Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. MethodsIn this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratoryconfirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients).Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03-1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61-12·23; p<0·0001), and d-dimer greater than 1 µg/mL (18·42, 2·64-128·55; p=0·0033) on admission. Median duration of viral shedding was 20·0 days (IQR 17·0-24·0) in survivors, but SARS-CoV-2 was detectable until death in non-survivors. The longest observed duration of viral shedding in survivors was 37 days.Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 µg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future.

BACKGROUNDNo therapeutics have yet been proven effective for the treatment of severe illness caused by SARS-CoV-2. METHODSWe conducted a randomized, controlled, open-label trial involving hospitalized adult patients with confirmed SARS-CoV-2 infection, which causes the respiratory illness Covid-19, and an oxygen saturation (Sao 2 ) of 94% or less while they were breathing ambient air or a ratio of the partial pressure of oxygen (Pao 2 ) to the fraction of inspired oxygen (Fio 2 ) of less than 300 mm Hg. Patients were randomly assigned in a 1:1 ratio to receive either lopinavir-ritonavir (400 mg and 100 mg, respectively) twice a day for 14 days, in addition to standard care, or standard care alone. The primary end point was the time to clinical improvement, defined as the time from randomization to either an improvement of two points on a seven-category ordinal scale or discharge from the hospital, whichever came first. RESULTSA total of 199 patients with laboratory-confirmed SARS-CoV-2 infection underwent randomization; 99 were assigned to the lopinavir-ritonavir group, and 100 to the standard-care group. Treatment with lopinavir-ritonavir was not associated with a difference from standard care in the time to clinical improvement (hazard ratio for clinical improvement, 1.24; 95% confidence interval [CI], 0.90 to 1.72). Mortality at 28 days was similar in the lopinavir-ritonavir group and the standard-care group (19.2% vs. 25.0%; difference, −5.8 percentage points; 95% CI, −17.3 to 5.7). The percentages of patients with detectable viral RNA at various time points were similar. In a modified intention-to-treat analysis, lopinavir-ritonavir led to a median time to clinical improvement that was shorter by 1 day than that observed with standard care (hazard ratio, 1.39; 95% CI, 1.00 to 1.91). Gastrointestinal adverse events were more common in the lopinavir-ritonavir group, but serious adverse events were more common in the standard-care group. Lopinavir-ritonavir treatment was stopped early in 13 patients (13.8%) because of adverse events. CONCLUSIONS

BackgroundUse of existing disease severity scores would greatly contribute to risk stratification and rationally resource allocation in COVID-19 pandemic. However, the performance of these scores in COVID-19 hospitalised patients with pneumonia was still unknown.MethodsIn this single center, retrospective study, all hospitalised patients with COVID-19 pneumonia from Wuhan Jin Yin-tan Hospital who had discharged or died as of February 15, 2020 were enrolled. Performance of PSI, CURB-65, A-DROP, CRB-65, SMART-COP, qSOFA and NEWS2 were validated. Net reclassification improvement (NRI) and integrated discrimination improvement (IDI) were also estimated.ResultsAmong the 654 patients enrolled, 133 patients died and 521 were discharged. Areas of under curves (AUCs) of A-DROP, CURB-65, PSI, SMART-COP, NEWS2, CRB-65 and qSOFA in the prediction of in-hospital death were 0.87, 0.85, 0.85, 0.84, 0.81, 0.80 and 0.73 respectively.ConclusionADROP is a reliable tool for risk stratification of death in COVID-19 hospitalised patients on admission.

The worldwide spread of coronavirus disease (COVID-19) has become a threat to global public health. It is of great importance to rapidly and accurately screen and distinguish patients with COVID-19 from those with community-acquired pneumonia (CAP). In this study, a total of 1,658 patients with COVID-19 and 1,027 CAP patients underwent thin-section CT and were enrolled. All images were preprocessed to obtain the segmentations of infections and lung fields. A set of handcrafted location-specific features was proposed to best capture the COVID-19 distribution pattern, in comparison to the conventional CT severity score (CT-SS) and radiomics features. An infection size-aware random forest method (iSARF) was proposed for discriminating COVID-19 from CAP. Experimental results show that the proposed method yielded its best performance when using the handcrafted features, with a sensitivity of 90.7%, a specificity of 87.2%, and an accuracy of 89.4% over state-of-the-art classifiers. Additional tests on 734 subjects, with thick slice images, demonstrates great generalizability. It is anticipated that our proposed framework could assist clinical decision making.

Objectives To investigate the different CT

Objective To evaluate the nutritional risk and therapy in severe and critical patients with COVID-19. Methods A total of 523 patients enrolled from four hospitals in Wuhan, China. The inclusion time was from January 2, 2020 to February 15. Clinical characteristics and laboratory values were obtained from electronic medical records, nursing records, and related examinations. Results Of these patients, 211 (40.3%) were admitted to the ICU and 115 deaths (22.0%). Patients admitted to the ICU had lower BMI and plasma protein levels. The median Nutrition risk in critically ill (NUTRIC) score of 211 patients in the ICU was 5 (4, 6) and Nutritional Risk Screening (NRS) score was 5 (3, 6). The ratio of parenteral nutrition (PN) therapy in non-survivors was greater than that in survivors, and the time to start nutrition therapy was later than that in survivors. The NUTRIC score can independently predict the risk of death in the hospital (OR = 1.197, 95%CI: 1.091–1.445, p = 0.006) and high NRS score patients have a higher risk of poor outcome in the ICU (OR = 1.880, 95%CI: 1.151–3.070, p = 0.012). After adjusted age and sex, for each standard deviation increase in BMI, the risk of in-hospital death was reduced by 13% (HR = 0.871, 95%CI: 0.795–0.955, p = 0.003), and the risk of ICU transfer was reduced by 7% (HR = 0.932, 95%CI:0.885–0.981, p = 0.007). The in-hospital survival time of patients with albumin level ≤35 g/L was significantly decreased (15.9 d, 95% CI: 13.7–16.3, vs 24.2 d, 95% CI: 22.3–29.7, p < 0.001). Conclusion Severe and critical patients with COVID-19 have a high risk of malnutrition. Low BMI and protein levels were significantly associated with adverse events. Early nutritional risk screening and therapy for patients with COVID-19 are necessary.

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In December 2019, several patients with pneumonia of an unknown cause were detected in Wuhan, China. On 7 January 2020, the causal organism was identified as a new coronavirus, later named as the 2019 novel coronavirus (2019-nCoV). Genome sequencing found the genetic sequence of 2019-nCoV homologous to that of severe acute respiratory syndrome-associated coronavirus. As of 29 January 2020, the virus had been diagnosed in more than 7000 patients in China and 77 patients in other countries. It is reported that both symptomatic and asymptomatic patients with 2019-nCoV can play a role in disease transmission via airborne and contact. This finding has caused a great concern about the prevention of illness spread. The clinical features of the infection are not specific and are often indistinguishable from those of other respiratory infections, making it difficult to diagnose. Given that the virus has a strong ability to spread between individuals, it is of top priority to identify potential or suspected patients as soon as possible-or the virus may cause a serious pandemic. Therefore, a precision medicine approach to managing this disease is urgently needed for detecting and controlling the spread of the virus. In this article, we present such an approach to managing 2019-nCoV-related pneumonia based on the unique traits of the virus recently revealed and on our experience with coronaviruses at West China Hospital in Chengdu, China.