The DOI matches its Crossref record; 27 of the 27 references it cites were found in a registry or an index.
A minimal common outcome measure set for COVID-19 clinical research
Open accessAbstract
Summary Clinical research is necessary for an effective response to an emerging infectious disease outbreak. However, research efforts are often hastily organised and done using various research tools, with the result that pooling data across studies is challenging. In response to the needs of the rapidly evolving COVID-19 outbreak, the Clinical Characterisation and Management Working Group of the WHO Research and Development Blueprint programme, the International Forum for Acute Care Trialists, and the International Severe Acute Respiratory and Emerging Infections Consortium have developed a minimum set of common outcome measures for studies of COVID-19. This set includes three elements: a measure of viral burden (quantitative PCR or cycle threshold), a measure of patient survival (mortality at hospital discharge or at 60 days), and a measure of patient progression through the health-care system by use of the WHO Clinical Progression Scale, which reflects patient trajectory and resource use over the course of clinical illness. We urge investigators to include these key data elements in ongoing and future studies to expedite the pooling of data during this immediate threat, and to hone a tool for future needs.
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Cites
Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., et al. (2020) · JAMA · doi:10.1001/jama.2020.1585 · Cited by 20,148
Self-citationLa certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
Martínez González, M. (2020) · DSPACE System - Metalibrary (University of the Coast) · Cited by 18,463
Grasselli, G., Zangrillo, A., Zanella, A., Antonelli, M., Cabrini, L., Castelli, A., Cereda, D., Coluccello, A., Foti, G., Fumagalli, R., et al. (2020) · JAMA · doi:10.1001/jama.2020.5394 · Cited by 5,469
A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19
Cao, B., Wang, Y., Wen, D., Liu, W., Wang, J., Fan, G., Ruan, L., Song, B., Cai, Y., Wei, M., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2001282 · Cited by 5,187
Self-citationLikert scales, levels of measurement, and the “laws” of statistics
Norman, G. (2010) · Advances in Health Sciences Education · doi:10.1007/s10459-010-9222-y · Cited by 4,850
Clinical Characteristics of Covid-19 in New York City
Goyal, P., Choi, J. J., Pinheiro, L. C., Schenck, E. J., Chen, R., Jabri, A., Satlin, M. J., Campion, T. R., Nahid, M., Ringel, J. B., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmc2010419 · Cited by 2,234
Xie, X., Zhong, Z., Zhao, W., Zheng, C., Wang, F., & Liu, J. (2020) · Radiology · doi:10.1148/radiol.2020200343 · Cited by 1,960
Developing core outcome sets for clinical trials: issues to consider
Williamson, P. R., Altman, D. G., Blazeby, J. M., Clarke, M., Devane, D., Gargon, E., & Tugwell, P. (2012) · Trials · doi:10.1186/1745-6215-13-132 · Cited by 1,661
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Cited by
Voysey, M., Clemens, S. A. C., Madhi, S. A., Weckx, L. Y., Folegatti, P. M., Aley, P. K., Angus, B., Baillie, V. L., Barnabas, S. L., Bhorat, Q. E., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32661-1 · Cited by 4,616
Self-citationInterleukin-6 receptor antagonists in critically ill patients with Covid-19.
The REMAP-CAP Investigators (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2100433 · Cited by 1,962
Tanriover, M. D., Doğanay, H. L., Akova, M., Güner, H. R., Azap, A., Akhan, S., Köse, Ş., Erdinç, F. Ş., Akalın, E. H., Tabak, Ö. F., et al. (2021) · The Lancet · doi:10.1016/s0140-6736(21)01429-x · Cited by 898
The Writing Committee for the REMAP-CAP Investigators, Angus, D. C., Derde, L., Al-Beidh, F., Annane, D., Arabi, Y., Beane, A., van Bentum-Puijk, W., Berry, L., Bhimani, Z., et al. (2020) · JAMA · doi:10.1001/jama.2020.17022 · Cited by 855
Self-citationHermine, O., Mariette, X., Tharaux, P.-L., Resche-Rigon, M., Porcher, R., Ravaud, P., CORIMUNO-19 Collaborative Group, Bureau, S., Dougados, M., Tibi, A., et al. (2021) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2020.6820 · Cited by 734
Metadata
- Authors
- Marshall, J. C., Murthy, S., Diaz, J., Adhikari, N. K., Angus, D. C., Arabi, Y. M., Baillie, K., Bauer, M., Berry, S., Blackwood, B., Bonten, M., Bozza, F., Brunkhorst, F., Cheng, A., Clarke, M., Dat, V. Q., de Jong, M., Denholm, J., Derde, L., Dunning, J., Feng, X., Fletcher, T., Foster, N., Fowler, R., Gobat, N., Gomersall, C., Gordon, A., Glueck, T., Harhay, M., Hodgson, C., Horby, P., Kim, Y., Kojan, R., Kumar, B., Laffey, J., Malvey, D., Martin-Loeches, I., McArthur, C., McAuley, D., McBride, S., McGuinness, S., Merson, L., Morpeth, S., Needham, D., Netea, M., Oh, M.-D., Phyu, S., Piva, S., Qiu, R., Salisu-Kabara, H., Shi, L., Shimizu, N., Sinclair, J., Tong, S., Turgeon, A., Uyeki, T., van de Veerdonk, F., Webb, S., Williamson, P., Wolf, T., & Zhang, J.
- Venue
- The Lancet Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2020-08
- Volume
- 20
- Issue
- 8
- Pages
- e192-e197
- ISSN
- 1473-3099 (ISSN-L)
- OpenAlex
- W3034858522
- Cited by
- 1,641
- References
- 27
- FWCI
- 35.82
- Type
- journal article
- Language
- en
- Open access
- green
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- Marshall, J. C., Murthy, S., Diaz, J., Adhikari, N. K., Angus, D. C., Arabi, Y. M., Baillie, K., Bauer, M., Berry, S., Blackwood, B., Bonten, M., Bozza, F., Brunkhorst, F., Cheng, A., Clarke, M., Dat, V. Q., de Jong, M., Denholm, J., Derde, L., . . . Zhang, J. (2020). A minimal common outcome measure set for COVID-19 clinical research. The Lancet Infectious Diseases. https://doi.org/10.1016/s1473-3099(20)30483-7
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