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

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 Japane...

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Veröffentlicht in:Journal of intensive care 2021-06, Vol.9 (1), p.1-42, Article 42
Hauptverfasser: Endo, Hideki, Ohbe, Hiroyuki, Kumasawa, Junji, Uchino, Shigehiko, Hashimoto, Satoru, Aoki, Yoshitaka, Asaga, Takehiko, Hashiba, Eiji, Hatakeyama, Junji, Hayakawa, Katsura, Ichihara, Nao, Irie, Hiromasa, Kawasaki, Tatsuya, Kurosawa, Hiroshi, Nakamura, Tomoyuki, Okamoto, Hiroshi, Shigemitsu, Hidenobu, Takaki, Shunsuke, Takimoto, Kohei, Uchida, Masatoshi, Uchimido, Ryo, Miyata, Hiroaki
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Sprache:eng
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Zusammenfassung: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.
ISSN:2052-0492
2052-0492
DOI:10.1186/s40560-021-00557-5