tetano
Editor, Senior Moderator
Am J Emerg Med
. 2020 Sep 23;S0735-6757(20)30848-2.
doi: 10.1016/j.ajem.2020.09.051. Online ahead of print.
Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients
Amos Cahan[SUP] 1 [/SUP], Tamar Gottesman[SUP] 2 [/SUP], Michal Tzuchman Katz[SUP] 3 [/SUP], Roee Masad[SUP] 3 [/SUP], Gal Azulay[SUP] 3 [/SUP], Dror Dicker[SUP] 4 [/SUP], Aliza Zeidman[SUP] 5 [/SUP], Evgeny Berkov[SUP] 6 [/SUP], Boaz Tadmor[SUP] 7 [/SUP], Shaul Lev[SUP] 8 [/SUP]
Affiliations
Abstract
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.
. 2020 Sep 23;S0735-6757(20)30848-2.
doi: 10.1016/j.ajem.2020.09.051. Online ahead of print.
Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients
Amos Cahan[SUP] 1 [/SUP], Tamar Gottesman[SUP] 2 [/SUP], Michal Tzuchman Katz[SUP] 3 [/SUP], Roee Masad[SUP] 3 [/SUP], Gal Azulay[SUP] 3 [/SUP], Dror Dicker[SUP] 4 [/SUP], Aliza Zeidman[SUP] 5 [/SUP], Evgeny Berkov[SUP] 6 [/SUP], Boaz Tadmor[SUP] 7 [/SUP], Shaul Lev[SUP] 8 [/SUP]
Affiliations
- PMID: 33039212
- PMCID: PMC7510415
- DOI: 10.1016/j.ajem.2020.09.051
Abstract
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.