J Intensive Care . 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

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J Intensive Care


. 2021 Jun 1;9(1):42.
doi: 10.1186/s40560-021-00557-5.
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


Hideki Endo ^{1 2} , Hiroyuki Ohbe ³ , Junji Kumasawa ⁴ , Shigehiko Uchino ⁵ , Satoru Hashimoto ⁶ , Yoshitaka Aoki ⁷ , Takehiko Asaga ⁸ , Eiji Hashiba ⁹ , Junji Hatakeyama ¹⁰ , Katsura Hayakawa ¹¹ , Nao Ichihara ¹² , Hiromasa Irie ¹³ , Tatsuya Kawasaki ¹⁴ , Hiroshi Kurosawa ¹⁵ , Tomoyuki Nakamura ¹⁶ , Hiroshi Okamoto ¹⁷ , Hidenobu Shigemitsu ¹⁸ , Shunsuke Takaki ¹⁹ , Kohei Takimoto ²⁰ , Masatoshi Uchida ²¹ , Ryo Uchimido ¹⁸ , Hiroaki Miyata ²²



Affiliations

• PMID: 34074343
• DOI: 10.1186/s40560-021-00557-5

Free article

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.

Keywords: Coronavirus disease 2019; Intensive care unit; Quality improvement; Risk of death; Risk prediction model.