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Conventional risk prediction models fail to accurately predict mortality risk among patients with coronavirus disease 2019 in intensive care units: a difficult time to assess clinical severity and quality of care

Authors :
Hideki Endo
Hiroyuki Ohbe
Junji Kumasawa
Shigehiko Uchino
Satoru Hashimoto
Yoshitaka Aoki
Takehiko Asaga
Eiji Hashiba
Junji Hatakeyama
Katsura Hayakawa
Nao Ichihara
Hiromasa Irie
Tatsuya Kawasaki
Hiroshi Kurosawa
Tomoyuki Nakamura
Hiroshi Okamoto
Hidenobu Shigemitsu
Shunsuke Takaki
Kohei Takimoto
Masatoshi Uchida
Ryo Uchimido
Hiroaki Miyata
Source :
Journal of Intensive Care, Vol 9, Iss 1, Pp 1-4 (2021)
Publication Year :
2021
Publisher :
BMC, 2021.

Abstract

Abstract Since the start of the coronavirus disease 2019 (COVID-19) pandemic, it has remained unknown whether conventional risk prediction tools used in intensive care units are applicable to patients with COVID-19. Therefore, we assessed the performance of established risk prediction models using the Japanese Intensive Care database. Discrimination and calibration of the models were poor. Revised risk prediction models are needed to assess the clinical severity of COVID-19 patients and monitor healthcare quality in ICUs overwhelmed by patients with COVID-19.

Details

Language :
English
ISSN :
20520492
Volume :
9
Issue :
1
Database :
Directory of Open Access Journals
Journal :
Journal of Intensive Care
Publication Type :
Academic Journal
Accession number :
edsdoj.4b81d101211d4aaba5a0da9775e9ac2b
Document Type :
article
Full Text :
https://doi.org/10.1186/s40560-021-00557-5