Frontispiece: Catalytic Asymmetric Synthesis of the anti‐COVID‐19 Drug Remdesivir

Asymmetric Synthesis The first catalytic asymmetric synthesis of remdesivir by the coupling of the P‐racemic phosphoryl chloride with protected nucleoside GS441524 is described by W. Zhang et al. in their Communication on page 20814.

Frontispiz: Catalytic Asymmetric Synthesis of the anti‐COVID‐19 Drug Remdesivir

Asymmetrische Synthese Die erste katalytische asymmetrische Synthese von Remdesivir durch die Kupplung von P‐racemischem Phosphorylchlorid mit dem geschützten Nukleosid GS441524 wird von W. Zhang et al. in der Zuschrift auf S. 21000 vorgestellt.

Epidemiological Features of 105 Patients Infected with the COVID-19.

OBJECTIVE: To investigate and evaluate the clinical features of patients infected with the 2019 novel coronavirus (COVID-19) outside of Wuhan. METHODS: 105 patients admitted to our hospital with clinical- and laboratory-confirmed COVID-19 infection were studied. Data were collected from January 17, 2020 to March 5, 2020. RESULTS: 105 patients (57 male and 48 female) were confirmed to have COVID-19 infection. Among the 105 patients, 55 (52%) had made short trips to Wuhan during the two weeks before the onset of illness, and these were the first-generation confirmed cases. An exact date of close contact with someone in Wenzhou with confirmed or suspected COVID-19 infection from Wuhan (the second-generation confirmed cases) could be provided by 38 (36%) patients. Of the remaining patients, six (6%; the third-generation confirmed cases) were familial clusters of the second-generation confirmed cases, three (3%) had no definite epidemiological features, and 16 (15%) were from the same location as for the case report. CONCLUSION: Due to the infectiousness of COVID-19, patients with infections should be diagnosed and treated as early as possible after developing fever symptoms or showing other clinical characteristics or imaging features. With respect to high-risk cases, we must focus on any complications that arise and take effective measures to treat them immediately. This will significantly improve the prognosis of patients with severe infections.

Towards an Artificial Intelligence Framework for Data-Driven Prediction of Coronavirus Clinical Severity

The virus SARS-CoV2, which causes coronavirus disease (COVID-19) has become a pandemic and has spread to every inhabited continent. Given the increasing caseload, there is an urgent need to augment clinical skills in order to identify from among the many mild cases the few that will progress to critical illness. We present a first step towards building an artificial intelligence (AI) framework, with predictive analytics (PA) capabilities applied to real patient data, to provide rapid clinical decision-making support. COVID-19 has presented a pressing need as a) clinicians are still developing clinical acumen to this novel disease and b) resource limitations in a surging pandemic require difficult resource allocation decisions. The objectives of this research are: (1) to algorithmically identify the combinations of clinical characteristics of COVID-19 that predict outcomes, and (2) to develop a tool with AI capabilities that will predict patients at risk for more severe illness on initial presentation. The predictive models learn from historical data to help predict who will develop acute respiratory distress syndrome (ARDS), a severe outcome in COVID-19. Our results, based on data from two hospitals in Wenzhou, Zhejiang, China, identified features on initial presentation with COVID-19 that were most predictive of later development of ARDS. A mildly elevated alanine aminotransferase (ALT) (a liver enzyme), the presence of myalgias (body aches), and an elevated hemoglobin (red blood cells), in this order, are the clinical features, on presentation, that are the most predictive. The predictive models that learned from historical data of patients from these two hospitals achieved 70% to 80% accuracy in predicting severe cases.

Catalytic Asymmetric Synthesis of the anti-COVID-19 Drug Remdesivir.

The catalytic asymmetric synthesis of the anti-COVID-19 drug Remdesivir has been realized by the coupling of the P-racemic phosphoryl chloride with protected nucleoside GS441524. The chiral bicyclic imidazole catalyst used is crucial for the dynamic kinetic asymmetric transformation (DyKAT) to proceed smoothly with high reactivity and excellent stereoselectivity (96 % conv., 22:1 SP :RP ). Mechanistic studies showed that this DyKAT is a first-order visual kinetic reaction dependent on the catalyst concentration. The unique chiral bicyclic imidazole skeleton and carbamate substituent of the catalyst are both required for the racemization process, involving the phosphoryl chloride, and subsequent stereodiscriminating step. A 10 gram scale reaction was also conducted with comparably excellent results, showing its potential for industrial application.

Lactate dehydrogenase and susceptibility to deterioration of mild COVID-19 patients: a multicenter nested case-control study.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has infected more than 4 million people within 4 months. There is an urgent need to properly identify high-risk cases that are more likely to deteriorate even if they present mild diseases on admission. METHODS: A multicenter nested case-control study was conducted in four designated hospitals in China enrolling confirmed COVID-19 patients who were mild on admission. Baseline clinical characteristics were compared between patients with stable mild illness (stable mild group) and those who deteriorated from mild to severe illness (progression group). RESULTS: From Jan 17, 2020, to Feb 1, 2020, 85 confirmed COVID-19 patients were enrolled, including 16 in the progression group and 69 in the stable mild group. Compared to stable mild group (n = 69), patients in the progression group (n = 16) were more likely to be older, male, presented with dyspnea, with hypertension, and with higher levels of lactase dehydrogenase and c-reactive protein. In multivariate logistic regression analysis, advanced age (odds ratio [OR], 1.012; 95% confidence interval [CI], 1.020-1.166; P = 0.011) and the higher level of lactase dehydrogenase (OR, 1.012; 95% CI, 1.001-1.024; P = 0.038) were independently associated with exacerbation in mild COVID-19 patients. CONCLUSION: Advanced age and high LDH level are independent risk factors for exacerbation in mild COVID-19 patients. Among the mild patients, clinicians should pay more attention to the elderly patients or those with high LDH levels.