Development and validation of a knowledge-driven risk calculator for critical illness in COVID-19 patients
Copyright © 2020. Published by Elsevier Inc..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2021 |
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| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:39 |
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| Enthalten in: |
The American journal of emergency medicine - 39(2021) vom: 03. Jan., Seite 143-145 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Cahan, Amos [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 22.12.2020 Date Revised 10.01.2021 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.ajem.2020.09.051 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM316091138 |
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| 500 | |a Date Revised 10.01.2021 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2020. Published by Elsevier Inc. | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Validation Study | |
| 700 | 1 | |a Gottesman, Tamar |e verfasserin |4 aut | |
| 700 | 1 | |a Katz, Michal Tzuchman |e verfasserin |4 aut | |
| 700 | 1 | |a Masad, Roee |e verfasserin |4 aut | |
| 700 | 1 | |a Azulay, Gal |e verfasserin |4 aut | |
| 700 | 1 | |a Dicker, Dror |e verfasserin |4 aut | |
| 700 | 1 | |a Zeidman, Aliza |e verfasserin |4 aut | |
| 700 | 1 | |a Berkov, Evgeny |e verfasserin |4 aut | |
| 700 | 1 | |a Tadmor, Boaz |e verfasserin |4 aut | |
| 700 | 1 | |a Lev, Shaul |e verfasserin |4 aut | |
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