The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Persistent symptoms 3 months after a SARS-CoV-2 infection: the post-COVID-19 syndrome?
Open accessAbstract
Background: Many patients with COVID-19 did not require hospitalisation, nor underwent COVID-19 testing. There is anecdotal evidence that patients with “mild” COVID-19 may complain about persistent symptoms, even weeks after the infection. This suggests that symptoms during the infection may not resolve spontaneously. The objective of this study was to assess whether multiple relevant symptoms recover following the onset of symptoms in hospitalised and nonhospitalised patients with COVID-19. Methods: A total of 2113 members of two Facebook groups for coronavirus patients with persistent complaints in the Netherlands and Belgium, and from a panel of people who registered on a website of the Lung Foundation Netherlands, were assessed for demographics, pre-existing comorbidities, health status, date of symptoms onset, COVID-19 diagnosis, healthcare utilisation, and the presence of 29 symptoms at the time of the onset of symptoms (retrospectively) and at follow-up (mean±sd 79±17 days after symptoms onset). Results: Overall, 112 hospitalised patients and 2001 nonhospitalised patients (confirmed COVID-19, n=345; symptom-based COVID-19, n=882; and suspected COVID-19, n=774) were analysed. The median number of symptoms during the infection reduced significantly over time (median (interquartile range) 14 (11–17)versus 6 (4–9); p<0.001). Fatigue and dyspnoea were the most prevalent symptoms during the infection and at follow-up (fatigue: 95%versus 87%; dyspnoea: 90%versus 71%). Conclusion: In previously hospitalised and nonhospitalised patients with confirmed or suspected COVID-19, multiple symptoms are present about 3 months after symptoms onset. This suggests the presence of a “post-COVID-19 syndrome” and highlights the unmet healthcare needs in a subgroup of patients with “mild” or “severe” COVID-19.
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Cites
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
Persistent Symptoms in Patients After Acute COVID-19
Carfì, A., Bernabei, R., Landi, F., & for the Gemelli Against COVID-19 Post-Acute Care Study Group (2020) · JAMA · doi:10.1001/jama.2020.12603 · Cited by 4,561 · cited 3×
“, those who were hospitalized) also a symptom burden persists in the months after the onset of symptoms this is in line with recent findings in hospitalized patients [4].”
BackgroundResultInfluentialSpruit, M. A., Singh, S. J., Garvey, C., ZuWallack, R., Nici, L., Rochester, C., Hill, K., Holland, A. E., Lareau, S. C., Man, W. D.-C., et al. (2013) · American Journal of Respiratory and Critical Care Medicine · doi:10.1164/rccm.201309-1634st · Cited by 3,938
Self-citationLi, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., & Shaman, J. (2020) · Science · doi:10.1126/science.abb3221 · Cited by 3,633
Docherty, A. B., Harrison, E. M., Green, C. A., Hardwick, H. E., Pius, R., Norman, L., Holden, K. A., Read, J. M., Dondelinger, F., Carson, G., et al. (2020) · BMJ · doi:10.1136/bmj.m1985 · Cited by 3,481
Lam, M. H.-B. (2009) · Archives of Internal Medicine · doi:10.1001/archinternmed.2009.384 · Cited by 723
Moldofsky, H., & Patcai, J. (2011) · BMC Neurology · doi:10.1186/1471-2377-11-37 · Cited by 604 · cited 1×
“This is also in line with findings in other post-viral/infectious syndromes [15-18] and findings from critically ill (non-COVID) patients that have been discharged from the ICU, who still experience a wide array of symptoms months”
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Cited by
Characterizing long COVID in an international cohort: 7 months of symptoms and their impact
Davis, H. E., Assaf, G. S., McCorkell, L., Wei, H., Low, R. J., Re'em, Y., Redfield, S., Austin, J. P., & Akrami, A. (2021) · eClinicalMedicine · doi:10.1016/j.eclinm.2021.101019 · Cited by 2,881
More than 50 long-term effects of COVID-19: a systematic review and meta-analysis
Lopez-Leon, S., Wegman-Ostrosky, T., Perelman, C., Sepulveda, R., Rebolledo, P. A., Cuapio, A., & Villapol, S. (2021) · Scientific Reports · doi:10.1038/s41598-021-95565-8 · Cited by 2,757
Long covid—mechanisms, risk factors, and management
Crook, H., Raza, S., Nowell, J., Young, M., & Edison, P. (2021) · BMJ · doi:10.1136/bmj.n1648 · Cited by 1,655
Symptoms, complications and management of long COVID: a review
Aiyegbusi, O. L., Hughes, S. E., Turner, G., Rivera, S. C., McMullan, C., Chandan, J. S., Haroon, S., Price, G., Davies, E. H., Nirantharakumar, K., et al. (2021) · Journal of the Royal Society of Medicine · doi:10.1177/01410768211032850 · Cited by 969
Persistent neurologic symptoms and cognitive dysfunction in non-hospitalized COVID-19 “long haulers”
Graham, E. L., Clark, J. R., Orban, Z. S., Lim, P. H., Szymanski, A. L., Taylor, C., DiBiase, R. M., Jia, D. T., Balabanov, R., Ho, S. U., et al. (2021) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.51350 · Cited by 693
Physical and mental health complications post-COVID-19: Scoping review
Shanbehzadeh, S., Tavahomi, M., Zanjari, N., Ebrahimi-Takamjani, I., & Amiri-arimi, S. (2021) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2021.110525 · Cited by 334
Characterizing long COVID: deep phenotype of a complex condition
Deer, R. R., Rock, M. A., Vasilevsky, N., Carmody, L., Rando, H., Anzalone, A. J., Basson, M. D., Bennett, T. D., Bergquist, T., Boudreau, E. A., et al. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103722 · Cited by 200
Blagova, O. V., Kogan, E. A., Lutokhina, Y. A., Kukleva, A. D., Ainetdinova, D. H., Novosadov, V. M., Rud`, R. S., Zaitsev, A. Y., Zaidenov, V. A., Kupriyanova, A. G., et al. (2021) · Kardiologiia · doi:10.18087/cardio.2021.6.n1659 · Cited by 34
Metadata
- Authors
- Goërtz, Y. M. J., Van Herck, M., Delbressine, J. M., Vaes, A. W., Meys, R., Machado, F. V. C., Houben-Wilke, S., Burtin, C., Posthuma, R., Franssen, F. M. E., van Loon, N., Hajian, B., Spies, Y., Vijlbrief, H., van ’t Hul, A. J., Janssen, D. J. A., & Spruit, M. A.
- Venue
- ERJ Open Research
- Publisher
- European Respiratory Society (ERS)
- Published
- 2020-09-10
- Volume
- 6
- Issue
- 4
- Pages
- 00542-2020
- ISSN
- 2312-0541 (ISSN-L)
- OpenAlex
- W3085847973
- Cited by
- 847
- References
- 7
- FWCI
- 63.34
- Type
- journal article
- Language
- en
- Open access
- gold
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