The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
COVID-19 and Venous Thromboembolism: A Meta-analysis of Literature Studies
Open accessAbstract
Coronavirus disease 2019 (COVID-19) may have a wide spectrum of clinical presentations, leading in some cases to a critical condition with poor long-term outcomes and residual disability requiring post-acute rehabilitation. A major concern in severe COVID-19 is represented by a concomitant prothrombotic state. However, contrasting data are available about the prevalence of venous thromboembolism (VTE), including deep vein thrombosis (DVT) and/or pulmonary embolism (PE). A detailed search on the association of COVID-19 with thromboembolic complications was conducted in the main electronic databases (PubMed, Web of Science, and Scopus) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The weighted mean prevalence (WMP) with 95% confidence interval (95% CI) was calculated with the random-effects model. Twenty studies enrolling 1,988 COVID-19 patients were included. The WMP of VTE was 31.3% (95% CI: 24.3–39.2%). The WMP of DVT was 19.8% (95% CI: 10.5–34.0%), whereas the WMP of PE was 18.9% (95% CI: 14.4–24.3%). Similar results were obtained when specifically analyzing studies on patients admitted to intensive care units and those on patients under antithrombotic prophylaxis. Regression models showed that an increasing age was associated with a higher prevalence of VTE (Z-score: 3.11, p = 0.001), DVT (Z-score: 2.33, p = 0.002), and PE (Z-score: 3.03, p = 0.002), while an increasing body mass index was associated with an increasing prevalence of PE (Z-score = 2.01, p = 0.04). Male sex did not impact the evaluated outcomes. The rate of thromboembolic complications in COVID-19 patients is definitely high. Considering the risk of fatal and disabling complications, adequate screening procedures and antithrombotic strategies should be implemented.
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Preferred Reporting Items for Systematic Reviews and Meta-Analyses: the PRISMA statement
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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
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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
A novel coronavirus from patients with pneumonia in China, 2019
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Cited by
Heart Disease and Stroke Statistics—2023 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Anderson, C. A. M., Arora, P., Avery, C. L., Baker-Smith, C. M., Beaton, A. Z., Boehme, A. K., Buxton, A. E., et al. (2023) · Circulation · doi:10.1161/cir.0000000000001123 · Cited by 8,300
Heart Disease and Stroke Statistics—2022 Update: A Report From the American Heart Association
Tsao, C. W., Aday, A. W., Almarzooq, Z. I., Alonso, A., Beaton, A. Z., Bittencourt, M. S., Boehme, A. K., Buxton, A. E., Carson, A. P., Commodore-Mensah, Y., et al. (2022) · Circulation · doi:10.1161/cir.0000000000001052 · Cited by 5,987
Thrombotic complications of COVID-19
Avila, J., Long, B., Holladay, D., & Gottlieb, M. (2021) · The American Journal of Emergency Medicine · doi:10.1016/j.ajem.2020.09.065 · Cited by 143
Metadata
- Authors
- Di Minno, A., Ambrosino, P., Calcaterra, I., & Di Minno, M. N. D.
- Venue
- Seminars in Thrombosis and Hemostasis
- Publisher
- Georg Thieme Verlag KG
- Published
- 2020-09-03
- Volume
- 46
- Issue
- 07
- Pages
- 763-771
- ISSN
- 0094-6176 (ISSN-L)
- 1098-9064
- OpenAlex
- W3081791594
- Cited by
- 300
- References
- 51
- FWCI
- 12.03
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Di Minno, A., Ambrosino, P., Calcaterra, I., & Di Minno, M. N. D. (2020). COVID-19 and Venous Thromboembolism: A Meta-analysis of Literature Studies. Seminars in Thrombosis and Hemostasis. https://doi.org/10.1055/s-0040-1715456
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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.