Virtual Reality Technology in Cognitive Rehabilitation Application: Bibliometric Analysis.

BACKGROUND: In recent years, with the development of computer science and medical science, virtual reality (VR) technology has become a promising tool for improving cognitive function. Research on VR-based cognitive training has garnered increasing attention. OBJECTIVE: This study aimed to investigate the application status, research hot spots, and emerging trends of VR in cognitive rehabilitation over the past 20 years. METHODS: Articles on VR-based cognitive rehabilitation from 2001 to 2021 were retrieved from the Web of Science Core Collection. CiteSpace software was used for the visual analysis of authors and countries or regions, and Scimago Graphica software was used for the geographic visualization of published countries or regions. Keywords were clustered using the gCLUTO software. RESULTS: A total of 1259 papers were included. In recent years, research on the application of VR in cognitive rehabilitation has been widely conducted, and the annual publication of relevant literature has shown a positive trend. The main research areas include neuroscience and neurology, psychology, computer science, and rehabilitation. The United States ranked first with 328 papers, and Italy ranked second with 140 papers. Giuseppe Riva, an Italian academic, was the most prolific author with 29 publications. The most frequently cited reference was "Using Reality to Characterize Episodic Memory Profiles in Amnestic Mild Cognitive Impairment and Alzheimer's Disease: Influence of Active and Passive Encoding." The most common keywords used by researchers include "virtual reality," "cognition," "rehabilitation," "performance," and "older adult." The largest source of research funding is from the public sector in the United States. CONCLUSIONS: The bibliometric analysis provided an overview of the application of VR in cognitive rehabilitation. VR-based cognitive rehabilitation can be integrated into multiple disciplines. We conclude that, in the context of the COVID-19 pandemic, the development of VR-based telerehabilitation is crucial, and there are still many problems that need to be addressed, such as the lack of consensus on treatment methods and the existence of safety hazards.

Identification of Monocytes Associated with Severe COVID-19 in the PBMCs of Severely Infected patients Through Single-Cell Transcriptome Sequencing.

Understanding the immunological characteristics of monocytes-including the characteristics associated with fibrosis-in severe coronavirus disease 2019 (COVID-19) is crucial for understanding the pathogenic mechanism of the disease and preventing disease severity. In this study, we performed single-cell transcriptomic sequencing of peripheral blood samples collected from six healthy controls and 14 COVID-19 samples including severe, moderate, and convalescent samples from three severely/critically ill and four moderately ill patients. We found that the monocytes were strongly remodeled in the severely/critically ill patients with COVID-19, with an increased proportion of monocytes and seriously reduced diversity. In addition, we discovered two novel severe-disease-specific monocyte subsets: Mono 0 and Mono 5. These subsets expressed amphiregulin (AREG), epiregulin (EREG), and cytokine interleukin-18 (IL-18) gene, exhibited an enriched erythroblastic leukemia viral oncogene homolog (ErbB) signaling pathway, and appeared to exhibit pro-fibrogenic and pro-inflammation characteristics. We also found metabolic changes in Mono 0 and Mono 5, including increased glycolysis/gluconeogenesis and an increased hypoxia inducible factor-1 (HIF-1) signaling pathway. Notably, one pre-severe sample displayed a monocyte atlas similar to that of the severe/critical samples. In conclusion, our study discovered two novel severe-disease-specific monocyte subsets as potential predictors and therapeutic targets for severe COVID-19. Overall, this study provides potential predictors for severe disease and therapeutic targets for COVID-19 and thus provides a resource for further studies on COVID-19.

Characteristics of COVID-19 Patients With SARS-CoV-2 Positivity in Feces.

Background: SARS-CoV-2 is highly contagious and poses a great threat to epidemic control and prevention. The possibility of fecal-oral transmission has attracted increasing concern. However, viral shedding in feces has not been completely investigated. Methods: This study retrospectively reviewed 97 confirmed coronavirus disease 2019 (COVID-19) patients hospitalized at the First Affiliated Hospital, School of Medicine, Zhejiang University, from January 19 to February 17, 2020. SARS-CoV-2 RNA in samples of sputum, nasopharyngeal or throat swabs, bronchoalveolar lavage and feces was detected by real-time reverse transcription polymerase chain reaction (RT-PCR). Clinical characteristics and parameters were compared between groups to determine whether fecal RNA was positive. Results: Thirty-four (35.1%) of the patients showed detectable SARS-CoV-2 RNA in feces, and 63 (64.9%) had negative detection results. The median time of viral shedding in feces was approximately 25 days, with the maximum time reaching 33 days. Prolonged fecal-shedding patients showed longer hospital stays. Those patients for whom fecal viral positivity persisted longer than 3 weeks also had lower plasma B-cell counts than those patients in the non-prolonged group [70.5 (47.3-121.5) per µL vs. 186.5 (129.3-376.0) per µL, P = 0.023]. Correlation analysis found that the duration of fecal shedding was positively related to the duration of respiratory viral shedding (R = 0.70, P < 0.001) and negatively related to peripheral B-cell counts (R = -0.44, P < 0.05). Conclusions: COVID-19 patients who shed SARS-CoV-2 RNA in feces presented similar clinical characteristics and outcomes as those who did not shed SARS-CoV-2 RNA in feces. The prolonged presence of SARS-CoV-2 nucleic acids in feces was highly correlated with the prolonged shedding of SARS-CoV-2 RNA in the respiratory tract and with lower plasma B-cell counts.

Cytokine Signature Associated With Disease Severity in COVID-19.

Coronavirus disease 2019 (COVID-19) broke out and then became a global epidemic at the end of 2019. With the increasing number of deaths, early identification of disease severity and interpretation of pathogenesis are very important. Aiming to identify biomarkers for disease severity and progression of COVID-19, 75 COVID-19 patients, 34 healthy controls and 23 patients with pandemic influenza A(H1N1) were recruited in this study. Using liquid chip technology, 48 cytokines and chemokines were examined, among which 33 were significantly elevated in COVID-19 patients compared with healthy controls. HGF and IL-1ß were strongly associated with APACHE II score in the first week after disease onset. IP-10, HGF and IL-10 were correlated positively with virus titers. Cytokines were significantly correlated with creatinine, troponin I, international normalized ratio and procalcitonin within two weeks after disease onset. Univariate analyses were carried out, and 6 cytokines including G-CSF, HGF, IL-10, IL-18, M-CSF and SCGF-ß were found to be associated with the severity of COVID-19. 11 kinds of cytokines could predict the severity of COVID-19, among which IP-10 and M-CSF were excellent predictors for disease severity. In conclusion, the levels of cytokines in COVID-19 were significantly correlated with the severity of the disease in the early stage, and serum cytokines could be used as warning indicators of the severity and progression of COVID-19. Early stratification of disease and intervention to reduce hypercytokinaemia may improve the prognosis of COVID-19 patients.

One-year follow-up of chest CT findings in patients after SARS-CoV-2 infection.

BACKGROUND: Knowledge about the 1-year outcome of COVID-19 is limited. The aim of this study was to follow-up and evaluate lung abnormalities on serial computed tomography (CT) scans in patients with COVID-19 after hospital discharge. METHODS: A prospective cohort study of patients with COVID-19 from the First Affiliated Hospital, Zhejiang University School of Medicine was conducted, with assessments of chest CT during hospitalization and at 2 weeks, 1 month, 3 months, 6 months, and 1 year after hospital discharge. Risk factors of residual CT opacities and the influence of residual CT abnormalities on pulmonary functions at 1 year were also evaluated. RESULTS: A total of 41 patients were followed in this study. Gradual recovery after hospital discharge was confirmed by the serial CT scores. Around 47% of the patients showed residual aberration on pulmonary CT with a median CT score of 0 (interquartile range (IQR) of 0-2) at 1 year after discharge, with ground-glass opacity (GGO) with reticular pattern as the major radiologic pattern. Patients with residual radiological abnormalities were older (p = 0.01), with higher rate in current smokers (p = 0.04), higher rate in hypertensives (p = 0.05), lower SaO2 (p = 0.004), and higher prevalence of secondary bacterial infections during acute phase (p = 0.02). Multiple logistic regression analyses indicated that age was a risk factor associated with residual radiological abnormalities (OR 1.08, 95% CI 1.01-1.15, p = 0.02). Pulmonary functions of total lung capacity (p = 0.008) and residual volume (p < 0.001) were reduced in patients with residual CT abnormalities and were negatively correlated with CT scores. CONCLUSION: During 1-year follow-up after discharge, COVID-19 survivors showed continuous improvement on chest CT. However, residual lesions could still be observed and correlated with lung volume parameters. The risk of developing residual CT opacities increases with age.

Gut mycobiota alterations in patients with COVID-19 and H1N1 infections and their associations with clinical features.

The relationship between gut microbes and COVID-19 or H1N1 infections is not fully understood. Here, we compared the gut mycobiota of 67 COVID-19 patients, 35 H1N1-infected patients and 48 healthy controls (HCs) using internal transcribed spacer (ITS) 3-ITS4 sequencing and analysed their associations with clinical features and the bacterial microbiota. Compared to HCs, the fungal burden was higher. Fungal mycobiota dysbiosis in both COVID-19 and H1N1-infected patients was mainly characterized by the depletion of fungi such as Aspergillus and Penicillium, but several fungi, including Candida glabrata, were enriched in H1N1-infected patients. The gut mycobiota profiles in COVID-19 patients with mild and severe symptoms were similar. Hospitalization had no apparent additional effects. In COVID-19 patients, Mucoromycota was positively correlated with Fusicatenibacter, Aspergillus niger was positively correlated with diarrhoea, and Penicillium citrinum was negatively correlated with C-reactive protein (CRP). In H1N1-infected patients, Aspergillus penicilloides was positively correlated with Lachnospiraceae members, Aspergillus was positively correlated with CRP, and Mucoromycota was negatively correlated with procalcitonin. Therefore, gut mycobiota dysbiosis occurs in both COVID-19 patients and H1N1-infected patients and does not improve until the patients are discharged and no longer require medical attention.

The serum metabolome of COVID-19 patients is distinctive and predictive.

BACKGROUND: Metabolism is critical for sustaining life, immunity and infection, but its role in COVID-19 is not fully understood. METHODS: Seventy-nine COVID-19 patients, 78 healthy controls (HCs) and 30 COVID-19-like patients were recruited in a prospective cohort study. Samples were collected from COVID-19 patients with mild or severe symptoms on admission, patients who progressed from mild to severe symptoms, and patients who were followed from hospital admission to discharge. The metabolome was assayed using gas chromatography-mass spectrometry. RESULTS: Serum butyric acid, 2-hydroxybutyric acid, l-glutamic acid, l-phenylalanine, l-serine, l-lactic acid, and cholesterol were enriched in COVID-19 and COVID-19-like patients versus HCs. Notably, d-fructose and succinic acid were enriched, and citric acid and 2-palmitoyl-glycerol were depleted in COVID-19 patients compared to COVID-19-like patients and HCs, and these four metabolites were not differentially distributed in non-COVID-19 groups. COVID-19 patients had enriched 4-deoxythreonic acid and depleted 1,5-anhydroglucitol compared to HCs and enriched oxalic acid and depleted phosphoric acid compared to COVID-19-like patients. A combination of d-fructose, citric acid and 2-palmitoyl-glycerol distinguished COVID-19 patients from HCs and COVID-19-like patients, with an area under the curve (AUC) > 0.92 after validation. The combination of 2-hydroxy-3-methylbutyric acid, 3-hydroxybutyric acid, cholesterol, succinic acid, L-ornithine, oleic acid and palmitelaidic acid predicted patients who progressed from mild to severe COVID-19, with an AUC of 0.969. After discharge, nearly one-third of metabolites were recovered in COVID-19 patients. CONCLUSIONS: The serum metabolome of COVID-19 patients is distinctive and has important value in investigating pathogenesis, determining a diagnosis, predicting severe cases, and improving treatment.

Alterations of the Gut Microbiota in Patients With Coronavirus Disease 2019 or H1N1 Influenza.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is an emerging serious global health problem. Gastrointestinal symptoms are common in COVID-19 patients, and severe acute respiratory syndrome coronavirus 2 RNA has been detected in stool specimens. However, the relationship between the gut microbiome and disease remains to be established. METHODS: We conducted a cross-sectional study of 30 patients with COVID-19, 24 patients with influenza A(H1N1), and 30 matched healthy controls (HCs) to identify differences in the gut microbiota by 16S ribosomal RNA gene V3-V4 region sequencing. RESULTS: Compared with HCs, COVID-19 patients had significantly reduced bacterial diversity; a significantly higher relative abundance of opportunistic pathogens, such as Streptococcus, Rothia, Veillonella, and Actinomyces; and a lower relative abundance of beneficial symbionts. Five biomarkers showed high accuracy for distinguishing COVID-19 patients from HCs with an area under the curve (AUC) up to 0.89. Patients with H1N1 displayed lower diversity and different overall microbial composition compared with COVID-19 patients. Seven biomarkers were selected to distinguish the 2 cohorts (AUC = 0.94). CONCLUSIONS: The gut microbial signature of patients with COVID-19 was different from that of H1N1 patients and HCs. Our study suggests the potential value of the gut microbiota as a diagnostic biomarker and therapeutic target for COVID-19, but further validation is needed.

The faecal metabolome in COVID-19 patients is altered and associated with clinical features and gut microbes.

Although SARS-CoV-2 can invade the intestine, though its effect on digestion and absorption is not fully understood. In the present study, 56 COVID-19 patients and 47 age- and sex-matched healthy subjects were divided into a discovery cohort and a validation cohort. Blood, faeces and clinical information were collected from the patients in the hospital and at discharge. The faecal metabolome was analysed using gas chromatography-mass spectrometry, and Spearman's correlation analyses of clinical features, the serum metabolome, and the faecal micro- and mycobiota were conducted. The results showed that, the faeces of COVID-19 patients were enriched with important nutrients that should be metabolized or absorbed, such as sucrose and 2-palmitoyl-glycerol; diet-related components that cannot be synthesized by humans, such as 1,5-anhydroglucitol and D-pinitol; and harmful metabolites, such as oxalate, were also detected. In contrast, purine metabolites such as deoxyinosine and hypoxanthine, low-water-soluble long-chain fatty alcohols/acids such as behenic acid, compounds rarely occurring in nature such as D-allose and D-arabinose, and microbe-related compounds such as 2,4-di-tert-butylphenol were depleted in the faeces of COVID-19 patients. Moreover, these metabolites significantly correlated with altered serum metabolites such as oxalate and gut microbesincluding Ruminococcaceae, Actinomyces, Sphingomonas and Aspergillus. Although levels of several faecal metabolites, such as sucrose, 1,5-anhydroglucitol and D-pinitol, of discharged patients were not different from those of healthy controls (HCs), those of oxalate and 2-palmitoyl-glycerol did differ. Therefore, alterations in the faecal metabolome of COVID-19 patients may reflect malnutrition and intestinal inflammation and warrant greater attention. The results of present study provide new insights into the pathogenesis and treatment of COVID-19.

The Artificial-Liver Blood-Purification System Can Effectively Improve Hypercytokinemia for COVID-19.

Since the December 2019 outbreak of coronavirus disease 2019 (COVID-19) in Wuhan, the infection has spread locally and globally resulting in a pandemic. As the numbers of confirmed diagnoses and deaths continue to rise, COVID-19 has become the focus of international public health. COVID-19 is highly contagious, and there is no effective treatment yet. New treatment strategies are urgently needed to improve the treatment success rate of severe and critically ill patients. Increasing evidence has shown that a cytokine storm plays an important role in the progression of COVID-19. The artificial-liver blood-purification system (ALS) is expected to improve the outcome of the cytokine storm. In the present study, the levels of cytokines were detected in 12 COVID-19 patients pre- and post-ALS with promising results. The present study shows promising evidence that ALS can block the cytokine storm, rapidly remove the inflammatory mediators, and hopefully, suppress the progression of the disease, thereby providing a new strategy for the clinical treatment of COVID-19.

Risk factors and clinical features of deterioration in COVID-19 patients in Zhejiang, China: a single-centre, retrospective study.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection swept through Wuhan and spread across China and overseas beginning in December 2019. To identify predictors associated with disease progression, we evaluated clinical risk factors for exacerbation of SARS-CoV-2 infection. METHODS: A retrospective analysis was used for PCR-confirmed COVID-19 (coronavirus disease 2019)-diagnosed hospitalized cases between January 19, 2020, and February 19, 2020, in Zhejiang, China. We systematically analysed the clinical characteristics of the patients and predictors of clinical deterioration. RESULTS: One hundred patients with COVID-19, with a median age of 54 years, were included. Among them, 49 patients (49%) had severe and critical disease. Age ([36-58] vs [51-70], P = 0.0001); sex (49% vs 77.6%, P = 0.0031); Body Mass Index (BMI) ([21.53-25.51] vs [23.28-27.01], P = 0.0339); hypertension (17.6% vs 57.1%, P < 0.0001); IL-6 ([6.42-30.46] vs [16.2-81.71], P = 0.0001); IL-10 ([2.16-5.82] vs [4.35-9.63], P < 0.0001); T lymphocyte count ([305-1178] vs [167.5-440], P = 0.0001); B lymphocyte count ([91-213] vs [54.5-163.5], P = 0.0001); white blood cell count ([3.9-7.6] vs [5.5-13.6], P = 0.0002); D2 dimer ([172-836] vs [408-953], P = 0.005), PCT ([0.03-0.07] vs [0.04-0.15], P = 0.0039); CRP ([3.8-27.9] vs [17.3-58.9], P < 0.0001); AST ([16, 29] vs [18, 42], P = 0.0484); artificial liver therapy (2% vs 16.3%, P = 0.0148); and glucocorticoid therapy (64.7% vs 98%, P < 0.0001) were associated with the severity of the disease. Age and weight were independent risk factors for disease severity. CONCLUSION: Deterioration among COVID-19-infected patients occurred rapidly after hospital admission. In our cohort, we found that multiple factors were associated with the severity of COVID19. Early detection and monitoring of these indicators may reduce the progression of the disease. Removing these factors may halt the progression of the disease. In addition, Oxygen support, early treatment with low doses of glucocorticoids and artificial liver therapy, when necessary, may help reduce mortality in critically ill patients.

Factors Associated With Prolonged Viral RNA Shedding in Patients with Coronavirus Disease 2019 (COVID-19).

BACKGROUND: An outbreak of coronavirus disease 2019 (COVID-19) is becoming a public health emergency. Data are limited on the duration and host factors related to viral shedding. METHODS: In this retrospective study, risk factors associated with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA shedding were evaluated in a cohort of 113 symptomatic patients from 2 hospitals outside Wuhan. RESULTS: The median (interquartile range) duration of SARS-CoV-2 RNA detection was 17 (13-22) days as measured from illness onset. When comparing patients with early (<15 days) and late (≥15 days after illness onset) viral RNA clearance, prolonged SARS-CoV-2 RNA shedding was associated with male sex (P = .009), old age (P = .033), concomitant hypertension (P = .009), delayed admission to hospital after illness onset (P = .001), severe illness at admission (P = .049), invasive mechanical ventilation (P = .006), and corticosteroid treatment (P = .025). Patients with longer SARS-CoV-2 RNA shedding duration had slower recovery of body temperature (P < .001) and focal absorption on radiograph images (P < .001) than patients with early SARS-CoV-2 RNA clearance. Male sex (OR, 3.24; 95% CI, 1.31-8.02), delayed hospital admission (OR, 1.30; 95% CI, 1.10-1.54), and invasive mechanical ventilation (OR, 9.88; 95% CI, 1.11-88.02) were independent risk factors for prolonged SARS-CoV-2 RNA shedding. CONCLUSIONS: Male sex, delayed admission to hospital after illness onset, and invasive mechanical ventilation were associated with prolonged SARS-CoV-2 RNA shedding. Hospital admission and general treatments should be started as soon as possible in symptomatic COVID-19 patients, especially male patients.

Effect of Corticosteroid Therapy on the Duration of SARS-CoV-2 Clearance in Patients with Mild COVID-19: A Retrospective Cohort Study.

INTRODUCTION: In December, 2019, an outbreak of the coronavirus disease 2019 (COVID-19), which was caused by a novel coronavirus, started in Wuhan, China. So far, there is limited clinical evidence on the effect of corticosteroid therapy for this disease. This study aims to investigate the association between corticosteroid therapy and the duration of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) clearance among patients with mild COVID-19. METHODS: Patients with mild COVID-19 were enrolled from two medical centers in China between January 13, 2020 and February 29, 2020. Baseline characteristics and durations of RNA clearance were compared between the corticosteroid and non-corticosteroid therapy groups. The independent effects of corticosteroid therapy on the duration of RNA clearance were estimated by generalized linear models. RESULTS: Of 82 patients with a mild infection, 40 patients were male (48.8%), with a median age of 49 years (interquartile range, IQR 36-61). Among those patients, 36 patients (43.9%) received corticosteroid therapy. The adjusted multivariate models showed that the effects of corticosteroids were non-significant on the durations of onset to first RNA clearance [ß 2.48, 95% CI (95% confidence interval) - 0.42 to 5.38, P = 0.0926] and to persistent RNA clearance (ß 1.54, 95% CI - 1.41 to 4.48, P = 0.3016), and durations of therapy to first RNA clearance (ß 2.16, 95% CI - 0.56 to 4.89, P = 0.1184) and to persistent RNA clearance (ß 1.22, 95% CI - 1.52 to 3.95, P = 0.3787). CONCLUSIONS: Corticosteroid therapy in patients with mild COVID-19 was not associated with the duration of SARS-CoV-2 clearance, suggesting that the use of corticosteroids may not be beneficial for patients with mild COVID-19 and should be prudently recommended in clinical practice. However, further studies are needed to verify the findings.

A Deep Learning System to Screen Novel Coronavirus Disease 2019 Pneumonia.

The real-time reverse transcription-polymerase chain reaction (RT-PCR) detection of viral RNA from sputum or nasopharyngeal swab had a relatively low positive rate in the early stage of coronavirus disease 2019 (COVID-19). Meanwhile, the manifestations of COVID-19 as seen through computed tomography (CT) imaging show individual characteristics that differ from those of other types of viral pneumonia such as influenza-A viral pneumonia (IAVP). This study aimed to establish an early screening model to distinguish COVID-19 from IAVP and healthy cases through pulmonary CT images using deep learning techniques. A total of 618 CT samples were collected: 219 samples from 110 patients with COVID-19 (mean age 50 years; 63 (57.3%) male patients); 224 samples from 224 patients with IAVP (mean age 61 years; 156 (69.6%) male patients); and 175 samples from 175 healthy cases (mean age 39 years; 97 (55.4%) male patients). All CT samples were contributed from three COVID-19-designated hospitals in Zhejiang Province, China. First, the candidate infection regions were segmented out from the pulmonary CT image set using a 3D deep learning model. These separated images were then categorized into the COVID-19, IAVP, and irrelevant to infection (ITI) groups, together with the corresponding confidence scores, using a location-attention classification model. Finally, the infection type and overall confidence score for each CT case were calculated using the Noisy-OR Bayesian function. The experimental result of the benchmark dataset showed that the overall accuracy rate was 86.7% in terms of all the CT cases taken together. The deep learning models established in this study were effective for the early screening of COVID-19 patients and were demonstrated to be a promising supplementary diagnostic method for frontline clinical doctors.

Impact of the COVID-19 pandemic on the process and outcome of thrombectomy for acute ischemic stroke.

BACKGROUND: The novel coronavirus disease 2019 (COVID-19) pandemic is still spreading across the world. Although the pandemic has an all-round impact on medical work, the degree of its impact on endovascular thrombectomy (EVT) for patients with acute ischemic stroke (AIS) is unclear. METHODS: We continuously included AIS patients with large artery occlusion who underwent EVT in a comprehensive stroke center before and during the Wuhan shutdown. The protected code stroke (PCS) for screening and treating AIS patients was established during the pandemic. The efficacy and safety outcomes including the rate of successful reperfusion (defined as modified Thrombolysis In Cerebral Infarction (mTICI) graded 2b or 3) and time intervals for reperfusion were compared between two groups: pre-pandemic and pandemic. RESULTS: A total of 55 AIS patients who received EVT were included. The baseline characteristics were comparable between the two groups. The time from hospital arrival to puncture (174 vs 125.5 min; p=0.002) and time from hospital arrival to reperfusion (213 vs 172 min; p=0.047) were significantly prolonged in the pandemic group compared with the pre-pandemic group. The rate of successful reperfusion was not significantly different between the two groups (85.7% (n=18) vs 88.2% (n=30); OR 0.971, 95% CI 0.785 to 1.203; p=1.000). CONCLUSION: The results of this study suggest a proper PCS algorithm which combines the COVID-19 screening and protection measures could decrease the impact of the disease on the clinical outcomes of EVT for AIS patients to the lowest extent possible during the pandemic.

Epidemiological, clinical and virological characteristics of 74 cases of coronavirus-infected disease 2019 (COVID-19) with gastrointestinal symptoms.

OBJECTIVE: The SARS-CoV-2-infected disease (COVID-19) outbreak is a major threat to human beings. Previous studies mainly focused on Wuhan and typical symptoms. We analysed 74 confirmed COVID-19 cases with GI symptoms in the Zhejiang province to determine epidemiological, clinical and virological characteristics. DESIGN: COVID-19 hospital patients were admitted in the Zhejiang province from 17 January 2020 to 8 February 2020. Epidemiological, demographic, clinical, laboratory, management and outcome data of patients with GI symptoms were analysed using multivariate analysis for risk of severe/critical type. Bioinformatics were used to analyse features of SARS-CoV-2 from Zhejiang province. RESULTS: Among enrolled 651 patients, 74 (11.4%) presented with at least one GI symptom (nausea, vomiting or diarrhoea), average age of 46.14 years, 4-day incubation period and 10.8% had pre-existing liver disease. Of patients with COVID-19 with GI symptoms, 17 (22.97%) and 23 (31.08%) had severe/critical types and family clustering, respectively, significantly higher than those without GI symptoms, 47 (8.14%) and 118 (20.45%). Of patients with COVID-19 with GI symptoms, 29 (39.19%), 23 (31.08%), 8 (10.81%) and 16 (21.62%) had significantly higher rates of fever >38.5°C, fatigue, shortness of breath and headache, respectively. Low-dose glucocorticoids and antibiotics were administered to 14.86% and 41.89% of patients, respectively. Sputum production and increased lactate dehydrogenase/glucose levels were risk factors for severe/critical type. Bioinformatics showed sequence mutation of SARS-CoV-2 with m6A methylation and changed binding capacity with ACE2. CONCLUSION: We report COVID-19 cases with GI symptoms with novel features outside Wuhan. Attention to patients with COVID-19 with non-classic symptoms should increase to protect health providers.