A predictive model for disease progression in non-severely ill patients with coronavirus disease 2019

doi:10.1183/13993003.01234-2020

Comment

. 2020 Jul 16;56(1):2001234.

doi: 10.1183/13993003.01234-2020. Print 2020 Jul.

A predictive model for disease progression in non-severely ill patients with coronavirus disease 2019

Mengyao Ji^{1

2}, Lei Yuan^{3

2}, Wei Shen^{4

5

2}, Junwei Lv^{4

5}, Yong Li^{6

2}, Jia Chen^{4

5}, Chaonan Zhu^{4

5}, Bo Liu^{4

5}, Zhenzhen Liang⁷, Qiang Lin^{4

5}, Wenjie Xie⁸, Ming Li³, Zhifan Chen⁹, Xuefang Lu¹⁰, YiJuan Ding¹, Ping An¹, Sheng Zhu^{4

5}, Mengting Gao³, Hao Ni^{4

5}, Lanhua Hu¹⁰, Guanglei Shi^{4

5}, Lei Shi^{4

5

11}, Weiguo Dong^{1

11}

Affiliations

¹ Dept of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
² Mengyao Ji, Lei Yuan, Wei Shen and Yong Li contributed equally to this paper.
³ Dept of Information Center, Renmin Hospital of Wuhan University, Wuhan China.
⁴ Shanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai, China.
⁵ Hangzhou YITU Healthcare Technology Co., Ltd, Hangzhou, China.
⁶ Dept of Radiology, Suining Central Hospital, Suining, China.
⁷ Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
⁸ Dept of Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, China.
⁹ Dept of Radiology, Affiliated Hospital of Chengdu University, Chengdu, China.
¹⁰ Dept of Radiology, Renmin Hospital of Wuhan University, Wuhan, China.
¹¹ Weiguo Dong and Lei Shi contributed equally to this article as lead authors and supervised the work.

PMID: 32430433
PMCID: PMC7241108
DOI: 10.1183/13993003.01234-2020

Comment

A predictive model for disease progression in non-severely ill patients with coronavirus disease 2019

Mengyao Ji et al. Eur Respir J. 2020.

. 2020 Jul 16;56(1):2001234.

doi: 10.1183/13993003.01234-2020. Print 2020 Jul.

Authors

Affiliations

¹ Dept of Gastroenterology, Renmin Hospital of Wuhan University, Wuhan, China.
² Mengyao Ji, Lei Yuan, Wei Shen and Yong Li contributed equally to this paper.
³ Dept of Information Center, Renmin Hospital of Wuhan University, Wuhan China.
⁴ Shanghai Key Laboratory of Artificial Intelligence for Medical Image and Knowledge Graph, Shanghai, China.
⁵ Hangzhou YITU Healthcare Technology Co., Ltd, Hangzhou, China.
⁶ Dept of Radiology, Suining Central Hospital, Suining, China.
⁷ Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
⁸ Dept of Critical Care Medicine, Renmin Hospital of Wuhan University, Wuhan, China.
⁹ Dept of Radiology, Affiliated Hospital of Chengdu University, Chengdu, China.
¹⁰ Dept of Radiology, Renmin Hospital of Wuhan University, Wuhan, China.
¹¹ Weiguo Dong and Lei Shi contributed equally to this article as lead authors and supervised the work.

PMID: 32430433
PMCID: PMC7241108
DOI: 10.1183/13993003.01234-2020

Abstract

A predictive model for COVID-19 https://bit.ly/2WHiEkJ

PubMed Disclaimer

Conflict of interest statement

Conflict of interest: M. Ji has nothing to disclose. Conflict of interest: L. Yuan has nothing to disclose. Conflict of interest: W. Shen has nothing to disclose. Conflict of interest: J. Lv has nothing to disclose. Conflict of interest: Y. Li has nothing to disclose. Conflict of interest: J. Chen has nothing to disclose. Conflict of interest: C. Zhu has nothing to disclose. Conflict of interest: B. Liu has nothing to disclose. Conflict of interest: Z. Liang has nothing to disclose. Conflict of interest: Q. Lin has nothing to disclose. Conflict of interest: W. Xie has nothing to disclose. Conflict of interest: M. Li has nothing to disclose. Conflict of interest: Z. Chen has nothing to disclose. Conflict of interest: X. Lu has nothing to disclose. Conflict of interest: Y. Ding has nothing to disclose. Conflict of interest: P. An has nothing to disclose. Conflict of interest: S. Zhu has nothing to disclose. Conflict of interest: M. Gao has nothing to disclose. Conflict of interest: H. Ni has nothing to disclose. Conflict of interest: L. Hu has nothing to disclose. Conflict of interest: G. Shi has nothing to disclose. Conflict of interest: L. Shi has nothing to disclose. Conflict of interest: W. Dong has nothing to disclose.

Comment on

Clinical Characteristics of Coronavirus Disease 2019 in China.
Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, Liu L, Shan H, Lei CL, Hui DSC, Du B, Li LJ, Zeng G, Yuen KY, Chen RC, Tang CL, Wang T, Chen PY, Xiang J, Li SY, Wang JL, Liang ZJ, Peng YX, Wei L, Liu Y, Hu YH, Peng P, Wang JM, Liu JY, Chen Z, Li G, Zheng ZJ, Qiu SQ, Luo J, Ye CJ, Zhu SY, Zhong NS; China Medical Treatment Expert Group for Covid-19. Guan WJ, et al. N Engl J Med. 2020 Apr 30;382(18):1708-1720. doi: 10.1056/NEJMoa2002032. Epub 2020 Feb 28. N Engl J Med. 2020. PMID: 32109013 Free PMC article.

Cited by

Artificial intelligence-based approaches for COVID-19 patient management.
Lan L, Sun W, Xu D, Yu M, Xiao F, Hu H, Xu H, Wang X. Lan L, et al. Intell Med. 2021 May;1(1):10-15. doi: 10.1016/j.imed.2021.05.005. Epub 2021 Jun 10. Intell Med. 2021. PMID: 34447600 Free PMC article. Review.
Predicting omicron pneumonia severity and outcome: a single-center study in Hangzhou, China.
Xu J, Cao Z, Miao C, Zhang M, Xu X. Xu J, et al. Front Med (Lausanne). 2023 May 26;10:1192376. doi: 10.3389/fmed.2023.1192376. eCollection 2023. Front Med (Lausanne). 2023. PMID: 37305146 Free PMC article.
Identification of Multisystem Inflammatory Syndrome in Children Classes and Development of Hyperinflammation Score in Pediatric COVID-19.
Totapally BR, Nadiger M, Hassor S, Laufer M, Etinger V, Ramos O, Biehler J, Meyer K, Melnick S. Totapally BR, et al. J Pediatr Intensive Care. 2021 Jun 19;12(2):137-147. doi: 10.1055/s-0041-1730932. eCollection 2023 Jun. J Pediatr Intensive Care. 2021. PMID: 37082465 Free PMC article.
Artificial intelligence computed tomography helps evaluate the severity of COVID-19 patients: A retrospective study.
Han Y, Mu SC, Zhang HD, Wei W, Wu XY, Jin CY, Gu GR, Xie BJ, Tong CY. Han Y, et al. World J Emerg Med. 2022;13(2):91-97. doi: 10.5847/wjem.j.1920-8642.2022.026. World J Emerg Med. 2022. PMID: 35237361 Free PMC article.
Obese COVID-19 patients show more severe pneumonia lesions on CT chest imaging.
Luo X MD, Jiaerken Y MD, Shen Z MD, Wang Q MD, Liu B PhD, Zhou H MD, Zheng H MD, Li Y MD, Gao Y MD, He S MD, Ji W MD, Liu Y MD, Ma J MD, Mao L MD, Wang X MD, Wang M MD, Su M MD, Huang P PhD, Shi L MD, Zhang M MD. Luo X MD, et al. Diabetes Obes Metab. 2021 Jan;23(1):290-293. doi: 10.1111/dom.14194. Epub 2020 Nov 19. Diabetes Obes Metab. 2021. PMID: 32945051 Free PMC article. No abstract available.

See all "Cited by" articles

References

1. http://2019ncov.chinacdc.cn/2019-nCoV/ Chinese Center for Disease Control and Prevention. Distribution of Covid-19. - PMC - PubMed
1. Guan WJ, Ni ZY, Hu Y, et al. . Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020; 382: 1708–1720. doi:10.1056/NEJMoa2002032 - DOI - PMC - PubMed
1. Wang D, Hu B, Hu C, et al. . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020; 323: 1061–1069. - PMC - PubMed
1. Yang X, Yu Y, Xu J, et al. . Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020; 8: 475–481. doi:10.1016/S2213-2600(20)30079-5 - DOI - PMC - PubMed
1. Metlay JP, Waterer GW, Long AC, et al. . Diagnosis and treatment of adults with community-acquired pneumonia. an official clinical practice guideline of the American Thoracic Society and Infectious Diseases Society of America. Am J Respir Crit Care Med 2019; 200: e45–e67. doi:10.1164/rccm.201908-1581ST - DOI - PMC - PubMed

Publication types

Actions
Actions

MeSH terms

Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions
Actions

LinkOut - more resources

Full Text Sources
Research Materials
- NCI CPTC Antibody Characterization Program
Miscellaneous
- NCI CPTAC Assay Portal

[1] http://2019ncov.chinacdc.cn/2019-nCoV/ Chinese Center for Disease Control and Prevention. Distribution of Covid-19. - PMC - PubMed

[2] http://2019ncov.chinacdc.cn/2019-nCoV/ Chinese Center for Disease Control and Prevention. Distribution of Covid-19. - PMC - PubMed

[3] Guan WJ, Ni ZY, Hu Y, et al. . Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020; 382: 1708–1720. doi:10.1056/NEJMoa2002032 - DOI - PMC - PubMed

[4] Guan WJ, Ni ZY, Hu Y, et al. . Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020; 382: 1708–1720. doi:10.1056/NEJMoa2002032 - DOI - PMC - PubMed

[5] Wang D, Hu B, Hu C, et al. . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020; 323: 1061–1069. - PMC - PubMed

[6] Wang D, Hu B, Hu C, et al. . Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA 2020; 323: 1061–1069. - PMC - PubMed

[7] Yang X, Yu Y, Xu J, et al. . Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020; 8: 475–481. doi:10.1016/S2213-2600(20)30079-5 - DOI - PMC - PubMed

[8] Yang X, Yu Y, Xu J, et al. . Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respir Med 2020; 8: 475–481. doi:10.1016/S2213-2600(20)30079-5 - DOI - PMC - PubMed

[9] Metlay JP, Waterer GW, Long AC, et al. . Diagnosis and treatment of adults with community-acquired pneumonia. an official clinical practice guideline of the American Thoracic Society and Infectious Diseases Society of America. Am J Respir Crit Care Med 2019; 200: e45–e67. doi:10.1164/rccm.201908-1581ST - DOI - PMC - PubMed

[10] Metlay JP, Waterer GW, Long AC, et al. . Diagnosis and treatment of adults with community-acquired pneumonia. an official clinical practice guideline of the American Thoracic Society and Infectious Diseases Society of America. Am J Respir Crit Care Med 2019; 200: e45–e67. doi:10.1164/rccm.201908-1581ST - DOI - PMC - PubMed

Save citation to file

Email citation

Add to Collections

Add to My Bibliography

Your saved search

Create a file for external citation management software

Your RSS Feed

A predictive model for disease progression in non-severely ill patients with coronavirus disease 2019

Affiliations

A predictive model for disease progression in non-severely ill patients with coronavirus disease 2019

Authors

Affiliations

Abstract

Conflict of interest statement

Comment on

Similar articles

Cited by

References

Publication types

MeSH terms

LinkOut - more resources

Full Text Sources

Research Materials

Miscellaneous

Abstract

Conflict of interest statement

Comment on

Similar articles

Cited by

References

Publication types

MeSH terms

Related information

LinkOut - more resources

Full Text Sources

Research Materials

Miscellaneous