hospitalization was 10.00 (8.00-14.25) days. The current study was limited by the small sample size and a lack of dynamic detection of inflammatory markers. CONCLUSIONS: Our data systemically presented the clinical and epidemiological features, as well as the outcomes, of pediatric patients with COVID-19. Stratified analysis was performed between mild and moderate cases. The findings offer new insight into early identification and intervention in pediatric patients with COVID-19.