Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)

Abstract The objective of the study was to develop and validate a prediction model that identifies COVID-19 patients at risk of requiring oxygen support based on five parameters: C-reactive protein (CRP), hypertension, age, and neutrophil and lymphocyte counts (CHANeL). This retrospective cohort stu...

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Autores principales:	Eunyoung Emily Lee, Woochang Hwang, Kyoung-Ho Song, Jongtak Jung, Chang Kyung Kang, Jeong-Han Kim, Hong Sang Oh, Yu Min Kang, Eun Bong Lee, Bum Sik Chin, Woojeung Song, Nam Joong Kim, Jin Kyun Park
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/36c39848d50e4665ae92c6686d53c0a6
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spelling	oai:doaj.org-article:36c39848d50e4665ae92c6686d53c0a62021-12-02T17:45:21ZPredication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)10.1038/s41598-021-92418-22045-2322https://doaj.org/article/36c39848d50e4665ae92c6686d53c0a62021-06-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-92418-2https://doaj.org/toc/2045-2322Abstract The objective of the study was to develop and validate a prediction model that identifies COVID-19 patients at risk of requiring oxygen support based on five parameters: C-reactive protein (CRP), hypertension, age, and neutrophil and lymphocyte counts (CHANeL). This retrospective cohort study included 221 consecutive COVID-19 patients and the patients were randomly assigned randomly to a training set and a test set in a ratio of 1:1. Logistic regression, logistic LASSO regression, Random Forest, Support Vector Machine, and XGBoost analyses were performed based on age, hypertension status, serial CRP, and neutrophil and lymphocyte counts during the first 3 days of hospitalization. The ability of the model to predict oxygen requirement during hospitalization was tested. During hospitalization, 45 (41.8%) patients in the training set (n = 110) and 41 (36.9%) in the test set (n = 111) required supplementary oxygen support. The logistic LASSO regression model exhibited the highest AUC for the test set, with a sensitivity of 0.927 and a specificity of 0.814. An online risk calculator for oxygen requirement using CHANeL predictors was developed. “CHANeL” prediction models based on serial CRP, neutrophil, and lymphocyte counts during the first 3 days of hospitalization, along with age and hypertension status, provide a reliable estimate of the risk of supplement oxygen requirement among patients hospitalized with COVID-19.Eunyoung Emily LeeWoochang HwangKyoung-Ho SongJongtak JungChang Kyung KangJeong-Han KimHong Sang OhYu Min KangEun Bong LeeBum Sik ChinWoojeung SongNam Joong KimJin Kyun ParkNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Eunyoung Emily Lee Woochang Hwang Kyoung-Ho Song Jongtak Jung Chang Kyung Kang Jeong-Han Kim Hong Sang Oh Yu Min Kang Eun Bong Lee Bum Sik Chin Woojeung Song Nam Joong Kim Jin Kyun Park Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)
description	Abstract The objective of the study was to develop and validate a prediction model that identifies COVID-19 patients at risk of requiring oxygen support based on five parameters: C-reactive protein (CRP), hypertension, age, and neutrophil and lymphocyte counts (CHANeL). This retrospective cohort study included 221 consecutive COVID-19 patients and the patients were randomly assigned randomly to a training set and a test set in a ratio of 1:1. Logistic regression, logistic LASSO regression, Random Forest, Support Vector Machine, and XGBoost analyses were performed based on age, hypertension status, serial CRP, and neutrophil and lymphocyte counts during the first 3 days of hospitalization. The ability of the model to predict oxygen requirement during hospitalization was tested. During hospitalization, 45 (41.8%) patients in the training set (n = 110) and 41 (36.9%) in the test set (n = 111) required supplementary oxygen support. The logistic LASSO regression model exhibited the highest AUC for the test set, with a sensitivity of 0.927 and a specificity of 0.814. An online risk calculator for oxygen requirement using CHANeL predictors was developed. “CHANeL” prediction models based on serial CRP, neutrophil, and lymphocyte counts during the first 3 days of hospitalization, along with age and hypertension status, provide a reliable estimate of the risk of supplement oxygen requirement among patients hospitalized with COVID-19.
format	article
author	Eunyoung Emily Lee Woochang Hwang Kyoung-Ho Song Jongtak Jung Chang Kyung Kang Jeong-Han Kim Hong Sang Oh Yu Min Kang Eun Bong Lee Bum Sik Chin Woojeung Song Nam Joong Kim Jin Kyun Park
author_facet	Eunyoung Emily Lee Woochang Hwang Kyoung-Ho Song Jongtak Jung Chang Kyung Kang Jeong-Han Kim Hong Sang Oh Yu Min Kang Eun Bong Lee Bum Sik Chin Woojeung Song Nam Joong Kim Jin Kyun Park
author_sort	Eunyoung Emily Lee
title	Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)
title_short	Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)
title_full	Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)
title_fullStr	Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)
title_full_unstemmed	Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)
title_sort	predication of oxygen requirement in covid-19 patients using dynamic change of inflammatory markers: crp, hypertension, age, neutrophil and lymphocyte (chanel)
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/36c39848d50e4665ae92c6686d53c0a6
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Predication of oxygen requirement in COVID-19 patients using dynamic change of inflammatory markers: CRP, hypertension, age, neutrophil and lymphocyte (CHANeL)

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