External validation of a clinical risk score to predict hospital admission and in-hospital mortality in COVID-19 patients
| Autor: | Alexandra Halalau, Zaid Imam, Patrick Karabon, Nikhil Mankuzhy, Aciel Shaheen, John Tu, Christopher Carpenter |
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| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | Annals of Medicine, Vol 53, Iss 1, Pp 78-86 (2021) |
| Druh dokumentu: | article |
| ISSN: | 07853890 1365-2060 0785-3890 |
| DOI: | 10.1080/07853890.2020.1828616 |
| Popis: | AbstractBackground Identification of patients with novel coronavirus disease 2019 (COVID-19) requiring hospital admission or at high-risk of in-hospital mortality is essential to guide patient triage and to provide timely treatment for higher risk hospitalized patients.Methods A retrospective multi-centre (8 hospital) cohort at Beaumont Health, Michigan, USA, reporting on COVID-19 patients diagnosed between 1 March and 1 April 2020 was used for score validation. The COVID-19 Risk of Complications Score was automatically computed by the EHR. Multivariate logistic regression models were built to predict hospital admission and in-hospital mortality using individual variables constituting the score. Validation was performed using both discrimination and calibration.Results Compared to Green scores, Yellow Scores (OR: 5.72) and Red Scores (OR: 19.1) had significantly higher odds of admission (both p |
| Databáze: | Directory of Open Access Journals |
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