tetano
Editor, Senior Moderator
Ann Med
. 2020 Sep 30;1-31.
doi: 10.1080/07853890.2020.1828616. Online ahead of print.
External Validation of a Clinical Risk Score to Predict Hospital Admission and In-Hospital Mortality in COVID-19 Patients
Alexandra Halalau[SUP] 1 2 [/SUP], Zaid Imam[SUP] 1 [/SUP], Patrick Karabon[SUP] 2 [/SUP], Nikhil Mankuzhy[SUP] 2 [/SUP], Aciel Shaheen[SUP] 1 [/SUP], John Tu[SUP] 1 2 3 [/SUP], Christopher Carpenter[SUP] 1 2 4 [/SUP]
Affiliations
Abstract
Background: 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-center (8 hospital) cohort at Beaumont Health, Michigan, USA, reporting on COVID-19 patients diagnosed between March 1 and April 1, 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 < 0.0001). Similarly, Yellow Scores (OR: 4.73) and Red Scores (OR: 13.3) had significantly higher odds of in-hospital mortality than Green Scores (both P < 0.0001). The cross-validated C-Statistics for the external validation cohort showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)).Conclusions: The COVID-19 Risk of Complications Score predicts the need for hospital admission and in-hospital mortality patients with COVID-19. Key Points:Can an electronic health record generated risk score predict the risk of hospital admission and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19)?In both validation cohorts of 2,025 and 1,290 COVID-19, the cross-validated C-Statistics showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)), respectively.The COVID-19 Risk of Complications Score may help predict the need for hospital admission if a patient contracts SARS-CoV-2 infection and in-hospital mortality for a hospitalized patient with COVID-19.
. 2020 Sep 30;1-31.
doi: 10.1080/07853890.2020.1828616. Online ahead of print.
External Validation of a Clinical Risk Score to Predict Hospital Admission and In-Hospital Mortality in COVID-19 Patients
Alexandra Halalau[SUP] 1 2 [/SUP], Zaid Imam[SUP] 1 [/SUP], Patrick Karabon[SUP] 2 [/SUP], Nikhil Mankuzhy[SUP] 2 [/SUP], Aciel Shaheen[SUP] 1 [/SUP], John Tu[SUP] 1 2 3 [/SUP], Christopher Carpenter[SUP] 1 2 4 [/SUP]
Affiliations
- PMID: 32997542
- DOI: 10.1080/07853890.2020.1828616
Abstract
Background: 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-center (8 hospital) cohort at Beaumont Health, Michigan, USA, reporting on COVID-19 patients diagnosed between March 1 and April 1, 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 < 0.0001). Similarly, Yellow Scores (OR: 4.73) and Red Scores (OR: 13.3) had significantly higher odds of in-hospital mortality than Green Scores (both P < 0.0001). The cross-validated C-Statistics for the external validation cohort showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)).Conclusions: The COVID-19 Risk of Complications Score predicts the need for hospital admission and in-hospital mortality patients with COVID-19. Key Points:Can an electronic health record generated risk score predict the risk of hospital admission and in-hospital mortality in patients diagnosed with coronavirus disease 2019 (COVID-19)?In both validation cohorts of 2,025 and 1,290 COVID-19, the cross-validated C-Statistics showed good discrimination for both hospital admission (C = 0.79 (95% CI: 0.77-0.81)) and in-hospital mortality (C = 0.75 (95% CI: 0.71-0.78)), respectively.The COVID-19 Risk of Complications Score may help predict the need for hospital admission if a patient contracts SARS-CoV-2 infection and in-hospital mortality for a hospitalized patient with COVID-19.