應對新型冠狀病毒肺炎的診治技術_Chinese Journal of Respiratory and Critical Care Medicine

Authors：

羅汶鑫 ,  李為民

四川大學華西醫院呼吸與危重癥醫學科（四川成都 610041）;

Corresponding?author：

李為民, Email: weimin003@163.com

Keywords：

DOI：

10.7507/1671-6205.202004116

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Citation： 羅汶鑫, 李為民. 應對新型冠狀病毒肺炎的診治技術. Chinese Journal of Respiratory and Critical Care Medicine, 2020, 19(3): 209-213. doi: 10.7507/1671-6205.202004116 Copy

1.	Wu F, Zhao S, Yu B, et al. A new coronavirus associated with human respiratory disease in China. Nature, 2020, 579(7798): 265-269.
2.	Wang M, Fu AS, Hu B, et al. Nanopore target sequencing for accurate and comprehensive detection of SARS-CoV-2 and other respiratory viruses[EB/OL]. medRxiv, 2020.03.04.20029538. https://doi.org/10.1101/2020.03.04.20029538.
3.	國家衛生健康委員會. 新型冠狀病毒肺炎診療方案(試行第七版)[EB/OL]. (2020-02-18). http://www.nhc.gov.cn/xcs/zhengcwj/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml.
4.	Chan JF, Yip CC, To KK, et al. Improved molecular diagnosis of COVID-19 by the novel, highly sensitive and specific COVID-19-RdRp/Hel real-time reverse transcription-polymerase chain reaction assay validated in vitro and with clinical specimens. J Clin Microbiol, 2020, 58(5): e00310-20.
5.	Chu DKW, Pan Y, Cheng SMS, et al. Molecular diagnosis of a novel coronavirus (2019-nCoV) causing an outbreak of pneumonia. Clin Chem, 2020, 66(4): 549-555.
6.	Yang Y, Yang MH, Shen CG, et al. Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections[EB/OL]. medRxiv, 2020.02.11.20021493. https://doi.org/10.1101/2020.02.11.20021493.
7.	To KK, Tsang OT, Chik-Yan Yip C, et al. Consistent detection of 2019 novel coronavirus in saliva[J/OL]. Clin Infect Dis. (2020-02-12). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa149/5734265.
8.	Yan C, Cui J, Huang L, et al. Rapid and visual detection of 2019 novel coronavirus (SARS-CoV-2) by a reverse transcription loop-mediated isothermal amplification assay[J/OL]. Clin Microbiol Infect, 2020. https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(20)30186-5/pdf.
9.	Gootenberg JS, Abudayyeh OO, Lee JW, et al. Nucleic acid detection with CRISPR-Cas13a/C2c2. Science, 2017, 356(6336): 438-442.
10.	Point-of-care testing for COVID-19 using SHERLOCK diagnostics[EB/OL]. (2020-05-05). https://www.stopcovid.science/docs/STOPCovid%20Whitepaper.pdf.
11.	Zhao JJ, Yuan Q, Wang HY, et al. Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019[J/OL]. Clin Infect Dis, 2020, (2020-03-28). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa344/5812996#.
12.	Jin Y, Wang M, Zuo Z, et al. Diagnostic value and dynamic variance of serum antibody in coronavirus disease 2019. Int J Infect Dis, 2020, 94: 49-52.
13.	Xiang J, Yan M, Li H, et al. Evaluation of enzyme-linked immunoassay and colloidal gold- immunochromatographic assay kit for detection of novel coronavirus (SARS-Cov-2) causing an outbreak of pneumonia (COVID-19) [EB/OL]. medRxiv, 2020.02.27.20028787. https://www.medrxiv.org/content/10.1101/2020.02.27.20028787v1.
14.	Guo L, Ren L, Yang S, et al. Profiling early humoral response to diagnose novel coronavirus disease (COVID-19)[J/OL]. Clin Infect Dis, 2020, (2020-03-21). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa310/5810754#.
15.	Li ZT, Yi YX, Luo XM, et al. Development and clinical application of a rapid IgM-IgG combined antibody test for SARS-CoV-2 infection diagnosis[J/OL]. J Med Virol, (2020-02-27). https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25727.
16.	To KK-W, Tsang OT-Y, Leung W-S, et al. Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study. Lancet Infect Dis, 2020, 20(5): 565-574.
17.	Alimadadi A, Aryal S, Manandhar I, et al. Artificial intelligence and machine learning to fight COVID-19. Physiol Genomics, 2020, 52: 200-202.
18.	Cleemput S, Dumon W, Fonseca V, et al. Genome detective coronavirus typing tool for rapid identification and characterization of novel coronavirus genomes[J/OL]. Bioinformatics, (2020-02-28). https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa145/5766118.
19.	Metsky HC, Freije CA, Kosoko-Thoroddsen T-SF, et al. CRISPR-based COVID-19 surveillance using a genomically-comprehensive machine learning approach[EB/OL]. bioRxiv, 2020.02.26.967026. https://www.biorxiv.org/content/10.1101/2020.02.26.967026v2.
20.	Ai T, Yang ZL, Hou HY, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019(COVID-19) in China: a report of 1014 cases[J/OL]. Radiology, (2020-02-26). https://doi.org/10.1148/radiol.2020200642.
21.	Xie XZ, Zhong Z, Zhao W, et al. Chest CT for typical 2019-nCoV pneumonia: relationship to negative RT-PCR testing[J/OL]. Radiology, (2020-02-12). https://doi.org/10.1148/radiol.2020200343.
22.	Kanne JP, Little BP, Chung JH, et al. Essentials for radiologists on COVID-19: an update radiology scientific expert panel[J/OL]. Radiology, (2020-02-27). https://doi.org/10.1148/radiol.2020200527.
23.	Chen J, Wu LL, Zhang J, et al. Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study[EB/OL]. medRxiv, 2020.02.25.20021568. https://www.medrxiv.org/content/10.1101/2020.02.25.20021568v2.
24.	Li L, Qin LX, Xu ZG, et al. Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT[J/OL]. Radiology, (2020-03-19). https://doi.org/10.1148/radiol.2020200905.
25.	Zhou M, Chen Y, Wang DX, et al. Improved deep learning model for differentiating novel coronavirus pneumonia and influenza pneumonia[EB/OL]. medRxiv, 2020.03.24.20043117. https://www.medrxiv.org/content/10.1101/2020.03.24.20043117v1.
26.	Zhavoronkov A. Artificial intelligence for drug discovery, biomarker development, and generation of novel chemistry. Mol Pharm, 2018, 15(10): 4311-4313.
27.	Richardson P, Griffin I, Tucker C, et al. Baricitinib as potential treatment for 2019-nCoV acute respiratory disease. Lancet, 2020, 395(10223): e30-e31.
28.	Ge YY, Tian TZ, Huang SL, et al. A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19[EB/OL]. bioRxiv, 2020.03.11.986836. https://www.biorxiv.org/content/10.1101/2020.03.11.986836v1.
29.	Chen YW, Yiu CPB, Wong KY. Prediction of the SARS-CoV-2(2019-nCoV) 3C-like protease (3CLpro) structure: virtual screening reveals velpatasvir, ledipasvir, and other drug repurposing candidates. F1000Res, 2020, 9: 129.
30.	Senior AW, Evans R, Jumper J, et al. Improved protein structure prediction using potentials from deep learning. Nature, 2020, 577(7792): 706-710.
31.	Jumper J, Tunyasuvunakool K, Kohli P, et al. Computational predictions of protein structures associated with COVID-19(Version 2)[EB/OL]. DeepMind website (2020-04-08). https://deepmind.com/research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19.
32.	Yan L, Zhang HT, Goncalves J, et al. A machine learning-based model for survival prediction in patients with severe COVID-19 infection[EB/OL]. medRxiv, 2020.02.27.20028027. https://www.medrxiv.org/content/10.1101/2020.02.27.20028027v3.
33.	Qi XL, Jiang ZC, Yu Q, et al. Machine learning-based CT radiomics model for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: a multicenter study[EB/OL]. medRxiv, 2020.02.29.20029603. https://www.medrxiv.org/content/10.1101/2020.02.29.20029603v1.
34.	Kamel Boulos MN, Geraghty EM. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) epidemic and associated events around the world: How 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. Int J Health Geogr, 2020, 19(1): 8.
35.	Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis, 2020, 20(5): 533-534.
36.	四川完成新型冠狀病毒感染肺炎 5G 遠程會診[V/OL]. (2020-01-27). http://www.xinhuanet.com/info/2020-01/27/c_138736590.htm.
37.	Clinical eHealth 中國物聯網輔助 COVID-19 診治專家. 物聯網輔助 2019 冠狀病毒病(COVID-19)診治中國專家共識. 復旦學報(醫學版), 2020, 47(2): 151-160.
38.	Sun S, Yu K, Xie Z, Pan X. China empowers Internet hospital to fight a-160.gainst COVID-19[J/OL]. J Infect, (2020-04-03). https://www.journalofinfection.com/article/S0163-4453(20)30183-3/pdf.

1. Wu F, Zhao S, Yu B, et al. A new coronavirus associated with human respiratory disease in China. Nature, 2020, 579(7798): 265-269.
2. Wang M, Fu AS, Hu B, et al. Nanopore target sequencing for accurate and comprehensive detection of SARS-CoV-2 and other respiratory viruses[EB/OL]. medRxiv, 2020.03.04.20029538. https://doi.org/10.1101/2020.03.04.20029538.
3. 國家衛生健康委員會. 新型冠狀病毒肺炎診療方案(試行第七版)[EB/OL]. (2020-02-18). http://www.nhc.gov.cn/xcs/zhengcwj/202003/46c9294a7dfe4cef80dc7f5912eb1989.shtml.
4. Chan JF, Yip CC, To KK, et al. Improved molecular diagnosis of COVID-19 by the novel, highly sensitive and specific COVID-19-RdRp/Hel real-time reverse transcription-polymerase chain reaction assay validated in vitro and with clinical specimens. J Clin Microbiol, 2020, 58(5): e00310-20.
5. Chu DKW, Pan Y, Cheng SMS, et al. Molecular diagnosis of a novel coronavirus (2019-nCoV) causing an outbreak of pneumonia. Clin Chem, 2020, 66(4): 549-555.
6. Yang Y, Yang MH, Shen CG, et al. Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections[EB/OL]. medRxiv, 2020.02.11.20021493. https://doi.org/10.1101/2020.02.11.20021493.
7. To KK, Tsang OT, Chik-Yan Yip C, et al. Consistent detection of 2019 novel coronavirus in saliva[J/OL]. Clin Infect Dis. (2020-02-12). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa149/5734265.
8. Yan C, Cui J, Huang L, et al. Rapid and visual detection of 2019 novel coronavirus (SARS-CoV-2) by a reverse transcription loop-mediated isothermal amplification assay[J/OL]. Clin Microbiol Infect, 2020. https://www.clinicalmicrobiologyandinfection.com/article/S1198-743X(20)30186-5/pdf.
9. Gootenberg JS, Abudayyeh OO, Lee JW, et al. Nucleic acid detection with CRISPR-Cas13a/C2c2. Science, 2017, 356(6336): 438-442.
10. Point-of-care testing for COVID-19 using SHERLOCK diagnostics[EB/OL]. (2020-05-05). https://www.stopcovid.science/docs/STOPCovid%20Whitepaper.pdf.
11. Zhao JJ, Yuan Q, Wang HY, et al. Antibody responses to SARS-CoV-2 in patients of novel coronavirus disease 2019[J/OL]. Clin Infect Dis, 2020, (2020-03-28). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa344/5812996#.
12. Jin Y, Wang M, Zuo Z, et al. Diagnostic value and dynamic variance of serum antibody in coronavirus disease 2019. Int J Infect Dis, 2020, 94: 49-52.
13. Xiang J, Yan M, Li H, et al. Evaluation of enzyme-linked immunoassay and colloidal gold- immunochromatographic assay kit for detection of novel coronavirus (SARS-Cov-2) causing an outbreak of pneumonia (COVID-19) [EB/OL]. medRxiv, 2020.02.27.20028787. https://www.medrxiv.org/content/10.1101/2020.02.27.20028787v1.
14. Guo L, Ren L, Yang S, et al. Profiling early humoral response to diagnose novel coronavirus disease (COVID-19)[J/OL]. Clin Infect Dis, 2020, (2020-03-21). https://academic.oup.com/cid/advance-article/doi/10.1093/cid/ciaa310/5810754#.
15. Li ZT, Yi YX, Luo XM, et al. Development and clinical application of a rapid IgM-IgG combined antibody test for SARS-CoV-2 infection diagnosis[J/OL]. J Med Virol, (2020-02-27). https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25727.
16. To KK-W, Tsang OT-Y, Leung W-S, et al. Temporal profiles of viral load in posterior oropharyngeal saliva samples and serum antibody responses during infection by SARS-CoV-2: an observational cohort study. Lancet Infect Dis, 2020, 20(5): 565-574.
17. Alimadadi A, Aryal S, Manandhar I, et al. Artificial intelligence and machine learning to fight COVID-19. Physiol Genomics, 2020, 52: 200-202.
18. Cleemput S, Dumon W, Fonseca V, et al. Genome detective coronavirus typing tool for rapid identification and characterization of novel coronavirus genomes[J/OL]. Bioinformatics, (2020-02-28). https://academic.oup.com/bioinformatics/advance-article/doi/10.1093/bioinformatics/btaa145/5766118.
19. Metsky HC, Freije CA, Kosoko-Thoroddsen T-SF, et al. CRISPR-based COVID-19 surveillance using a genomically-comprehensive machine learning approach[EB/OL]. bioRxiv, 2020.02.26.967026. https://www.biorxiv.org/content/10.1101/2020.02.26.967026v2.
20. Ai T, Yang ZL, Hou HY, et al. Correlation of chest CT and RT-PCR testing in coronavirus disease 2019(COVID-19) in China: a report of 1014 cases[J/OL]. Radiology, (2020-02-26). https://doi.org/10.1148/radiol.2020200642.
21. Xie XZ, Zhong Z, Zhao W, et al. Chest CT for typical 2019-nCoV pneumonia: relationship to negative RT-PCR testing[J/OL]. Radiology, (2020-02-12). https://doi.org/10.1148/radiol.2020200343.
22. Kanne JP, Little BP, Chung JH, et al. Essentials for radiologists on COVID-19: an update radiology scientific expert panel[J/OL]. Radiology, (2020-02-27). https://doi.org/10.1148/radiol.2020200527.
23. Chen J, Wu LL, Zhang J, et al. Deep learning-based model for detecting 2019 novel coronavirus pneumonia on high-resolution computed tomography: a prospective study[EB/OL]. medRxiv, 2020.02.25.20021568. https://www.medrxiv.org/content/10.1101/2020.02.25.20021568v2.
24. Li L, Qin LX, Xu ZG, et al. Artificial intelligence distinguishes COVID-19 from community acquired pneumonia on chest CT[J/OL]. Radiology, (2020-03-19). https://doi.org/10.1148/radiol.2020200905.
25. Zhou M, Chen Y, Wang DX, et al. Improved deep learning model for differentiating novel coronavirus pneumonia and influenza pneumonia[EB/OL]. medRxiv, 2020.03.24.20043117. https://www.medrxiv.org/content/10.1101/2020.03.24.20043117v1.
26. Zhavoronkov A. Artificial intelligence for drug discovery, biomarker development, and generation of novel chemistry. Mol Pharm, 2018, 15(10): 4311-4313.
27. Richardson P, Griffin I, Tucker C, et al. Baricitinib as potential treatment for 2019-nCoV acute respiratory disease. Lancet, 2020, 395(10223): e30-e31.
28. Ge YY, Tian TZ, Huang SL, et al. A data-driven drug repositioning framework discovered a potential therapeutic agent targeting COVID-19[EB/OL]. bioRxiv, 2020.03.11.986836. https://www.biorxiv.org/content/10.1101/2020.03.11.986836v1.
29. Chen YW, Yiu CPB, Wong KY. Prediction of the SARS-CoV-2(2019-nCoV) 3C-like protease (3CLpro) structure: virtual screening reveals velpatasvir, ledipasvir, and other drug repurposing candidates. F1000Res, 2020, 9: 129.
30. Senior AW, Evans R, Jumper J, et al. Improved protein structure prediction using potentials from deep learning. Nature, 2020, 577(7792): 706-710.
31. Jumper J, Tunyasuvunakool K, Kohli P, et al. Computational predictions of protein structures associated with COVID-19(Version 2)[EB/OL]. DeepMind website (2020-04-08). https://deepmind.com/research/open-source/computational-predictions-of-protein-structures-associated-with-COVID-19.
32. Yan L, Zhang HT, Goncalves J, et al. A machine learning-based model for survival prediction in patients with severe COVID-19 infection[EB/OL]. medRxiv, 2020.02.27.20028027. https://www.medrxiv.org/content/10.1101/2020.02.27.20028027v3.
33. Qi XL, Jiang ZC, Yu Q, et al. Machine learning-based CT radiomics model for predicting hospital stay in patients with pneumonia associated with SARS-CoV-2 infection: a multicenter study[EB/OL]. medRxiv, 2020.02.29.20029603. https://www.medrxiv.org/content/10.1101/2020.02.29.20029603v1.
34. Kamel Boulos MN, Geraghty EM. Geographical tracking and mapping of coronavirus disease COVID-19/severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) epidemic and associated events around the world: How 21st century GIS technologies are supporting the global fight against outbreaks and epidemics. Int J Health Geogr, 2020, 19(1): 8.
35. Dong E, Du H, Gardner L. An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect Dis, 2020, 20(5): 533-534.
36. 四川完成新型冠狀病毒感染肺炎 5G 遠程會診[V/OL]. (2020-01-27). http://www.xinhuanet.com/info/2020-01/27/c_138736590.htm.
37. Clinical eHealth 中國物聯網輔助 COVID-19 診治專家. 物聯網輔助 2019 冠狀病毒病(COVID-19)診治中國專家共識. 復旦學報(醫學版), 2020, 47(2): 151-160.
38. Sun S, Yu K, Xie Z, Pan X. China empowers Internet hospital to fight a-160.gainst COVID-19[J/OL]. J Infect, (2020-04-03). https://www.journalofinfection.com/article/S0163-4453(20)30183-3/pdf.

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應對新型冠狀病毒肺炎的診治技術

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