Epidemiological, clinical and virological characteristics of 74 cases of coronavirus-infected disease 2019 (COVID-19) with gastrointestinal symptomsObjective 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 m 6 A 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.
Analysis of Epidemiological and Clinical Features in Older Patients With Coronavirus Disease 2019 (COVID-19) Outside WuhanJiangshan Lian, Xi Jin, Shaorui Hao et al.|Clinical Infectious Diseases|2020 BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) has become a large threat to public health in China, with high contagious capacity and varied mortality. This study aimed to investigate the epidemiological and clinical characteristics of older patients with COVID-19 outside Wuhan. METHODS: A retrospective study was performed, with collecting data from medical records of confirmed COVID-19 patients in Zhejiang province from 17 January to 12 February 2020. Epidemiological, clinical, and treatment data were analyzed between older (≥ 60 years) and younger (< 60 years) patients. RESULTS: A total of 788 patients with confirmed COVID-19 were selected; 136 were older patients with corresponding mean age of 68.28 ± 7.31 years. There was a significantly higher frequency of women in older patient group compared with younger patients (57.35% vs 46.47%, P = .021). The presence of coexisting medical conditions was significantly higher in older patients compared with younger patients (55.15% vs 21.93%, P < .001), including the rate of hypertension, diabetes, heart disease, and chronic obstructive pulmonary disease. Significantly higher rates of severe clinical type (older vs younger groups: 16.18% vs 5.98%, P < .001), critical clinical type (8.82% vs 0.77%, P < .001), shortness of breath (12.50% vs 3.07%, P < .001), and temperature of > 39.0°C (13.97% vs 7.21%, P = .010) were observed in older patients compared with younger patients. Finally, higher rates of intensive care unit admission (9.56% vs 1.38%, P < .001) and methylprednisolone application (28.68% vs 9.36%, P < .001) were also identified in older patients compared with younger ones. CONCLUSIONS: The specific epidemiological and clinical features of older COVID-19 patients included significantly higher female sex, body temperature, comorbidities, and rate of severe and critical type disease.
Epidemiological, clinical characteristics of cases of SARS-CoV-2 infection with abnormal imaging findingsXiaoli Zhang, Huan Cai, Jianhua Hu et al.|International Journal of Infectious Diseases|2020 PurposeTo investigate the epidemiological and clinical characteristics of COVID-19 patients with abnormal imaging findings.MethodsPatients confirmed with SARS-CoV-2 infection in Zhejiang province from January 17 to February 8 who had undergone CT or X-ray were enrolled. Epidemiological and clinical data were analyzed among those with abnormal or normal imaging findings.ResultsExcluding 72 patients with normal images, 230 of 573 patients showed abnormalities affecting more than two lung lobes. The median radiographic score was 2.0, and there was a negative correlation between that score and the oxygenation index (ρ = −0.657, P < 0.001). Patients with abnormal images were older (46.65 ± 13.82), with a higher rate of coexisting condition (28.8%), a lower rate of exposure history, and longer time between onset and confirmation (5 days) than non-pneumonia patients (all P < 0.05). A higher rate of fever, cough, expectoration and headache, a lower level of lymphocytes, albumin, and serum sodium levels and a higher total bilirubin, creatine kinase, lactate dehydrogenase, and C-reactive protein levels and a lower oxygenation index were observed in pneumonia patients (all P < 0.05). Muscle ache, shortness of breath, nausea and vomiting, lower lymphocytes levels, and higher serum creatinine and radiographic score at admission were predictive factors for the severe/critical subtype.ConclusionPatients with abnormal images have more obvious clinical manifestations and laboratory changes. Combing clinical features and radiographic scores can effectively predict severe/critical types.
Heparin-Poloxamer Thermosensitive Hydrogel Loaded with bFGF and NGF Enhances Peripheral Nerve Regeneration in Diabetic RatsRui Li, Yiyang Li, Yanqing Wu et al.|Biomaterials|2018 The serum metabolome of COVID-19 patients is distinctive and predictiveDing Shi, Yan Ren, Longxian Lv et al.|Metabolism|2021