TY - JOUR
T1 - Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients
AU - Cahan, Amos
AU - Gottesman, Tamar
AU - Katz, Michal Tzuchman
AU - Masad, Roee
AU - Azulay, Gal
AU - Dicker, Dror
AU - Zeidman, Aliza
AU - Berkov, Evgeny
AU - Tadmor, Boaz
AU - Lev, Shaul
N1 - Publisher Copyright:
© 2020
PY - 2021/1
Y1 - 2021/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85092227465&partnerID=8YFLogxK
U2 - 10.1016/j.ajem.2020.09.051
DO - 10.1016/j.ajem.2020.09.051
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C2 - 33039212
AN - SCOPUS:85092227465
SN - 0735-6757
VL - 39
SP - 143
EP - 145
JO - American Journal of Emergency Medicine
JF - American Journal of Emergency Medicine
ER -