Journal of Intensive Care (Jun 2021)
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,
- 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
Affiliations
- Hideki Endo
- Department of Healthcare Quality Assessment, Graduate School of Medicine, The University of Tokyo
- Hiroyuki Ohbe
- Department of Clinical Epidemiology and Health Economics, School of Public Health, The University of Tokyo
- Junji Kumasawa
- Department of Critical Care Medicine, Sakai City Medical Center
- Shigehiko Uchino
- Intensive Care Unit, The Jikei University School of Medicine
- Satoru Hashimoto
- Department of Anesthesiology and Intensive Care Medicine, Kyoto Prefectural University of Medicine
- Yoshitaka Aoki
- Department of Anesthesiology and Intensive Care Medicine, Hamamatsu University School of Medicine
- Takehiko Asaga
- Intensive Care Unit, Kagawa University Hospital
- Eiji Hashiba
- Division of Intensive Care, Hirosaki University Hospital
- Junji Hatakeyama
- Department of Emergency and Critical Care Medicine, National Hospital Organization Tokyo Medical Center
- Katsura Hayakawa
- Department of Emergency and Critical Care Medicine, Saitama Red Cross Hospital
- Nao Ichihara
- Department of Healthcare Quality Assessment, Graduate School of Medicine, The University of Tokyo
- Hiromasa Irie
- Department of Anesthesiology, Kurashiki Central Hospital
- Tatsuya Kawasaki
- Department of Pediatric Critical Care, Shizuoka Children’s Hospital
- Hiroshi Kurosawa
- Department of Pediatric Critical Care Medicine, Hyogo Prefectural Kobe Children’s Hospital
- Tomoyuki Nakamura
- Department of Anesthesiology and Critical Care Medicine, Fujita Health University School of Medicine
- Hiroshi Okamoto
- Department of Critical Care Medicine, St. Luke’s International Hospital
- Hidenobu Shigemitsu
- Department of Intensive Care Medicine, Graduate School of Medicine, Tokyo Medical and Dental University
- Shunsuke Takaki
- Department of Anesthesiology and Critical Care Medicine, Yokohama City University
- Kohei Takimoto
- Department of Intensive Care Medicine, Kameda Medical Center
- Masatoshi Uchida
- Department of Emergency and Critical Care Medicine, Dokkyo Medical University
- Ryo Uchimido
- Department of Intensive Care Medicine, Graduate School of Medicine, Tokyo Medical and Dental University
- Hiroaki Miyata
- Department of Health Policy and Management, School of Medicine, Keio University
- DOI
- https://doi.org/10.1186/s40560-021-00557-5
- Journal volume & issue
-
Vol. 9,
no. 1
pp. 1 – 4
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.
Keywords
- Coronavirus disease 2019
- Risk of death
- Intensive care unit
- Risk prediction model
- Quality improvement
