The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Covid-19 hyperinflammation and post-Covid-19 illness may be rooted in mast cell activation syndrome
Open accessAbstract
OBJECTIVES: One-fifth of Covid-19 patients suffer a severe course of Covid-19 infection; however, the specific causes remain unclear. Mast cells (MCs) are activated by SARS-CoV-2. Although only recently recognized, MC activation syndrome (MCAS), usually due to acquired MC clonality, is a chronic multisystem disorder with inflammatory and allergic themes, and an estimated prevalence of 17%. This paper describes a novel conjecture explaining how MCAS might cause a propensity for severe acute Covid-19 infection and chronic post-Covid-19 illnesses. METHODS: Observations of Covid-19 illness in patients with/without MCAS were compared with extensive clinical experience with MCAS. RESULTS: The prevalence of MCAS is similar to that of severe cases within the Covid-19-infected population. Much of Covid-19's hyperinflammation is concordant with manners of inflammation which MC activation can drive. Drugs with activity against MCs or their mediators have preliminarily been observed to be helpful in Covid-19 patients. None of the authors' treated MCAS patients with Covid-19 suffered severe infection, let alone mortality. CONCLUSIONS: Hyperinflammatory cytokine storms in many severely symptomatic Covid-19 patients may be rooted in an atypical response to SARS-CoV-2 by the dysfunctional MCs of MCAS rather than a normal response by normal MCs. If proven, this theory has significant therapeutic and prognostic implications.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Zhou, F., Yu, T., Du, R., Fan, G., Liu, Y., Liu, Z., Xiang, J., Wang, Y., Song, B., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30566-3 · Cited by 27,263
Dexamethasone in Hospitalized Patients with Covid-19
The RECOVERY Collaborative Group (2021) · New England Journal of Medicine · doi:10.1056/nejmoa2021436 · Cited by 11,477
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
Ruan, Q., Yang, K., Wang, W., Jiang, L., & Song, J. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-05991-x · Cited by 4,898
Association of cardiac injury with mortality in hospitalized patients with COVID-19 in Wuhan, China
Shi, S., Qin, M., Shen, B., Cai, Y., Liu, T., Yang, F., Gong, W., Liu, X., Liang, J., Zhao, Q., et al. (2020) · JAMA Cardiology · doi:10.1001/jamacardio.2020.0950 · Cited by 4,349
Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study
Chen, T., Wu, D., Chen, H., Yan, W., Yang, D., Chen, G., Ma, K., Xu, D., Yu, H., Wang, H., et al. (2020) · BMJ · doi:10.1136/bmj.m1091 · Cited by 3,903
Pulmonary fibrosis and COVID-19: the potential role for antifibrotic therapy
George, P. M., Wells, A. U., & Jenkins, R. G. (2020) · The Lancet Respiratory Medicine · doi:10.1016/s2213-2600(20)30225-3 · Cited by 1,085
Troyer, E. A., Kohn, J. N., & Hong, S. (2020) · Brain, Behavior, and Immunity · doi:10.1016/j.bbi.2020.04.027 · Cited by 964
Cytokine storms: understanding COVID-19
Mangalmurti, N., & Hunter, C. A. (2020) · Immunity · doi:10.1016/j.immuni.2020.06.017 · Cited by 698
Cytokine storm intervention in the early stages of COVID-19 pneumonia
Sun, X., Wang, T., Cai, D., Hu, Z., Chen, J., Liao, H., Zhi, L., Wei, H., Zhang, Z., Qiu, Y., et al. (2020) · Cytokine & Growth Factor Reviews · doi:10.1016/j.cytogfr.2020.04.002 · Cited by 513
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
“tical dashed lines indicate the range for “No fatigue”[10-21], “Fatigue”[22-34], and “Extreme” (>=35).”
Long COVID or post-COVID-19 syndrome: putative pathophysiology, risk factors, and treatments
Yong, S. J. (2021) · Infectious Diseases · doi:10.1080/23744235.2021.1924397 · Cited by 1,339
Pathophysiology and mechanism of long COVID: a comprehensive review
Castanares-Zapatero, D., Chalon, P., Kohn, L., Dauvrin, M., Detollenaere, J., Maertens de Noordhout, C., Primus-de Jong, C., Cleemput, I., & Van den Heede, K. (2022) · Annals of Medicine · doi:10.1080/07853890.2022.2076901 · Cited by 585
Fernández-de-las-Peñas, C., Palacios-Ceña, D., Gómez-Mayordomo, V., Florencio, L. L., Cuadrado, M. L., Plaza-Manzano, G., & Navarro-Santana, M. (2021) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2021.06.009 · Cited by 574
Pretorius, E., Vlok, M., Venter, C., Bezuidenhout, J. A., Laubscher, G. J., Steenkamp, J., & Kell, D. B. (2021) · Cardiovascular Diabetology · doi:10.1186/s12933-021-01359-7 · Cited by 518
Metadata
- Authors
- Afrin, L. B., Weinstock, L. B., & Molderings, G. J.
- Venue
- International Journal of Infectious Diseases
- Publisher
- Elsevier BV
- Published
- 2020-11
- Volume
- 100
- Pages
- 327-332
- ISSN
- 1201-9712 (ISSN-L)
- OpenAlex
- W3086293749
- Cited by
- 314
- References
- 19
- FWCI
- 16.40
- Type
- journal article
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Covid-19 hyperinflammation and post-Covid-19 illness may be rooted in mast cell activation syndrome. https://app.cochat.ai/papers/10.1016/j.ijid.2020.09.016
- The paper
- Afrin, L. B., Weinstock, L. B., & Molderings, G. J. (2020). Covid-19 hyperinflammation and post-Covid-19 illness may be rooted in mast cell activation syndrome. International Journal of Infectious Diseases. https://doi.org/10.1016/j.ijid.2020.09.016
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
