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10.24875/ACM.20000370 http://scihub22266oqcxt.onion/10.24875/ACM.20000370 33147597!10161849!33147597     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Arch+Cardiol+Mex 2021 ; 91 (Suplemento COVID): 001-011 Nephropedia Template TP {{tp|p=33147597|t=2021. The 2020 research pandemic: A bibliometric analysis of publications on COVID-19 and their scientific impact during the first months |pdf=|usr=}}{{33147597}} gab.com Text The 2020 research pandemic: A bibliometric analysis of publications on COVID-19 and their scientific impact during the first months JO: Arch Cardiol Mex http://www.kidney.de/pget.php?&tw=1&pmid=33147597 #FOAvip BACKGROUND: The outbreak of COVID-19 has created a landslide of publications, from different sources and unequal impact. We considered that the first 3 months are crucial to understand how knowledge has been generated by performing a bibliometric analysis, including the citations to these articles to guide researchers in exploring this field, and to evaluate the relationship between confirmed COVID-19 cases and deaths with the number of papers per country. METHODS: Scientific publications were obtained from PubMed (January-March 2020) and their citations during the first 6 months retrieved from the Scopus database. An analysis of the number of papers by country, approach (type and category of publication), and impact was made. A multiple linear regression model was implemented to analyze the correlation between the number of publications and confirmed cases and deaths. RESULTS: A total of 2,530 publications were analyzed with 59,104 citations (23.4 citations/article), written by authors from 67 countries. China was the country with more publications (988, 39%) and more citations (36,416, 63%) followed by the United States with 423 articles (16.7%) and 7,458 citations (12.6%). The coauthorship network identified 10,756 authors. According to the multivariate analysis, both confirmed cases and deaths were significantly correlated with the number of publications per country (corrected by population size and gross domestic product). CONCLUSION: The correlation with the number of publications suggests that cases and deaths had some impact on the medical literature, reflecting how rapidly the scientific community has been on the frontline in the fight against COVID-19. Twit Text FOAVip The 2020 research pandemic: A bibliometric analysis of publications on COVID-19 and their scientific impact during the first months ????Arch Cardiol Mex http://www.kidney.de/pget.php?&tw=1&pmid=33147597 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33147597 #FOAvip English Wikipedia <ref>{{Cite pmid|33147597}}</ref> The 2020 research pandemic: A bibliometric analysis of publications on COVID-19 and their scientific impact during the first months #MMPMID33147597 Dieguez-Campa CE; Perez-Neri I; Reyes-Teran G; Flores-Apodaca IA; Castillo-Ledon-Pretelini J; Mercado-Bautista O; Alvarez-Santana R; Zenteno MA; Bowles B; Lee A Arch Cardiol Mex 2021[Dec]; 91 (Suplemento COVID): 001-011 PMID33147597show ga BACKGROUND: The outbreak of COVID-19 has created a landslide of publications, from different sources and unequal impact. We considered that the first 3 months are crucial to understand how knowledge has been generated by performing a bibliometric analysis, including the citations to these articles to guide researchers in exploring this field, and to evaluate the relationship between confirmed COVID-19 cases and deaths with the number of papers per country. METHODS: Scientific publications were obtained from PubMed (January-March 2020) and their citations during the first 6 months retrieved from the Scopus database. An analysis of the number of papers by country, approach (type and category of publication), and impact was made. A multiple linear regression model was implemented to analyze the correlation between the number of publications and confirmed cases and deaths. RESULTS: A total of 2,530 publications were analyzed with 59,104 citations (23.4 citations/article), written by authors from 67 countries. China was the country with more publications (988, 39%) and more citations (36,416, 63%) followed by the United States with 423 articles (16.7%) and 7,458 citations (12.6%). The coauthorship network identified 10,756 authors. According to the multivariate analysis, both confirmed cases and deaths were significantly correlated with the number of publications per country (corrected by population size and gross domestic product). CONCLUSION: The correlation with the number of publications suggests that cases and deaths had some impact on the medical literature, reflecting how rapidly the scientific community has been on the frontline in the fight against COVID-19. |*Bibliometrics[MESH] |*Biomedical Research/trends[MESH] |*COVID-19[MESH] |China[MESH] |Databases, Factual[MESH] |Humans[MESH] |Pandemics[MESH] |Publications/statistics & numerical data[MESH]The 2020 research pandemic: A bibliometric analysis of publications on(epmc).pdf DeepDyve Pubget Overpricing