TY - JOUR
T1 - Conventional risk prediction models fail to accurately predict mortality risk among patients with coronavirus disease 2019 in intensive care units
T2 - a difficult time to assess clinical severity and quality of care
AU - Endo, Hideki
AU - Ohbe, Hiroyuki
AU - Kumasawa, Junji
AU - Uchino, Shigehiko
AU - Hashimoto, Satoru
AU - Aoki, Yoshitaka
AU - Asaga, Takehiko
AU - Hashiba, Eiji
AU - Hatakeyama, Junji
AU - Hayakawa, Katsura
AU - Ichihara, Nao
AU - Irie, Hiromasa
AU - Kawasaki, Tatsuya
AU - Kurosawa, Hiroshi
AU - Nakamura, Tomoyuki
AU - Okamoto, Hiroshi
AU - Shigemitsu, Hidenobu
AU - Takaki, Shunsuke
AU - Takimoto, Kohei
AU - Uchida, Masatoshi
AU - Uchimido, Ryo
AU - Miyata, Hiroaki
N1 - Funding Information:
This paper was written as a part of the JIPAD project, which was funded by the Japanese Society of Intensive Care Medicine.
Funding Information:
HE, NI, and HM are affiliated with the Department of Healthcare Quality Assessment at the University of Tokyo. The department is a social collaboration department supported by grants from the National Clinical Database, Johnson & Johnson K.K., and Nipro Corporation. The other authors do not have any competing interests to declare.
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
KW - Coronavirus disease 2019
KW - Intensive care unit
KW - Quality improvement
KW - Risk of death
KW - Risk prediction model
UR - http://www.scopus.com/inward/record.url?scp=85107366319&partnerID=8YFLogxK
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U2 - 10.1186/s40560-021-00557-5
DO - 10.1186/s40560-021-00557-5
M3 - Letter
AN - SCOPUS:85107366319
SN - 2052-0492
VL - 9
JO - Journal of Intensive Care
JF - Journal of Intensive Care
IS - 1
M1 - 42
ER -