Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission.
As SARS-CoV-2 infections continue to cause hospital admissions around the world, there is a continued need to accurately assess those at highest risk of death to guide resource use and clinical management. The ISARIC 4C mortality score provides mortality risk prediction at admission to hospital base...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0274158 |
| _version_ | 1797774509155024896 |
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| author | Tim Crocker-Buque Jonathan Myles Adam Brentnall Rhian Gabe Stephen Duffy Sophie Williams Simon Tiberi |
| author_facet | Tim Crocker-Buque Jonathan Myles Adam Brentnall Rhian Gabe Stephen Duffy Sophie Williams Simon Tiberi |
| author_sort | Tim Crocker-Buque |
| collection | DOAJ |
| description | As SARS-CoV-2 infections continue to cause hospital admissions around the world, there is a continued need to accurately assess those at highest risk of death to guide resource use and clinical management. The ISARIC 4C mortality score provides mortality risk prediction at admission to hospital based on demographic and physiological parameters. Here we evaluate dynamic use of the 4C score at different points following admission. Score components were extracted for 6,373 patients admitted to Barts Health NHS Trust hospitals between 1st August 2020 and 19th July 2021 and total score calculated every 48 hours for 28 days. Area under the receiver operating characteristic (AUC) statistics were used to evaluate discrimination of the score at admission and subsequent inpatient days. Patients who were still in hospital at day 6 were more likely to die if they had a higher score at day 6 than others also still in hospital who had the same score at admission. Discrimination of dynamic scoring in those still in hospital was superior with the area under the curve 0.71 (95% CI 0.69-0.74) at admission and 0.82 (0.80-0.85) by day 8. Clinically useful changes in the dynamic parts of the score are unlikely to be associated with subject-level measurements. Dynamic use of the ISARIC 4C score is likely to provide accurate and timely information on mortality risk during a patient's hospital admission. |
| first_indexed | 2024-03-12T22:22:09Z |
| format | Article |
| id | doaj.art-ced50fb4a8be4f20806c18816a499984 |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-03-12T22:22:09Z |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-ced50fb4a8be4f20806c18816a4999842023-07-23T05:31:28ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-011710e027415810.1371/journal.pone.0274158Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission.Tim Crocker-BuqueJonathan MylesAdam BrentnallRhian GabeStephen DuffySophie WilliamsSimon TiberiAs SARS-CoV-2 infections continue to cause hospital admissions around the world, there is a continued need to accurately assess those at highest risk of death to guide resource use and clinical management. The ISARIC 4C mortality score provides mortality risk prediction at admission to hospital based on demographic and physiological parameters. Here we evaluate dynamic use of the 4C score at different points following admission. Score components were extracted for 6,373 patients admitted to Barts Health NHS Trust hospitals between 1st August 2020 and 19th July 2021 and total score calculated every 48 hours for 28 days. Area under the receiver operating characteristic (AUC) statistics were used to evaluate discrimination of the score at admission and subsequent inpatient days. Patients who were still in hospital at day 6 were more likely to die if they had a higher score at day 6 than others also still in hospital who had the same score at admission. Discrimination of dynamic scoring in those still in hospital was superior with the area under the curve 0.71 (95% CI 0.69-0.74) at admission and 0.82 (0.80-0.85) by day 8. Clinically useful changes in the dynamic parts of the score are unlikely to be associated with subject-level measurements. Dynamic use of the ISARIC 4C score is likely to provide accurate and timely information on mortality risk during a patient's hospital admission.https://doi.org/10.1371/journal.pone.0274158 |
| spellingShingle | Tim Crocker-Buque Jonathan Myles Adam Brentnall Rhian Gabe Stephen Duffy Sophie Williams Simon Tiberi Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. PLoS ONE |
| title | Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. |
| title_full | Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. |
| title_fullStr | Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. |
| title_full_unstemmed | Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. |
| title_short | Using ISARIC 4C mortality score to predict dynamic changes in mortality risk in COVID-19 patients during hospital admission. |
| title_sort | using isaric 4c mortality score to predict dynamic changes in mortality risk in covid 19 patients during hospital admission |
| url | https://doi.org/10.1371/journal.pone.0274158 |
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