Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients.

Autor: Cahan A; Kahun Medical Ltd, Tel Aviv, Israel; Infectious Diseases Unit, Samson Assuta Ashdod University Hospital, Ashdod, Israel. Electronic address: amos@kahun.com., Gottesman T; Department of Infectious Diseases and Infection Control Unit, Hasharon Campus, Rabin Medical Center, Petach Tikva, Israel; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel., Katz MT; Kahun Medical Ltd, Tel Aviv, Israel., Masad R; Kahun Medical Ltd, Tel Aviv, Israel., Azulay G; Kahun Medical Ltd, Tel Aviv, Israel., Dicker D; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Internal Medicine D, Hasharon Campus, Rabin Medical Center, Petach Tikva, Israel., Zeidman A; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Internal Medicine B, Hasharon Campus, Rabin Medical Center, Petach Tikva, Israel., Berkov E; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; Internal Medicine C, Hasharon Campus, Rabin Medical Center, Petach Tikva, Israel., Tadmor B; Research Authority, Rabin Medical Center, Petach Tikva, Israel., Lev S; The Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel; General Intensive Care Unit, Hasharon Hospital, Rabin Medical Center, Petach Tikva, Israel.
Jazyk: angličtina
Zdroj: The American journal of emergency medicine [Am J Emerg Med] 2021 Jan; Vol. 39, pp. 143-145. Date of Electronic Publication: 2020 Sep 23.
DOI: 10.1016/j.ajem.2020.09.051
Abstrakt: Facing the novel coronavirus disease (COVID-19) pandemic, evidence to inform decision-making at all care levels is essential. Based on the results of a study by Petrilli et al., we have developed a calculator using patient data at admission to predict critical illness (intensive care, mechanical ventilation, hospice care, or death). We report a retrospective validation of the calculator on 145 consecutive patients admitted with COVID-19 to a single hospital in Israel. Despite considerable differences between the original and validation study populations, of 18 patients with critical illness, 17 were correctly identified (sensitivity: 94.4%, 95% CI, 72.7%-99.9%; specificity: 81.9%, 95% CI, 74.1%-88.2%). Of 127 patients with non-critical illness, 104 were correctly identified. Our results indicate that published knowledge can be reliably applied to assess patient risk, potentially reducing the cognitive burden on physicians, and helping policymakers better prepare for future needs.
Competing Interests: Declaration of Competing Interest AC, MZK, RM and GA are employed by Kahun Medical Ltd. All other authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2020. Published by Elsevier Inc.)
Databáze: MEDLINE
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