ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019

Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Ma...
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Autor*in:	Zhihong Weng [verfasserIn] Qiaosen Chen [verfasserIn] Sumeng Li [verfasserIn] Huadong Li [verfasserIn] Qian Zhang [verfasserIn] Sihong Lu [verfasserIn] Li Wu [verfasserIn] Leiqun Xiong [verfasserIn] Bobin Mi [verfasserIn] Di Liu [verfasserIn] Mengji Lu [verfasserIn] Dongliang Yang [verfasserIn] Hongbo Jiang [verfasserIn] Shaoping Zheng [verfasserIn] Xin Zheng [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2020

Schlagwörter:	SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor

Übergeordnetes Werk:	In: Journal of Translational Medicine - BMC, 2003, 18(2020), 1, Seite 10
Übergeordnetes Werk:	volume:18 ; year:2020 ; number:1 ; pages:10

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1186/s12967-020-02505-7

Katalog-ID:	DOAJ047453141

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520			\|a Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management.
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allfields	10.1186/s12967-020-02505-7 doi (DE-627)DOAJ047453141 (DE-599)DOAJ735fa127556a4f7cbd8ce9c9456bc3f8 DE-627 ger DE-627 rakwb eng Zhihong Weng verfasserin aut ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management. SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor Medicine R Qiaosen Chen verfasserin aut Sumeng Li verfasserin aut Huadong Li verfasserin aut Qian Zhang verfasserin aut Sihong Lu verfasserin aut Li Wu verfasserin aut Leiqun Xiong verfasserin aut Bobin Mi verfasserin aut Di Liu verfasserin aut Mengji Lu verfasserin aut Dongliang Yang verfasserin aut Hongbo Jiang verfasserin aut Shaoping Zheng verfasserin aut Xin Zheng verfasserin aut In Journal of Translational Medicine BMC, 2003 18(2020), 1, Seite 10 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:18 year:2020 number:1 pages:10 https://doi.org/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/article/735fa127556a4f7cbd8ce9c9456bc3f8 kostenfrei http://link.springer.com/article/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2020 1 10
spelling	10.1186/s12967-020-02505-7 doi (DE-627)DOAJ047453141 (DE-599)DOAJ735fa127556a4f7cbd8ce9c9456bc3f8 DE-627 ger DE-627 rakwb eng Zhihong Weng verfasserin aut ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management. SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor Medicine R Qiaosen Chen verfasserin aut Sumeng Li verfasserin aut Huadong Li verfasserin aut Qian Zhang verfasserin aut Sihong Lu verfasserin aut Li Wu verfasserin aut Leiqun Xiong verfasserin aut Bobin Mi verfasserin aut Di Liu verfasserin aut Mengji Lu verfasserin aut Dongliang Yang verfasserin aut Hongbo Jiang verfasserin aut Shaoping Zheng verfasserin aut Xin Zheng verfasserin aut In Journal of Translational Medicine BMC, 2003 18(2020), 1, Seite 10 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:18 year:2020 number:1 pages:10 https://doi.org/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/article/735fa127556a4f7cbd8ce9c9456bc3f8 kostenfrei http://link.springer.com/article/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2020 1 10
allfields_unstemmed	10.1186/s12967-020-02505-7 doi (DE-627)DOAJ047453141 (DE-599)DOAJ735fa127556a4f7cbd8ce9c9456bc3f8 DE-627 ger DE-627 rakwb eng Zhihong Weng verfasserin aut ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management. SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor Medicine R Qiaosen Chen verfasserin aut Sumeng Li verfasserin aut Huadong Li verfasserin aut Qian Zhang verfasserin aut Sihong Lu verfasserin aut Li Wu verfasserin aut Leiqun Xiong verfasserin aut Bobin Mi verfasserin aut Di Liu verfasserin aut Mengji Lu verfasserin aut Dongliang Yang verfasserin aut Hongbo Jiang verfasserin aut Shaoping Zheng verfasserin aut Xin Zheng verfasserin aut In Journal of Translational Medicine BMC, 2003 18(2020), 1, Seite 10 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:18 year:2020 number:1 pages:10 https://doi.org/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/article/735fa127556a4f7cbd8ce9c9456bc3f8 kostenfrei http://link.springer.com/article/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2020 1 10
allfieldsGer	10.1186/s12967-020-02505-7 doi (DE-627)DOAJ047453141 (DE-599)DOAJ735fa127556a4f7cbd8ce9c9456bc3f8 DE-627 ger DE-627 rakwb eng Zhihong Weng verfasserin aut ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management. SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor Medicine R Qiaosen Chen verfasserin aut Sumeng Li verfasserin aut Huadong Li verfasserin aut Qian Zhang verfasserin aut Sihong Lu verfasserin aut Li Wu verfasserin aut Leiqun Xiong verfasserin aut Bobin Mi verfasserin aut Di Liu verfasserin aut Mengji Lu verfasserin aut Dongliang Yang verfasserin aut Hongbo Jiang verfasserin aut Shaoping Zheng verfasserin aut Xin Zheng verfasserin aut In Journal of Translational Medicine BMC, 2003 18(2020), 1, Seite 10 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:18 year:2020 number:1 pages:10 https://doi.org/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/article/735fa127556a4f7cbd8ce9c9456bc3f8 kostenfrei http://link.springer.com/article/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2020 1 10
allfieldsSound	10.1186/s12967-020-02505-7 doi (DE-627)DOAJ047453141 (DE-599)DOAJ735fa127556a4f7cbd8ce9c9456bc3f8 DE-627 ger DE-627 rakwb eng Zhihong Weng verfasserin aut ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019 2020 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management. SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor Medicine R Qiaosen Chen verfasserin aut Sumeng Li verfasserin aut Huadong Li verfasserin aut Qian Zhang verfasserin aut Sihong Lu verfasserin aut Li Wu verfasserin aut Leiqun Xiong verfasserin aut Bobin Mi verfasserin aut Di Liu verfasserin aut Mengji Lu verfasserin aut Dongliang Yang verfasserin aut Hongbo Jiang verfasserin aut Shaoping Zheng verfasserin aut Xin Zheng verfasserin aut In Journal of Translational Medicine BMC, 2003 18(2020), 1, Seite 10 (DE-627)369084136 (DE-600)2118570-0 14795876 nnns volume:18 year:2020 number:1 pages:10 https://doi.org/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/article/735fa127556a4f7cbd8ce9c9456bc3f8 kostenfrei http://link.springer.com/article/10.1186/s12967-020-02505-7 kostenfrei https://doaj.org/toc/1479-5876 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2009 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2055 GBV_ILN_2111 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 18 2020 1 10
language	English
source	In Journal of Translational Medicine 18(2020), 1, Seite 10 volume:18 year:2020 number:1 pages:10
sourceStr	In Journal of Translational Medicine 18(2020), 1, Seite 10 volume:18 year:2020 number:1 pages:10
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor Medicine R
isfreeaccess_bool	true
container_title	Journal of Translational Medicine
authorswithroles_txt_mv	Zhihong Weng @@aut@@ Qiaosen Chen @@aut@@ Sumeng Li @@aut@@ Huadong Li @@aut@@ Qian Zhang @@aut@@ Sihong Lu @@aut@@ Li Wu @@aut@@ Leiqun Xiong @@aut@@ Bobin Mi @@aut@@ Di Liu @@aut@@ Mengji Lu @@aut@@ Dongliang Yang @@aut@@ Hongbo Jiang @@aut@@ Shaoping Zheng @@aut@@ Xin Zheng @@aut@@
publishDateDaySort_date	2020-01-01T00:00:00Z
hierarchy_top_id	369084136
id	DOAJ047453141
language_de	englisch
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We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. 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author	Zhihong Weng
spellingShingle	Zhihong Weng misc SARS-Cov-2 misc COVID-19 misc Nomogram misc Mortality misc Risk factor misc Medicine misc R ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019
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topic_title	ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019 SARS-Cov-2 COVID-19 Nomogram Mortality Risk factor
topic	misc SARS-Cov-2 misc COVID-19 misc Nomogram misc Mortality misc Risk factor misc Medicine misc R
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title	ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019
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title_full	ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019
author_sort	Zhihong Weng
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author_browse	Zhihong Weng Qiaosen Chen Sumeng Li Huadong Li Qian Zhang Sihong Lu Li Wu Leiqun Xiong Bobin Mi Di Liu Mengji Lu Dongliang Yang Hongbo Jiang Shaoping Zheng Xin Zheng
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doi_str_mv	10.1186/s12967-020-02505-7
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title_sort	andc: an early warning score to predict mortality risk for patients with coronavirus disease 2019
title_auth	ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019
abstract	Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management.
abstractGer	Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management.
abstract_unstemmed	Abstract Background Patients with severe Coronavirus Disease 2019 (COVID-19) will progress rapidly to acute respiratory failure or death. We aimed to develop a quantitative tool for early predicting mortality risk of patients with COVID-19. Methods 301 patients with confirmed COVID-19 admitted to Main District and Tumor Center of the Union Hospital of Huazhong University of Science and Technology (Wuhan, China) between January 1, 2020 to February 15, 2020 were enrolled in this retrospective two-centers study. Data on patient demographic characteristics, laboratory findings and clinical outcomes was analyzed. A nomogram was constructed to predict the death probability of COVID-19 patients. Results Age, neutrophil-to-lymphocyte ratio, d-dimer and C-reactive protein obtained on admission were identified as predictors of mortality for COVID-19 patients by LASSO. The nomogram demonstrated good calibration and discrimination with the area under the curve (AUC) of 0.921 and 0.975 for the derivation and validation cohort, respectively. An integrated score (named ANDC) with its corresponding death probability was derived. Using ANDC cut-off values of 59 and 101, COVID-19 patients were classified into three subgroups. The death probability of low risk group (ANDC < 59) was less than 5%, moderate risk group (59 ≤ ANDC ≤ 101) was 5% to 50%, and high risk group (ANDC < 101) was more than 50%, respectively. Conclusion The prognostic nomogram exhibited good discrimination power in early identification of COVID-19 patients with high mortality risk, and ANDC score may help physicians to optimize patient stratification management.
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title_short	ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019
url	https://doi.org/10.1186/s12967-020-02505-7 https://doaj.org/article/735fa127556a4f7cbd8ce9c9456bc3f8 http://link.springer.com/article/10.1186/s12967-020-02505-7 https://doaj.org/toc/1479-5876
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author2	Qiaosen Chen Sumeng Li Huadong Li Qian Zhang Sihong Lu Li Wu Leiqun Xiong Bobin Mi Di Liu Mengji Lu Dongliang Yang Hongbo Jiang Shaoping Zheng Xin Zheng
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up_date	2024-07-04T01:22:32.221Z
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ANDC: an early warning score to predict mortality risk for patients with Coronavirus Disease 2019

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