KIKUCHI Ken
Department School of Medicine(Tokyo Women's Medical University Hospital), School of Medicine Position Professor |
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Article types | Original article |
Language | English |
Peer review | Peer reviewed |
Title | Polymerase-chain reaction testing to prevent hospital-acquired severe acute respiratory syndrome coronavirus 2 infection in Shinjuku, an epicenter in Tokyo: The Tokyo Women's Medical University model. |
Journal | Formal name:Respiratory investigation Abbreviation:Respir Investig ISSN code:22125353/22125345 |
Domestic / Foregin | Foregin |
Volume, Issue, Page | 59(3),pp.356-359 |
Author and coauthor | Arimura Ken†, Tagaya Etsuko, Kikuchi Ken, Mitsuda Toshihiro, Yasuda Gaku, Azuma Haruna, Konda Naoko, Ikarashi Yuichi, Chiba Yukihide, Kusama Kaoru, Sakama Reiko, Hagiwara Shotaro, Shimizu Satoru, Shimamoto Ken, Nomura Minoru, Yaguchi Arino, Niinami Hiroshi, Kondo Mitsuko, Tanabe Kazunari, Kawana Masatoshi |
Publication date | 2021/05 |
Summary | Hospital-acquired severe acute respiratory virus coronavirus 2 (SARS-CoV-2) infection is a healthcare challenge. We hypothesized that polymerase chain reaction testing of symptomatic triaged outpatients and all inpatients before hospitalization in Shinjuku, a coronavirus disease 2019 (COVID-19) epicenter in Tokyo, using the Tokyo Women's Medical University (TMWU) model would be feasible and efficient at preventing COVID-19. This retrospective study enrolled 2981 patients from March to May 2020. The prevalence of SARS-CoV-2 infection was 1.81% (95% credible interval [CI]: 0.95-3.47%) in triaged symptomatic outpatients, 0.04% (95% CI: 0.0002-0.2%) in scheduled asymptomatic inpatients, 3.78% (95% CI: 1.82-7.26%) in emergency inpatients, and 2.4% (95% CI: 1.49-3.82%) in symptomatic patients. There were no cases of hospital-acquired SARS-CoV-2 infection. This shows that the TWMU model could prevent hospital-acquired SARS-CoV-2 infection and is feasible and effective in reducing the impact of SARS-CoV-2 infection in the hospitals. |
DOI | 10.1016/j.resinv.2020.12.009 |
PMID | 33579647 |