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Background: Coronavirus disease 2019(COVID-19) has spread worldwide. The present study aimed to characterize the clinical features and outcomes of imported COVID-19 patients with high body mass index (BMI) and the independent association of BMI with disease severity.Methods: In this retrospective cohort study, 455 imported COVID-19 patients were admitted and discharged in Zhejiang province by February 28, 2020. Epidemiological, demographic, clinical, laboratory, radiological, treatment, and outcome data were collected, analyzed and compared between patients with BMI ≥ 24and < 24.Results: A total of 268 patients had BMI < 24, and 187 patients had BMI ≥ 24. Those with high BMI were mostly men, had a smoking history, fever, cough, and sputum than those with BMI < 24. A large number of patients with BMI ≥ 24 were diagnosed as severe/critical types. Some biochemical indicators were significantly elevated in patients with BMI ≥ 24. Also, acute liver injury was the most common complication in these patients. The median days from illness onset to severe acute respiratory syndrome coronavirus 2 detection, duration of hospitalization, and days from illness onset to discharge were significantly longer in patients with BMI ≥ 24 than those with BMI < 24. High BMI, exposure to Wuhan, any coexisting medical condition, high temperature, C-reactive protein (CRP), and increased lactate dehydrogenase (LDH) were independent risk factors for severe/critical COVID-19. After adjusting for age, sex and above factors, BMI was still independently associated with progression to severe/critical illness (P = 0.0040). Hemoglobin, alanine aminotransferase (ALT), CRP, and serum creatinine (Scr) were independent risk factors associated with high BMI.Conclusions: Contrasted with the imported COVID-19 patients with BMI < 24, high proportion of COVID-19 patients with BMI ≥ 24 in our study, especially those with elevated CRP and LDH, developed to severe type, with longer hospitalization duration and anti-virus course. Thus, high BMI is a risk factor for the progression and prognosis of imported COVID-19. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID‐19) has become a serious public health problem worldwide. Here, we stratified COVID‐19 patients based on their comorbidities to assess their risk of serious adverse outcomes. We collected 856 hospitalized cases diagnosed with COVID‐19 from 17 January to 7 February 2020, in Zhejiang Province, and analyzed their comorbidities and composite endpoint (including admission to intensive care unit owing to disease progression, shock, invasive ventilation, and death) to determine the relationship between comorbidities and adverse outcomes. The median age of patients was 46 (36‐56) years; 439 (51.3%) were men, 242 (28.3%) had comorbidities, and 152 (17.8%) had two or more comorbidities. The most common comorbidity was hypertension (142 [16.6%]), followed by diabetes (64 [7.5%]). Of the 856 patients, there are 154 (18.0%) severe cases. Thirty‐two (3.7%) reached composite endpoints, of which 22 (9.1%) were from the comorbidity group and 10 (1.6%) from the non‐comorbidity group (P <.001). After adjusting for age and gender status, the risk of reaching the composite endpoint was higher in the group with comorbidity than in that without comorbidity (hazard ratio [HR] 3.04, 95% confidence interval [CI]: 1.40‐6.60). HR values for patients with one, two, and three or more comorbidities were 1.61 (95% CI: 0.44‐5.91), 3.44 (95% CI: 1.31‐9.08), and 6.90 (95% CI: 2.69‐17.69), respectively. COVID‐19 patients with comorbidities had worse clinical outcomes as compared with those without any comorbidity. The higher the number of comorbidities, the greater was the risk of serious adverse outcomes. Highlights: COVID‐19 has be a great threat to world health.We aimed to investigate clinical features of patients with comorbidities and reveal the relationship between comorbidities and serious adverse outcomes of COVID‐19.Patients with comorbidities were more likely to have imaging abnormalities and clinical manifestations, including hemoptysis, diarrhea, and shortness of breath. the risk of reaching adverse outcomes was also higher than that with non‐comorbidity.The higher the number of comorbidities, the greater was the risk of serious adverse outcomes. [ABSTRACT FROM AUTHOR]

Background: The severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and the associated coronavirus disease (COVID‐19) have spread throughout China. Previous studies predominantly focused on its place of origin, Wuhan, causing over estimation of the disease severity due to selection bias. We analyzed 465 confirmed cases in Zhejiang province to determine the epidemiological, clinical, and virological characteristics of COVID‐19. Methods: Epidemiological, demographic, clinical, laboratory, and management data from qRT‐PCR confirmed COVID‐19 patients from January 17, 2020, to January 31, 2020, were collected, followed by multivariate logistic regression analysis for independent predictors of severe/critical‐type COVID‐19 and bioinformatic analysis for features of SARS‐CoV‐2 from Zhejiang province. Results: Among 465 COVID‐19 patients, median age was 45 years, while hypertension, diabetes, and chronic liver disease were the most common comorbidities. History of exposure to the epidemic area was present in 170 (36.56%) and 185 (39.78%) patients were clustered in 77 families. Severe/critical‐type of COVID‐19 developed in 49 (10.54%) patients. Fever and cough were the most common symptoms, while diarrhea/vomiting was reported in 58 (12.47%) patients. Multivariate analysis revealed eight risk factors for severe/critical COVID‐19. Glucocorticoids and antibiotics were administered to 60 (12.90%) and 218(46.88%) patients, respectively. Bioinformatics showed four single amino acid mutations and one amino acid position loss in SARS‐CoV‐2 from Zhejiang province, with more similarity to humans than to viruses. Conclusions: SARS‐CoV‐2 showed virological mutations and more human transmission in Zhejiang province, indicating considerable epidemiological and clinical changes. Caution in glucocorticoid and antibiotics use is advisable. [ABSTRACT FROM AUTHOR]

Background: The outbreak of coronavirus disease 2019 (COVID-19) is now becoming an enormous threat to public health. The clinical spectrum of COVID-19 is extensive, of which critical cases are with rapid disease progression and high mortality. The aim of our study is to summarize the characteristics of different subtypes and explore risk factors of illness severity for early identification and prompt treatment. Methods: In this retrospective study, we collected data of patients confirmed COVID-19 in Zhejiang Province from 17 January to 12 February 2020. According to the definition of clinical classification, we divided confirmed cases into four types, and summarize epidemiological and clinical characteristics, laboratory and radiograph findings, treatments, and outcomes, respectively. Moreover, we used univariate and multivariate ordinal logistic regression models to explore risk factors for the severity of illness in patients with COVID-19. Results: A total of 788 patients were enrolled in our study, of whom 52 cases (6.6%) were mild type, 658 cases (83.5%) were common type, 61 cases (7.2%) were severe type, and 17 cases (2.2%) were critical type. Multivariate ordinal logistic regression demonstrated increasing odds of the severity of illness in patients with COVID-19 associated with male (odds ratio [OR] = 1.7, 95% confidence interval [CI]: 1.2–2.6 P = 0.008), fever (OR = 3.6, 95% CI: 2.1–6.3, P < 0.001), cough (OR = 1.7, 95% CI: 1.0–2.9, P = 0.041), hemoptysis (OR = 3.4, 95% CI: 1.1–10.3, P = 0.032), gastrointestinal symptoms (OR = 1.9, 95% CI: 1.0–3.5, P = 0.047), hypertension (OR = 2.6, 95% CI: 1.2–5.6, P = 0.013). With the increase of age-grading, risk for the severity of illness was gradually higher (≤ 18 years [OR = 1.0], 19–40 years [OR = 12.7, 95% CI: 4.5–36.0, P < 0.001], 41–65 years [OR = 14.8, 95% CI: 5.2–42.1, P < 0.001], ≥ 66 years [OR = 56.5, 95% CI: 17.1–186.5, P < 0.001]). Conclusions: Clinicians should pay close attention to these features in patients with COVID-19 including older age, male, fever, cough, hemoptysis, gastrointestinal symptoms and hypertension to identify the severity of illness as early as possible. [ABSTRACT FROM AUTHOR]

• COVID-19 has a great threat to world health. • We investigated clinical features of patients with abnormal imaging findings. • Those with abnormal images have more obvious clinical and laboratory features. • Combing clinical data with imaging scores can predict severe/critical type. To investigate the epidemiological and clinical characteristics of COVID-19 patients with abnormal imaging findings. Patients 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. Excluding 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. Patients with abnormal images have more obvious clinical manifestations and laboratory changes. Combing clinical features and radiographic scores can effectively predict severe/critical types. [ABSTRACT FROM AUTHOR]