Status and hotspot analysis of Qingfei Paidu Decoction for the prevention and treatment of COVID-19 based on bibliometric analysis.

Background: Qingfei Paidu Decoction (QFPDD) has played an important role in the prevention and treatment of COVID-19 infection in China. The present study aims to perform an econometric analysis and visualization of the literature on the treatment of COVID-19 with QFPDD in the Chinese databases and English databases. Methods: Six databases including such as Chinese databases CNKI, VIP, CBM, WANFANG as well as English databases PubMed, Web of Science were searched for publications related to the prevention and treatment of COVID-19 with QFPDD. The institutions, authors, keywords of each publication were cisualized using the software of CiteSpace. Results: A total of 187 literature on the prevention and treatment of novel coronavirus infection with QFPDD were included, of which 145 (77.5%) were in Chinese and 42 (22.5%) were in English. Those publications were written by 926 authors from 383 institutions. There were 78 theoretical studies (41.7%), 63 clinical studies (33.7%), and 46 basic studies (24.6%). The cooperative institutions with the core of "Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences" and "Shanghai University of Chinese Medicine Cross Academy of Science" have been formed, and two core teams with "Wang Yanping" and "Zhang Weidong" have been formed. The keyword analysis showed that the research mainly focuses on pathologic pathogenesis, clinical efficacy, adverse reactions, integrated Chinese and western medicine therapy, network pharmacology research. Conclusion: QFPDD has attracted worldwide attention, mechanism research and clinical research may become a future development trend. Therefore, in-depth basic research and clinical studies with large samples and multi-center cooperation should be carried out to provide high-level evidence-based evidence for the prevention and treatment of COVID-19 with QFPDD.

Effect of Qingfei Paidu decoction combined with Western medicine treatments for COVID-19: A systematic review and meta-analysis.

BACKGROUND: Qingfei Paidu decoction (QFPDD) showed to be beneficial for the treatment of coronavirus disease 2019 (COVID-19) in China. PURPOSE: This study aimed to systematically assemble the evidence on the efficacy and safety of QFPDD combined with Western medicine treatments (WMT) for COVID-19. STUDY DESIGN: Systematic review and meta-analysis. METHODS: A comprehensive literature search was conducted in PubMed, Embase, Cochrane Library, CNKI, CSTJ, CBM, Wanfang Data for clinical trials with a control arm until January 13, 2022. Studies matched the selection criteria were included. Data extraction and quality assessment of the included studies were independently conducted by two reviewers. Review Manager 5.4 was used for meta-analysis. RESULTS: A total of 9 trials including 1108 COVID-19 patients met the selection criteria. Meta-analysis demonstrated that QFPDD combined with WMT reduced aggravation rate (AR) by 71% [risk ratio (RR) = 0.29, 95% confidence intervals (CI) (0.17, 0.51)], increased effective rate (ER) by 13% [RR = 1.13, 95%CI (1.04, 1.22)], shortened 4.78 days of viral shedding [95%CI (-5.79, -3.77)] and 4.45 days of hospital stay [95%CI (-6.05, -2.86)], also decreased the incidence of adverse events (AE) by 56% [RR = 0.44, 95%CI (0.22, 0.89)]. CONCLUSION: QFPDD combined with WMT might reduce the proportion of severe cases and the incidence of AE, shorten the duration of viral shedding and length of hospital stay. More randomized controlled trials (RCTs) are required to confirm our findings in the future.

Research on the Evaluation Method of Enterprises' Independent Innovation Ability Based on Improved BP Neural Network and DQN Algorithm.

The development of enterprises has a very important influence on promoting national economic growth and improving comprehensive economic strength. This work evaluates the independent innovation ability of enterprises, analyzes the characteristics and difficulties of technological innovation of enterprises, and proposes corresponding solutions to promote independent technological innovation of enterprises. Firstly, the characteristics of the research object are clarified, and on the basis of relevant research, the theory of technological innovation and evaluation at home and abroad is expounded. At the same time, the basic theory of the improved BP neural network and DQN algorithm is introduced, which provides a theoretical basis for the research of the thesis. Secondly, according to the characteristics of enterprise technological innovation, an index system for evaluating the technological innovation capability of enterprises is constructed. Then, according to the related theory of the improved BP neural network and DQN algorithm, a neural network model for evaluating the technological innovation capability of enterprises is designed, and the validity of the model is verified through empirical research. Finally, this paper applies the evaluation model to the surveyed enterprises, comprehensively analyzes the characteristics and existing problems of independent technological innovation of enterprises, and proposes practical and feasible countermeasures to improve technological innovation capabilities from the perspective of enterprises themselves. The research results of this paper can be used as an effective supplement to the research on independent technological innovation of enterprises, and at the same time promote the continuous improvement of independent technological innovation capabilities of enterprises.

Diagnostic Value of Neutrophil-Lymphocyte Ratio and Platelet-Lymphocyte Ratio in Patients with Severe COVID-19 - 7 PLADs, China, January 21-February 10, 2020.

What is already known about this topic?: Coronavirus disease 2019 (COVID-19) causes symptoms ranging from mild to severe. Indicators for identifying severe COVID-19 infection have not been well identified, especially for young patients. What is added by this report?: Both neutrophil-lymphocyte ratio (NLR) [area under curve (AUC): 0.80; the odds ratios (OR) and 95% confidence intervals (95% CI): 1.30 (1.13-1.50)] and platelet-lymphocyte ratio (PLR) [AUC: 0.87; OR (95% CI): 1.05 (1.01-1.09)] were determined to be indicators for recognition of patients with severe COVID-19 in young patients less than age 40. What are the implications for public health practice?: NLR and PLR are useful indicators for identifying patients with severe COVID-19, especially in young patients less than age 40.

Association between early treatment with Qingfei Paidu decoction and favorable clinical outcomes in patients with COVID-19: A retrospective multicenter cohort study.

The coronavirus disease 2019 (COVID-19) epidemic has been almost controlled in China under a series of policies, including "early diagnosis and early treatment". This study aimed to explore the association between early treatment with Qingfei Paidu decoction (QFPDD) and favorable clinical outcomes. In this retrospective multicenter study, we included 782 patients (males, 56 %; median age 46) with confirmed COVID-19 from 54 hospitals in nine provinces of China, who were divided into four groups according to the treatment initiation time from the first date of onset of symptoms to the date of starting treatment with QFPDD. The primary outcome was time to recovery; days of viral shedding, duration of hospital stay, and course of the disease were also analyzed. Compared with treatment initiated after 3 weeks, early treatment with QFPDD after less than 1 week, 1-2 weeks, or 2-3 weeks had a higher likelihood of recovery, with adjusted hazard ratio (HR) (95 % confidence interval [CI]) of 3.81 (2.65-5.48), 2.63 (1.86-3.73), and 1.92 (1.34-2.75), respectively. The median course of the disease decreased from 34 days to 24 days, 21 days, and 18 days when treatment was administered early by a week (P < 0.0001). Treatment within a week was related to a decrease by 1-4 days in the median duration of hospital stay compared with late treatment (P<0.0001). In conclusion, early treatment with QFPDD may serve as an effective strategy in controlling the epidemic, as early treatment with QFPDD was associated with favorable outcomes, including faster recovery, shorter time to viral shedding, and a shorter duration of hospital stay. However, further multicenter, prospective studies with a larger sample size should be conducted to confirm the benefits of early treatment with QFPDD.

A rapid advice guideline for the diagnosis and treatment of 2019 novel coronavirus (2019-nCoV) infected pneumonia (standard version).

In December 2019, a new type viral pneumonia cases occurred in Wuhan, Hubei Province; and then named "2019 novel coronavirus (2019-nCoV)" by the World Health Organization (WHO) on 12 January 2020. For it is a never been experienced respiratory disease before and with infection ability widely and quickly, it attracted the world's attention but without treatment and control manual. For the request from frontline clinicians and public health professionals of 2019-nCoV infected pneumonia management, an evidence-based guideline urgently needs to be developed. Therefore, we drafted this guideline according to the rapid advice guidelines methodology and general rules of WHO guideline development; we also added the first-hand management data of Zhongnan Hospital of Wuhan University. This guideline includes the guideline methodology, epidemiological characteristics, disease screening and population prevention, diagnosis, treatment and control (including traditional Chinese Medicine), nosocomial infection prevention and control, and disease nursing of the 2019-nCoV. Moreover, we also provide a whole process of a successful treatment case of the severe 2019-nCoV infected pneumonia and experience and lessons of hospital rescue for 2019-nCoV infections. This rapid advice guideline is suitable for the first frontline doctors and nurses, managers of hospitals and healthcare sections, community residents, public health persons, relevant researchers, and all person who are interested in the 2019-nCoV.