Rationale: The coronavirus disease (COVID-19) pandemic is now a global health concern. Objectives: We compared the clinical characteristics, laboratory examinations, computed tomography images, and treatments of patients with COVID-19 from three different cities in China. Methods: A total of 476 patients were recruited from January 1, 2020, to February 15, 2020, at three hospitals in Wuhan, Shanghai, and Anhui. The patients were divided into four groups according to age and into three groups (moderate, severe, and critical) according to the fifth edition of the Guidelines on the Diagnosis and Treatment of COVID-19 issued by the National Health Commission of China. Measurements and Main Results: The incidence of comorbidities was higher in the severe (46.3%) and critical (67.1%) groups than in the moderate group (37.8%). More patients were taking angiotensinconverting enzyme inhibitors/angiotensin II receptor blockers in the moderate group than in the severe and critical groups. More patients had multiple lung lobe involvement and pleural effusion in the critical group than in the moderate group. More patients received antiviral agents within the first 4 days in the moderate group than in the severe group, and more patients received antibiotics and corticosteroids in the critical and severe groups. Patients .75 years old had a significantly lower survival rate than younger patients. Conclusions: Multiple organ dysfunction and impaired immune function were the typical characteristics of patients with severe or critical illness. There was a significant difference in the use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers among patients with different severities of disease. Involvement of multiple lung lobes and pleural effusion were associated with the severity of COVID-19. Advanced age (>75 yr) was a risk factor for mortality.

Background: Chest computed tomography (CT) has been found to have high sensitivity in diagnosing novel coronavirus pneumonia (NCP) at the early stage, giving it an advantage over nucleic acid detection during the current pandemic. In this study, we aimed to develop and validate an integrated deep learning framework on chest CT images for the automatic detection of NCP, focusing particularly on differentiating NCP from influenza pneumonia (IP). Methods: A total of 148 confirmed NCP patients [80 male; median age, 51.5 years; interquartile range (IQR), 42.5-63.0 years] treated in 4 NCP designated hospitals between January 11, 2020 and February 23, 2020 were retrospectively enrolled as a training cohort, along with 194 confirmed IP patients (112 males; median age, 65.0 years; IQR, 55.0-78.0 years) treated in 5 hospitals from May 2015 to February 2020. An external validation set comprising 57 NCP patients and 50 IP patients from 8 hospitals was also enrolled.Two deep learning schemes (the Trinary scheme and the Plain scheme) were developed and compared using receiver operating characteristic (ROC) curves.Results: Of the NCP lesions, 96.6% were >1 cm and 76.8% were of a density <−500 Hu, indicating them to have less consolidation than IP lesions, which had nodules ranging from 5-10 mm. The Trinary scheme accurately distinguished NCP from IP lesions, with an area under the curve (AUC) of 0.93. For patient-level classification in the external validation set, the Trinary scheme outperformed the Plain scheme (AUC: 0.87 vs. 0.71) and achieved human specialist-level performance.Conclusions: Our study has potentially provided an accurate tool on chest CT for early diagnosis of NCP with high transferability and showed high efficiency in differentiating between NCP and IP; these findings could help to reduce misdiagnosis and contain the pandemic transmission.

Corona Virus Disease 2019 (COVID-19) has presented an unprecedented challenge to the health-care system across the world. The current study aims to identify the determinants of illness severity of COVID-19 based on ordinal responses. A retrospective cohort of COVID-19 patients from four hospitals in three provinces in China was established, and 598 patients were included from 1 January to 8 March 2020, and divided into moderate, severe and critical illness group. Relative variables were retrieved from electronic medical records. The univariate and multivariate ordinal logistic regression models were fitted to identify the independent predictors of illness severity. The cohort included 400 (66.89%) moderate cases, 85 (14.21%) severe and 113 (18.90%) critical cases, of whom 79 died during hospitalisation as of 28 April. Patients in the age group of 70+ years (OR = 3.419, 95% CI: 1.596–7.323), age of 40–69 years (OR = 1.586, 95% CI: 0.824–3.053), hypertension (OR = 3.372, 95% CI: 2.185–5.202), ALT >50 μ/l (OR = 3.304, 95% CI: 2.107–5.180), cTnI >0.04 ng/ml (OR = 7.464, 95% CI: 4.292–12.980), myohaemoglobin>48.8 ng/ml (OR = 2.214, 95% CI: 1.42–3.453) had greater risk of developing worse severity of illness. The interval between illness onset and diagnosis (OR = 1.056, 95% CI: 1.012–1.101) and interval between illness onset and admission (OR = 1.048, 95% CI: 1.009–1.087) were independent significant predictors of illness severity. Patients of critical illness suffered from inferior survival, as compared with patients in the severe group (HR = 14.309, 95% CI: 5.585–36.659) and in the moderate group (HR = 41.021, 95% CI: 17.588–95.678). Our findings highlight that the identified determinants may help to predict the risk of developing more severe illness among COVID-19 patients and contribute to optimising arrangement of health resources.

Background: Coronavirus disease 2019 (COVID-19) emerged in December 2019 and has spread globally. Diabetics are at increased risk of infections caused by a variety of pathogens including viruses. The present research aims to describe clinical characteristics and outcomes of COVID-19 patients with diabetes. Methods: A retrospective multicenter study of COVID-19 patients with diabetes was conducted in four hospitals in Wuhan, Shanghai, and Anhui Province. Reverse transcription polymerase chain reaction or next-generation sequencing was carried out to confirm the existence of severe acute respiratory syndrome coronavirus 2 from respiratory specimens. Results: A total of 54 diabetics (10.36%) were recruited from among 521 COVID-19 patients, with a median age of 63 (interquartile range, 52-70) years. Among them, 51 had been previously diagnosed with diabetes and 3 had been newly diagnosed based on glycosylated hemoglobin over 6.5%. For COVID-19, 47 of the 54 patients had an exposure history. Fever (47/54, 87.04%), dry cough (36/54, 66.67%), and expectoration (21/53, 39.62%) were among the top three symptoms. Lung infiltration was bilateral (46/52, 88.46%) and multilobe (47/52, 90.38%), and ground-glass opacity (36/37, 97.30%) was the most common pattern in radiological images. Moreover, COVID-19 patients with diabetes were prone to be classified as severe or critical cases (46.30%, 25/54) and had complications such as acute lung injury, acute Huahua Yi, Fangying Lu, and Xiaoyan Jin contributed equally to this work.

Although many strategies have been developed for non-small cell lung cancer (NSCLC), more secondary and further treatments are needed due to drug resistance or tumor recurrence. Apatinib is a novel oral antiangiogenic agent and in this study, we aim to investigate the clinical value of apatinib in heavily pretreated NSCLC. Here, we reported the characteristics, efficacy and adverse events of three patients treated with apatinib (500 mg/day). We also summarized the currently available evidence and ongoing clinical trials regarding the use of apatinib in NSCLC. Two cases of adenocarcinoma and one case of squamous cell carcinoma were treated with apatinib due to disease progression after previous treatments of chemotherapy and epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI). All patients responded to apatinib rapidly and underwent drug resistance shortly afterwards. The patient with squamous cell carcinoma died of hemoptysis. Other adverse events were acceptable. All previous relevant studies were compared and showed similar results but a longer progression-free survival. Additionally, ongoing clinical trials were systematically searched and listed. In conclusion, apatinib shows some efficacy in heavily treated NSCLC and generally tolerable toxicity in non-squamous NSCLC. More solid evidence will be accessible in near future.