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. 2022 May 18;8:12. doi: 10.1186/s40959-022-00137-y

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 1 — Forest Plot of Analysis of Multiple Clinical Variables and the Likelihood of stroke/TIA Occurring in Cancer Patients. Multivariate analysis was carried out using conditional logistic regression to study the effects of the clinical variables on the likelihood of having Stroke/TIA. The points represent the Odds Ratio, and the lines represent the 95% confidence interval. Points in blue represent an OR >1 indicating that cases with Stroke/TIA are more likely to have the corresponding clinical characteristic. Lines (CIs) which do not cross the null value of 1 represent statistical significance