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Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019
BACKGROUND: Uncertainty surrounding COVID-19 regarding rapid progression to acute respiratory distress syndrome and unusual clinical characteristics make discharge from a monitored setting challenging. A clinical risk score to predict 14-day occurrence of hypoxia, ICU admission, and death is unavail...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer International Publishing
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713904/ https://www.ncbi.nlm.nih.gov/pubmed/33274414 http://dx.doi.org/10.1007/s11606-020-06353-5 |
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author | Levine, David M. Lipsitz, Stuart R. Co, Zoe Song, Wenyu Dykes, Patricia C. Samal, Lipika |
author_facet | Levine, David M. Lipsitz, Stuart R. Co, Zoe Song, Wenyu Dykes, Patricia C. Samal, Lipika |
author_sort | Levine, David M. |
collection | PubMed |
description | BACKGROUND: Uncertainty surrounding COVID-19 regarding rapid progression to acute respiratory distress syndrome and unusual clinical characteristics make discharge from a monitored setting challenging. A clinical risk score to predict 14-day occurrence of hypoxia, ICU admission, and death is unavailable. OBJECTIVE: Derive and validate a risk score to predict suitability for discharge from a monitored setting among an early cohort of patients with COVID-19. DESIGN: Model derivation and validation in a retrospective cohort. We built a manual forward stepwise logistic regression model to identify variables associated with suitability for discharge and assigned points to each variable. Event-free patients were included after at least 14 days of follow-up. PARTICIPANTS: All adult patients with a COVID-19 diagnosis between March 1, 2020, and April 12, 2020, in 10 hospitals in Massachusetts, USA. MAIN MEASURES: Fourteen-day composite predicting hypoxia, ICU admission, and death. We calculated a risk score for each patient as a predictor of suitability for discharge evaluated by area under the curve. KEY RESULTS: Of 2059 patients with COVID-19, 1326 met inclusion. The 1014-patient training cohort had a mean age of 58 years, was 56% female, and 65% had at least one comorbidity. A total of 255 (25%) patients were suitable for discharge. Variables associated with suitability for discharge were age, oxygen saturation, and albumin level, yielding a risk score between 0 and 55. At a cut point of 30, the score had a sensitivity of 83% and specificity of 82%. The respective c-statistic for the derivation and validation cohorts were 0.8939 (95% CI, 0.8687 to 0.9192) and 0.8685 (95% CI, 0.8095 to 0.9275). The score performed similarly for inpatients and emergency department patients. CONCLUSIONS: A 3-item risk score for patients with COVID-19 consisting of age, oxygen saturation, and an acute phase reactant (albumin) using point of care data predicts suitability for discharge and may optimize scarce resources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-020-06353-5. |
format | Online Article Text |
id | pubmed-7713904 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer International Publishing |
record_format | MEDLINE/PubMed |
spelling | pubmed-77139042020-12-04 Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 Levine, David M. Lipsitz, Stuart R. Co, Zoe Song, Wenyu Dykes, Patricia C. Samal, Lipika J Gen Intern Med Original Research BACKGROUND: Uncertainty surrounding COVID-19 regarding rapid progression to acute respiratory distress syndrome and unusual clinical characteristics make discharge from a monitored setting challenging. A clinical risk score to predict 14-day occurrence of hypoxia, ICU admission, and death is unavailable. OBJECTIVE: Derive and validate a risk score to predict suitability for discharge from a monitored setting among an early cohort of patients with COVID-19. DESIGN: Model derivation and validation in a retrospective cohort. We built a manual forward stepwise logistic regression model to identify variables associated with suitability for discharge and assigned points to each variable. Event-free patients were included after at least 14 days of follow-up. PARTICIPANTS: All adult patients with a COVID-19 diagnosis between March 1, 2020, and April 12, 2020, in 10 hospitals in Massachusetts, USA. MAIN MEASURES: Fourteen-day composite predicting hypoxia, ICU admission, and death. We calculated a risk score for each patient as a predictor of suitability for discharge evaluated by area under the curve. KEY RESULTS: Of 2059 patients with COVID-19, 1326 met inclusion. The 1014-patient training cohort had a mean age of 58 years, was 56% female, and 65% had at least one comorbidity. A total of 255 (25%) patients were suitable for discharge. Variables associated with suitability for discharge were age, oxygen saturation, and albumin level, yielding a risk score between 0 and 55. At a cut point of 30, the score had a sensitivity of 83% and specificity of 82%. The respective c-statistic for the derivation and validation cohorts were 0.8939 (95% CI, 0.8687 to 0.9192) and 0.8685 (95% CI, 0.8095 to 0.9275). The score performed similarly for inpatients and emergency department patients. CONCLUSIONS: A 3-item risk score for patients with COVID-19 consisting of age, oxygen saturation, and an acute phase reactant (albumin) using point of care data predicts suitability for discharge and may optimize scarce resources. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11606-020-06353-5. Springer International Publishing 2020-12-03 2021-03 /pmc/articles/PMC7713904/ /pubmed/33274414 http://dx.doi.org/10.1007/s11606-020-06353-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Original Research Levine, David M. Lipsitz, Stuart R. Co, Zoe Song, Wenyu Dykes, Patricia C. Samal, Lipika Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 |
title | Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 |
title_full | Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 |
title_fullStr | Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 |
title_full_unstemmed | Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 |
title_short | Derivation of a Clinical Risk Score to Predict 14-Day Occurrence of Hypoxia, ICU Admission, and Death Among Patients with Coronavirus Disease 2019 |
title_sort | derivation of a clinical risk score to predict 14-day occurrence of hypoxia, icu admission, and death among patients with coronavirus disease 2019 |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7713904/ https://www.ncbi.nlm.nih.gov/pubmed/33274414 http://dx.doi.org/10.1007/s11606-020-06353-5 |
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