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Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis

Background and objectives: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to more than 200 countries. In light of this situation, the Japanese Government declared a state of emergency in seven regions of Japan on 7 April 2020 u...

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Autores principales: Fujii, Yosuke, Daijo, Hiroki, Hirota, Kiichi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7915187/
https://www.ncbi.nlm.nih.gov/pubmed/33567770
http://dx.doi.org/10.3390/medicina57020153
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author Fujii, Yosuke
Daijo, Hiroki
Hirota, Kiichi
author_facet Fujii, Yosuke
Daijo, Hiroki
Hirota, Kiichi
author_sort Fujii, Yosuke
collection PubMed
description Background and objectives: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to more than 200 countries. In light of this situation, the Japanese Government declared a state of emergency in seven regions of Japan on 7 April 2020 under the provisions of the law. The medical care delivery system has been under pressure. Although various surgical societies have published guidelines on which to base their surgical decisions, it is not clear how general anesthesia has been performed and will be performed in Japan. Materials and Methods: One of the services provided by the social network service Twitter is a voting function—Twitter Polls—through which anonymous surveys were conducted. We analyzed the results of a series of surveys 17 times over 22 weeks on Twitter on the status of operating restrictions using quadratic programming to solve the mathematical optimizing problem, and public data provided by the Japanese Government were used to estimate the current changes in the number of general anesthesia performed in Japan. Results: The minimum number of general anesthesia cases per week was estimated at 67.1% compared to 2015 on 27 April 2020. The timeseries trend was compatible with the results reported by the Japanese Society of Anesthesiologists (correlation coefficient r = 0.69, p < 0.001). Conclusions: The number of general anesthesia was reduced up to two-thirds during the pandemic of COVID-19 in Japan and was successfully quantitatively estimated using a quick questionnaire on Twitter.
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spelling pubmed-79151872021-03-01 Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis Fujii, Yosuke Daijo, Hiroki Hirota, Kiichi Medicina (Kaunas) Article Background and objectives: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to more than 200 countries. In light of this situation, the Japanese Government declared a state of emergency in seven regions of Japan on 7 April 2020 under the provisions of the law. The medical care delivery system has been under pressure. Although various surgical societies have published guidelines on which to base their surgical decisions, it is not clear how general anesthesia has been performed and will be performed in Japan. Materials and Methods: One of the services provided by the social network service Twitter is a voting function—Twitter Polls—through which anonymous surveys were conducted. We analyzed the results of a series of surveys 17 times over 22 weeks on Twitter on the status of operating restrictions using quadratic programming to solve the mathematical optimizing problem, and public data provided by the Japanese Government were used to estimate the current changes in the number of general anesthesia performed in Japan. Results: The minimum number of general anesthesia cases per week was estimated at 67.1% compared to 2015 on 27 April 2020. The timeseries trend was compatible with the results reported by the Japanese Society of Anesthesiologists (correlation coefficient r = 0.69, p < 0.001). Conclusions: The number of general anesthesia was reduced up to two-thirds during the pandemic of COVID-19 in Japan and was successfully quantitatively estimated using a quick questionnaire on Twitter. MDPI 2021-02-08 /pmc/articles/PMC7915187/ /pubmed/33567770 http://dx.doi.org/10.3390/medicina57020153 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fujii, Yosuke
Daijo, Hiroki
Hirota, Kiichi
Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
title Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
title_full Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
title_fullStr Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
title_full_unstemmed Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
title_short Estimation of the Number of General Anesthesia Cases Based on a Series of Nationwide Surveys on Twitter during COVID-19 Pandemic in Japan: A Statistical Analysis
title_sort estimation of the number of general anesthesia cases based on a series of nationwide surveys on twitter during covid-19 pandemic in japan: a statistical analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7915187/
https://www.ncbi.nlm.nih.gov/pubmed/33567770
http://dx.doi.org/10.3390/medicina57020153
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