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10.1213/ANE.0000000000005602 http://scihub22266oqcxt.onion/10.1213/ANE.0000000000005602 33886509!ä!33886509 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Anesth+Analg 2021 ; 133 (2): 515-525 Nephropedia Template TP {{tp|p=33886509|t=2021. Dissemination of Anesthesia Information During the Coronavirus Disease 2019 Pandemic Through Twitter: An Infodemiology Study |pdf=|usr=}}{{33886509}} gab.com Text Dissemination of Anesthesia Information During the Coronavirus Disease 2019 Pandemic Through Twitter: An Infodemiology Study JO: Anesth Analg http://www.kidney.de/pget.php?&tw=1&pmid=33886509 #FOAvip BACKGROUND: Twitter is a web-based social media platform that allows instantaneous sharing of user-generated messages (tweets). We performed an infodemiology study of the coronavirus disease 2019 (COVID-19) Twitter conversation related to anesthesiology to describe how Twitter has been used during the pandemic and ways to optimize Twitter use by anesthesiologists. METHODS: This was a cross-sectional study of tweets related to the specialty of anesthesiology and COVID-19 tweeted between January 21 and October 13, 2020. A publicly available COVID-19 Twitter dataset was filtered for tweets meeting inclusion criteria (tweets including anesthesiology keywords). Using descriptive statistics, tweets were reviewed for tweet and account characteristics. Tweets were filtered for specific topics of interest likely to be impactful or informative to anesthesiologists of COVID-19 practice (airway management, personal protective equipment, ventilators, COVID testing, and pain management). Tweet activity was also summarized descriptively to show temporal profiles over the pandemic. RESULTS: Between January 21 and October 13, 2020, 23,270 of 241,732,881 tweets (0.01%) met inclusion criteria and were generated by 15,770 accounts. The majority (51.9%) of accounts were from the United States. Seven hundred forty-nine (4.8%) of all users self-reported as anesthesiologists. 33.8% of all tweets included at least one word or phrase preceded by the # symbol (hashtag), which functions as a label to search for all tweets including a specific hashtag, with the most frequently used being #anesthesia. About half (52.2%) of all tweets included at least one hyperlink, most frequently linked to other social media, news organizations, medical organizations, or scientific publications. The majority of tweets (67%) were not retweeted. COVID-19 anesthesia tweet activity started before the pandemic was declared. The trend of daily tweet activity was similar to, and preceded, the US daily death count by about 2 weeks. CONCLUSIONS: The toll of the pandemic has been reflected in the anesthesiology conversation on Twitter, representing 0.01% of all COVID-19 tweets. Daily tweet activity showed how the Twitter community used the platform to learn about important topics impacting anesthesiology practice during a global pandemic. Twitter is a relevant platform through which to communicate about anesthesiology topics, but further research is required to delineate its effectiveness, benefits, and limitations for anesthesiology discussions. Twit Text FOAVip Dissemination of Anesthesia Information During the Coronavirus Disease 2019 Pandemic Through Twitter: An Infodemiology Study ????Anesth Analg http://www.kidney.de/pget.php?&tw=1&pmid=33886509 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33886509 #FOAvip English Wikipedia <ref>{{Cite pmid|33886509}}</ref> Dissemination of Anesthesia Information During the Coronavirus Disease 2019 Pandemic Through Twitter: An Infodemiology Study #MMPMID33886509 Gai N; So D; Siddiqui A; Steinberg BE Anesth Analg 2021[Aug]; 133 (2): 515-525 PMID33886509show ga BACKGROUND: Twitter is a web-based social media platform that allows instantaneous sharing of user-generated messages (tweets). We performed an infodemiology study of the coronavirus disease 2019 (COVID-19) Twitter conversation related to anesthesiology to describe how Twitter has been used during the pandemic and ways to optimize Twitter use by anesthesiologists. METHODS: This was a cross-sectional study of tweets related to the specialty of anesthesiology and COVID-19 tweeted between January 21 and October 13, 2020. A publicly available COVID-19 Twitter dataset was filtered for tweets meeting inclusion criteria (tweets including anesthesiology keywords). Using descriptive statistics, tweets were reviewed for tweet and account characteristics. Tweets were filtered for specific topics of interest likely to be impactful or informative to anesthesiologists of COVID-19 practice (airway management, personal protective equipment, ventilators, COVID testing, and pain management). Tweet activity was also summarized descriptively to show temporal profiles over the pandemic. RESULTS: Between January 21 and October 13, 2020, 23,270 of 241,732,881 tweets (0.01%) met inclusion criteria and were generated by 15,770 accounts. The majority (51.9%) of accounts were from the United States. Seven hundred forty-nine (4.8%) of all users self-reported as anesthesiologists. 33.8% of all tweets included at least one word or phrase preceded by the # symbol (hashtag), which functions as a label to search for all tweets including a specific hashtag, with the most frequently used being #anesthesia. About half (52.2%) of all tweets included at least one hyperlink, most frequently linked to other social media, news organizations, medical organizations, or scientific publications. The majority of tweets (67%) were not retweeted. COVID-19 anesthesia tweet activity started before the pandemic was declared. The trend of daily tweet activity was similar to, and preceded, the US daily death count by about 2 weeks. CONCLUSIONS: The toll of the pandemic has been reflected in the anesthesiology conversation on Twitter, representing 0.01% of all COVID-19 tweets. Daily tweet activity showed how the Twitter community used the platform to learn about important topics impacting anesthesiology practice during a global pandemic. Twitter is a relevant platform through which to communicate about anesthesiology topics, but further research is required to delineate its effectiveness, benefits, and limitations for anesthesiology discussions. |*COVID-19[MESH] |*Information Dissemination[MESH] |Anesthesiologists/*trends[MESH] |Anesthesiology/*trends[MESH] |Cross-Sectional Studies[MESH] |Humans[MESH] |Scholarly Communication/*trends[MESH] |Social Media/*trends[MESH]Dissemination of Anesthesia Information During the Coronavirus Disease(epmc).pdf DeepDyve Pubget Overpricing