Carotid Enadrterectomy for Thrombosis of the Internal Carotid Artery in Patients With COVID-19.

Analysis of the results of emergency carotid endarterectomy (CEE) against the background of internal carotid artery (ICA) thrombosis in the acute period of acute cerebrovascular accident (ACVA) in patients with COVID-19. During the COVID-19 pandemic (April 1, 2020-May 1, 2021), 43 patients with ICA thrombosis and a positive polymerase chain reaction (PCR) result for SARS-CoV-2 were included in this prospective study. In all cases, CEE was performed in the acutest period of ACVA. These patients were included in group 1. The comparison group was represented by 89 patients who underwent CEE in the acute period of stroke, in the period before the COVID-19 pandemic (April 1, 2019-March 1, 2020). According to laboratory parameters, patients with COVID-19 had severe coagulopathy (with an increase in D-dimer: 3832 ± 627.2 ng/mL, fibrinogen: 12.6 ± 3.1 g/L, prothrombin: 155.7 ± 10, 2%), inflammatory syndrome (increased ferritin: 646.2 ± 56.1 ng/mL, C-reactive protein: 161.3 ± 17.2 mg/L, interleukin-6: 183.3 ± 51.7 pg/mL, leukocytosis: 27.3 ± 1.7 10E9/L). In the hospital postoperative period, the groups were comparable in terms of the incidence of deaths (group 1: 2.3%, n = 1; group 2: 1.1%, n = 1; P= 0.81; OR=2.09; 95 % CI = 0.12-34.3) myocardial infarction (group 1: 2.3%, n = 1; group 2: 0%; P= 0.7; OR = 6.3; 95% CI = 0.25-158.5), CVA (group 1: 2.3%, n = 1; group 2: 2.2%, n = 2; P= 0.55; OR = 1.03; 95% CI = 0,.09-11.7). ICA thrombosis and hemorrhagic transformations were not recorded. However, due to severe coagulopathy with ongoing anticoagulant/antiplatelet therapy, patients with COVID-19 more often developed bleeding in the operation area (group 1: 11.6%, n = 5; group 2: 1.1%, n = 1; P= 0.02; OR = 11.5; 95% CI = 1.3-102.5). In all cases, the flow of hemorrhagic discharge came from the drainage localized in the subcutaneous fat. This made it possible to remove skin sutures in a dressing room, suturing the source of bleeding and applying secondary sutures under local anesthesia. Emergency CEE in the acute period of stroke is an effective and safe method of cerebral revascularization in case of ICA thrombosis in conditions of COVID-19.

Into the Unobservables: A Multi-range Encoder-decoder Framework for COVID-19 Prediction

The ongoing COVID-19 pandemic has dramatically changed people's daily lives. A robust forecasting model for COVID-19 infections is essential for governments and institutions to plan timely and perform accurate interventions. Mainstream solutions for COVID-19 prediction fit reported data only by considering observed cases. However, the neglected facts that positive samples are incomplete and many facts of the novel disease are unknown may be prone to cause severe error accumulation, especially in long-term predictions. To fully understand the spreading patterns of the virus, we propose an encoder-decoder framework: (i) in the encoder we embed historical case data into multiple expose-infection ranges and learn message passing between time slices and across ranges with coarse-grained human mobility data incorporated;(ii) in the decoder, we decode the embedded features based on reported cases as well as deaths to jointly consider the effect of both observed and hidden data. We model the spreading of disease in over 60 counties of California and New York, which are two of the most metropolitan areas in the US. The proposed framework significantly outperforms state-of-the-art baselines on JHU COVID-19 dataset on both weekly prediction and daily prediction tasks. We design detailed ablation studies to verify the effectiveness of each key module and find the model not only works with the assistance of mobility data but also with purely cases and deaths, which implies its broad application scenarios. © 2021 ACM.

Multi-faceted classification for the identification of informative communications during crises: Case of Covid-19

Social media data are used to enhance crisis management, as people widely adopt social media to share and acquire information to cope with uncertainties in crises. Identification and extraction of informative communications out of large volumes of data is critical for accurate situational awareness and timely response. Existing studies use conditions of geolocations, keywords, and topics separately or jointly to retrieve data that can be crisis related, but are not enough to filter subsets of data for different crisis management tasks. We propose that the crisis communication purposes of users can be detected to enhance data selection and prioritization for different crisis management tasks. A classification framework was built to identify three facets of a message: content type, audience type, and information source. The definitions of these categories are not dependent on a specific type of crises. So the classification framework can be potentially applied to different crisis scenarios. Machine learning models were created for the automatic classification of messages. Results showed the CNN-based model achieved the best accuracy (88.5%) for the classification of content type. The proposed Naive Bayes and logistic repression with predetermined features can best differentiate audience types and information source with an accuracy of 72.7% and 72.2%, respectively. © 2021 IEEE.

Review of nuclear technology in the application of COVID-19 epidemic prevention and control

In the early stage of the outbreak of COVD-19 in Wuhan city at the end of 2019, the demand for medical protective equipment increased rapidly. Many problems emerged, such as poor quality and short supply of protective masks, shortage of medical supplies caused by long sterilization cycles, difficult treatment of the medical waste and wastewater of which might cause the secondary infection. Herein, three specific applications of nuclear technology were summarized to fight against the COVID-19. The first one is the nuclear pore membrane (NPM) produced by nuclear technology. It can be used to fabricate face masks with high filtration efficiency and good reusability after simple processing. Hence the problems of poor reusability and poor filtration effects of common disposable masks can be solved by using NPM technology. The second application is the radiation sterilization technology in the process of producing medical supplies such as masks and protective clothing. The long cycle of common sterilization technology makes the demand exceed supply whereas the radiation sterilization technology can greatly shorten the production cycle and increase output, which could alleviate the shortage of medical supplies in anti-epidemic process. The third application is the use of γ-ray, X-ray or high-energy electron to sterilize medical wastewater and garbage, among which massive of surviving coronavirus are still infectious. It can treat large-volume of wastewater rapidly with a broad vision of application. Due to these unique advantages, nuclear technology has been playing an important role in this epidemic prevention and control, it possesses broader development prospects in the future. © 2020, Science Press. All right reserved.

Causes and countermeasures of false-negative results for 2019 novel coronavirus nucleic acid test

In December 2019, a cluster of patients with pneumonia of unknown cause were linked to a seafood wholesale market in Wuhan, China. Some studies found that the virus was a new kind of virus which had never been found in the human body. Then, the virus was named 2019 novel coronavirus (2019-nCoV) by the World Health Organization (WHO). 2019-nCoV nucleic acid detection is one of the essential indicators of COVID-19. Recently, some false-negative cases in China-Japan Friendship Hospital and Hangzhou Hospital led the clinical doctors to question the value of the nucleic acid detection. In this paper, more than 3 000 results of 2019-nCoV detection in Zhongnan Hospital, Wuhan University were analyzed. Attention should be paid to the root cause of false-negative results and the related countermeasures should be taken.