The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
COVID-19 and metabolic disease: mechanisms and clinical management
Open accessAbstract
Up to 50% of the people who have died from COVID-19 had metabolic and vascular disorders. Notably, there are many direct links between COVID-19 and the metabolic and endocrine systems. Thus, not only are patients with metabolic dysfunction (eg, obesity, hypertension, non-alcoholic fatty liver disease, and diabetes) at an increased risk of developing severe COVID-19 but also infection with SARS-CoV-2 might lead to new-onset diabetes or aggravation of pre-existing metabolic disorders. In this Review, we provide an update on the mechanisms of how metabolic and endocrine disorders might predispose patients to develop severe COVID-19. Additionally, we update the practical recommendations and management of patients with COVID-19 and post-pandemic. Furthermore, we summarise new treatment options for patients with both COVID-19 and diabetes, and highlight current challenges in clinical management.
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
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
Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor
Lan, J., Ge, J., Yu, J., Shan, S., Zhou, H., Fan, S., Zhang, Q., Shi, X., Wang, Q., Zhang, L., et al. (2020) · Nature · doi:10.1038/s41586-020-2180-5 · Cited by 5,983
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
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2021) · Science · doi:10.1126/science.abg3055 · Cited by 2,581
Estimated transmissibility and impact of SARS-CoV-2 lineage B.1.1.7 in England
Davies, N. G., Abbott, S., Barnard, R. C., Jarvis, C. I., Kucharski, A. J., Munday, J. D., Pearson, C. A. B., Russell, T. W., Tully, D. C., Washburne, A. D., et al. (2020) · doi:10.1101/2020.12.24.20248822 · Cited by 2,557
The WHO Rapid Evidence Appraisal for COVID-19 Therapies (REACT) Working Group, Sterne, J. A. C., Murthy, S., Diaz, J. V., Slutsky, A. S., Villar, J., Angus, D. C., Annane, D., Azevedo, L. C. P., Berwanger, O., et al. (2020) · JAMA · doi:10.1001/jama.2020.17023 · Cited by 2,257
Neuropilin-1 facilitates SARS-CoV-2 cell entry and infectivity
Cantuti-Castelvetri, L., Ojha, R., Pedro, L. D., Djannatian, M., Franz, J., Kuivanen, S., van der Meer, F., Kallio, K., Kaya, T., Anastasina, M., et al. (2020) · Science · doi:10.1126/science.abd2985 · Cited by 1,925
High-dimensional characterization of post-acute sequelae of COVID-19
Al-Aly, Z., Xie, Y., & Bowe, B. (2021) · Nature · doi:10.1038/s41586-021-03553-9 · Cited by 1,518
Genomics and epidemiology of the P.1 SARS-CoV-2 lineage in Manaus, Brazil
Faria, N. R., Mellan, T. A., Whittaker, C., Claro, I. M., Candido, D. D. S., Mishra, S., Crispim, M. A. E., Sales, F. C. S., Hawryluk, I., McCrone, J. T., et al. (2021) · Science · doi:10.1126/science.abh2644 · Cited by 1,461
Zhang, P., Zhu, L., Cai, J., Lei, F., Qin, J.-J., Xie, J., Liu, Y.-M., Zhao, Y.-C., Huang, X., Lin, L., et al. (2020) · Circulation Research · doi:10.1161/circresaha.120.317134 · Cited by 1,133
Cited by
Hossain, M. J., Al‐Mamun, M., & Islam, M. R. (2024) · Health Science Reports · doi:10.1002/hsr2.2004 · Cited by 928
Risks and burdens of incident diabetes in long COVID: a cohort study
Xie, Y., & Al-Aly, Z. (2022) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(22)00044-4 · Cited by 564
Khunti, K., Aroda, V. R., Bhatt, D. L., Bozkurt, B., Buse, J. B., Heerspink, H. L., Inzucchi, S. E., Lam, C. S. P., Marx, N., McMurray, J. J. V., et al. (2022) · Diabetes, Obesity and Metabolism · doi:10.1111/dom.14805 · Cited by 37
Self-citation
Metadata
- Authors
- Steenblock, C., Schwarz, P. E. H., Ludwig, B., Linkermann, A., Zimmet, P., Kulebyakin, K., Tkachuk, V. A., Markov, A. G., Lehnert, H., de Angelis, M. H., Rietzsch, H., Rodionov, R. N., Khunti, K., Hopkins, D., Birkenfeld, A. L., Boehm, B., Holt, R. I. G., Skyler, J. S., DeVries, J. H., Renard, E., Eckel, R. H., Alberti, K. G. M. M., Geloneze, B., Chan, J. C., Mbanya, J. C., Onyegbutulem, H. C., Ramachandran, A., Basit, A., Hassanein, M., Bewick, G., Spinas, G. A., Beuschlein, F., Landgraf, R., Rubino, F., Mingrone, G., & Bornstein, S. R.
- Venue
- The Lancet Diabetes & Endocrinology
- Publisher
- Elsevier BV
- Published
- 2021-11
- Volume
- 9
- Issue
- 11
- Pages
- 786-798
- ISSN
- 2213-8587 (ISSN-L)
- OpenAlex
- W3202042764
- Cited by
- 246
- References
- 18
- FWCI
- 14.51
- 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: COVID-19 and metabolic disease: mechanisms and clinical management. https://app.cochat.ai/papers/10.1016/s2213-8587(21)00244-8
- The paper
- Steenblock, C., Schwarz, P. E. H., Ludwig, B., Linkermann, A., Zimmet, P., Kulebyakin, K., Tkachuk, V. A., Markov, A. G., Lehnert, H., de Angelis, M. H., Rietzsch, H., Rodionov, R. N., Khunti, K., Hopkins, D., Birkenfeld, A. L., Boehm, B., Holt, R. I. G., Skyler, J. S., DeVries, J. H., . . . Bornstein, S. R. (2021). COVID-19 and metabolic disease: mechanisms and clinical management. The Lancet Diabetes & Endocrinology. https://doi.org/10.1016/s2213-8587(21)00244-8
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.
