Smart-Plexer: a breakthrough workflow for hybrid development of multiplex PCR assays (preprint)

Developing multiplex PCR assays requires an extensive amount of experimental testing, the number of which exponentially increases by the number of multiplexed targets. Dedicated efforts must be devoted to the design of optimal multiplex assays for specific and sensitive identification of multiple analytes in a single well reaction. Inspired by data-driven approaches, we reinvent the way of designing and developing multiplex assays by proposing a hybrid, easy-to-use workflow, named Smart-Plexer, which couples empirical testing of singleplex assays and computer simulation of multiplexing. The Smart-Plexer leverages kinetic inter-target distances among amplification curves to generate optimal multiplex PCR primer sets for accurate multi-pathogen identification. The optimal single-channel assays, together with a novel data-driven approach, Amplification Curve Analysis (ACA), were demonstrated to be capable of classifying the presence of desired targets in a single test for seven common respiratory infection pathogens.

Clinical Features of Patients Without Fever Infected by SARS-CoV-2: an Observational Study (preprint)

Objective: A large number of patients had infected by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). We aimed to clarify the clinical features of the patients without fever infected by SARS-CoV-2.Methods: This is a retrospective and single-center study. We collected and analyzed the data of demographic, clinical presentation, laboratory tests, radiological results, treatment, and complications. The patients with fever and without fever were compared.Results: 113 patients were enrolled in the study, 36 (31.9%) patients without fever on admission. Among the patients without fever, the mean age was 41 years (IQR, 30-53; Range, 8-82years) and 18 (50%) were male. The median from the onset of illness to the first admission was 3.0 days. None of the patients without fever had complications and received high-flow oxygen therapy or invasive ventilation. As of Feb 22, 2020, 8 patients (22.2%) were discharged, and the remaining patients were still hospitalized. Conclusions: Out of 113 patients with SARS-COV-2 infection, patients without fever accounted for 31.9% in total. The clinical prognosis of patients without fever may be better than those of patients with fever on admission.

Developing the nomogram for the prediction of in-hospital incidence of acute respiratory distress syndrome in patients with COVID-19 (preprint)

Background: Acute respiratory distress syndrome (ARDS) was the most common complication of coronavirus disease-2019(COVID-19), leading to poor clinical outcomes. However, the model to predict the in-hospital incidence of ARDS in patients with COVID-19 is limited. Therefore, we aimed to develop a predictive nomogram for the in-hospital incidence of ARDS in COVID-19 patients.Methods: Patients with COVID-19 admitted to Changsha Public Health Centre between Jan 30, 2020, and Feb 22, 2020, were enrolled. Clinical characteristics and laboratory variables were analyzed in patients with ARDS. Risk factors for ARDS were selected by LASSO binary logistic regression. Nomogram was established based on risk factors and validated by the dataset.Results: A total of 113 patients, involving 99 in the non-ARDS group and 14 in the ARDS group were included in the study. 8 variables including hypertension, chronic obstructive pulmonary disease (COPD), cough, lactate dehydrogenase (LDH), creatine kinase (CK), white blood count (WBC), body temperature, and heart rate were identified to be included in the model. The specificity, sensitivity, and accuracy of the full model were 100%, 85.7%, and 87.5% respectively. The calibration curve also showed good agreement between the predicted and observed values in the model.Conclusions: The nomogram can predict the in-hospital incidence of ARDS in COVID-19 patients. It helps physicians to make an individualized treatment plan for each patient.

The relationship of COVID-19 severity with cardiovascular disease and its traditional risk factors: A systematic review and meta-analysis (preprint)

Background: Whether cardiovascular disease (CVD) and its traditional risk factors predict severe coronavirus disease 2019 (COVID-19) is uncertain, in part, because of potential confounding by age and sex. Methods: We performed a systematic review of studies that explored pre-existing CVD and its traditional risk factors as risk factors of severe COVID-19 (defined as death, acute respiratory distress syndrome, mechanical ventilation, or intensive care unit admission). We searched PubMed and Embase for papers in English with original data ([≥]10 cases of severe COVID-19). Using random-effects models, we pooled relative risk (RR) estimates and conducted meta-regression analyses. Results: Of the 661 publications identified in our search, 25 papers met our inclusion criteria, with 76,638 COVID-19 patients including 11,766 severe cases. Older age was consistently associated with severe COVID-19 in all eight eligible studies, with RR >~5 in >60-65 vs. <50 years. Three studies showed no change in the RR of age after adjusting for covariate(s). In univariate analyses, factors robustly associated with severe COVID-19 were male sex (10 studies; pooled RR=1.73, [95%CI 1.50-2.01]), hypertension (8 studies; 2.87 [2.09-3.93]), diabetes (9 studies; 3.20 [2.26-4.53]), and CVD (10 studies; 4.97 [3.76-6.58]). RR for male sex was likely to be independent of age. For the other three factors, meta-regression analyses suggested confounding by age. Only four studies reported multivariable analysis, but most of them showed adjusted RR ~2 for hypertension, diabetes, and CVD. No study explored renin-angiotensin system inhibitors as a risk factor for severe COVID-19. Conclusions: Despite the potential for confounding, these results suggest that hypertension, diabetes, and CVD are independently associated with severe COVID-19 and, together with age and male sex, can be used to inform objective decisions on COVID-19 testing, clinical management, and workforce planning.

Exploration and analysis of the management mode of a cabin hospital during the outbreak of COVID-19 / 中华医院管理杂志

Since the outbreak of COVID-19 in Wuhan, cabin hospitals have played an important role in preventing the spread of the epidemic and admitting all the patients and suspected ones. As one of the first three cabin hospitals in Wuhan, Jianghan cabin hospital under care of Wuhan Union Hospital has efficiently fulfilled its purpose of admitting patients of mild symptoms. Measures taken by the cabin hospital include clearing its positioning, optimizing its layout, establishing organization structure, setting up the rules and regulations, and strengthening the prevention and control of hospital infection. This article briefly summed up the operation and management practices of the cabin hospital, and analyzed its management difficulties, hence putting forwards suggestions on medical emergency management system of China, for references of hospitals and authorities in charge.

Difficulties and strategies of public hospitals in their participation in the prevention and control of novel coronavirus pneumonia / 中华医院管理杂志

Outbreak of the novel coronavirus pneumonia (NC) across the country has seriously threatened people's lives and health, endangering smooth operation of the national economy and social stability. An all-out campaign to save the NCP patients and reduce their mortality is not only one of the key tasks to fight against the epidemic, but also a major responsibility and mission of public hospitals. In view of the field practice of Wuhan Union Hospital in the epicenter, the authorsDescribed the challenges faced by such hospitals in the prevention and control, summarized its experiences and proposed improvement measures, for reference of other public hospitals and relevant authorities.