The DOI matches its Crossref record; 73 of the 73 references it cites were found in a registry or an index.
Cytokine elevation in severe and critical COVID-19: a rapid systematic review, meta-analysis, and comparison with other inflammatory syndromes
Open accessAbstract
The description of a so-called cytokine storm in patients with COVID-19 has prompted consideration of anti-cytokine therapies, particularly interleukin-6 antagonists. However, direct systematic comparisons of COVID-19 with other critical illnesses associated with elevated cytokine concentrations have not been reported. In this Rapid Review, we report the results of a systematic review and meta-analysis of COVID-19 studies published or posted as preprints between Nov 1, 2019, and April 14, 2020, in which interleukin-6 concentrations in patients with severe or critical disease were recorded. 25 COVID-19 studies (n=1245 patients) were ultimately included. Comparator groups included four trials each in sepsis (n=5320), cytokine release syndrome (n=72), and acute respiratory distress syndrome unrelated to COVID-19 (n=2767). In patients with severe or critical COVID-19, the pooled mean serum interleukin-6 concentration was 36·7 pg/mL (95% CI 21·6–62·3 pg/mL; I2=57·7%). Mean interleukin-6 concentrations were nearly 100 times higher in patients with cytokine release syndrome (3110·5 pg/mL, 632·3–15 302·9 pg/mL; p<0·0001), 27 times higher in patients with sepsis (983·6 pg/mL, 550·1–1758·4 pg/mL; p<0·0001), and 12 times higher in patients with acute respiratory distress syndrome unrelated to COVID-19 (460 pg/mL, 216·3–978·7 pg/mL; p<0·0001). Our findings question the role of a cytokine storm in COVID-19-induced organ dysfunction. Many questions remain about the immune features of COVID-19 and the potential role of anti-cytokine and immune-modulating treatments in patients with the disease.
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
1 retracted
Wang, X., Xu, W., Hu, G., Xia, S., Sun, Z., Liu, Z., Xie, Y., Zhang, R., Jiang, S., & Lu, L. (2020) · Cellular & Molecular Immunology · doi:10.1038/s41423-020-0498-4 · Cited by 175
RetractedClinical 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
The third international consensus definitions for sepsis and septic shock (Sepsis-3).
Singer, M., Deutschman, C. S., Seymour, C. W., Shankar-Hari, M., Annane, D., Bauer, M., Bellomo, R., Bernard, G. R., Chiche, J.-D., Coopersmith, C. M., et al. (2016) · JAMA · doi:10.1001/jama.2016.0287 · Cited by 28,250
Self-citationZhou, 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
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
Wan, X., Wang, W., Liu, J., & Tong, T. (2014) · BMC Medical Research Methodology · doi:10.1186/1471-2288-14-135 · Cited by 11,735
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
Effect of Dexamethasone in Hospitalized Patients with COVID-19 – Preliminary Report
Horby, P., Lim, W. S., Emberson, J., Mafham, M., Bell, J., Linsell, L., Staplin, N., Brightling, C., Ustianowski, A., Elmahi, E., et al. (2020) · doi:10.1101/2020.06.22.20137273 · Cited by 11,475
Chen, Y., Wang, L., Kang, Q., Zhang, X., Yu, G., Wan, X., Wang, J., & Zhu, K. (2017) · Cellular Physiology and Biochemistry · doi:10.1159/000477308 · Cited by 10,679
Harrell, F. E. (2001) · Springer Series in Statistics · doi:10.1007/978-1-4757-3462-1 · Cited by 9,195
Cited by
Karki, R., Sharma, B. R., Tuladhar, S., Williams, E. P., Zalduondo, L., Samir, P., Zheng, M., Sundaram, B., Banoth, B., Malireddi, R. K. S., et al. (2021) · Cell · doi:10.1016/j.cell.2020.11.025 · Cited by 1,734
The WHO Rapid Evidence Appraisal for COVID-19 Therapies (REACT) Working Group, Domingo, P., Mur, I., Mateo, G. M., Gutierrez, M. D. M., Pomar, V., de Benito, N., Corbacho, N., Herrera, S., Millan, L., et al. (2021) · JAMA · doi:10.1001/jama.2021.11330 · Cited by 678
SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis
Wendisch, D., Dietrich, O., Mari, T., von Stillfried, S., Ibarra, I. L., Mittermaier, M., Mache, C., Chua, R. L., Knoll, R., Timm, S., et al. (2021) · Cell · doi:10.1016/j.cell.2021.11.033 · Cited by 528
Badulak, J., Antonini, M. V., Stead, C. M., Shekerdemian, L., Raman, L., Paden, M. L., Agerstrand, C., Bartlett, R. H., Barrett, N., Combes, A., et al. (2021) · ASAIO Journal · doi:10.1097/mat.0000000000001422 · Cited by 404
COVID-19 and pulmonary fibrosis: a potential role for lung epithelial cells and fibroblasts
John, A. E., Joseph, C., Jenkins, G., & Tatler, A. L. (2021) · Immunological Reviews · doi:10.1111/imr.12977 · Cited by 219
Metadata
- Authors
- Leisman, D. E., Ronner, L., Pinotti, R., Taylor, M. D., Sinha, P., Calfee, C. S., Hirayama, A. V., Mastroiani, F., Turtle, C. J., Harhay, M. O., Legrand, M., & Deutschman, C. S.
- Venue
- The Lancet Respiratory Medicine
- Publisher
- Elsevier BV
- Published
- 2020-12
- Volume
- 8
- Issue
- 12
- Pages
- 1233-1244
- ISSN
- 2213-2600 (ISSN-L)
- OpenAlex
- W3093261446
- Cited by
- 855
- References
- 73
- FWCI
- 9.78
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Cytokine elevation in severe and critical COVID-19: a rapid systematic review, meta-analysis, and comparison with other inflammatory syndromes. https://app.cochat.ai/papers/10.1016/s2213-2600(20)30404-5
- The paper
- Leisman, D. E., Ronner, L., Pinotti, R., Taylor, M. D., Sinha, P., Calfee, C. S., Hirayama, A. V., Mastroiani, F., Turtle, C. J., Harhay, M. O., Legrand, M., & Deutschman, C. S. (2020). Cytokine elevation in severe and critical COVID-19: a rapid systematic review, meta-analysis, and comparison with other inflammatory syndromes. The Lancet Respiratory Medicine. https://doi.org/10.1016/s2213-2600(20)30404-5
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.