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Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis
BACKGROUND: Moyamoya disease can lead to stroke with devastating consequences, it is necessary to find a non-invasive and effective approach to identify the occurrence of stroke. In this study, we aim to analyze the association between ultrasound parameters and ipsilateral cerebral hemisphere stroke...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9555074/ https://www.ncbi.nlm.nih.gov/pubmed/36221122 http://dx.doi.org/10.1186/s41016-022-00300-5 |
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author | Zheng, Shuai Wang, Fumin Cheng, Linggang Li, Rui Zhang, Dong He, Wen Zhang, Wei |
author_facet | Zheng, Shuai Wang, Fumin Cheng, Linggang Li, Rui Zhang, Dong He, Wen Zhang, Wei |
author_sort | Zheng, Shuai |
collection | PubMed |
description | BACKGROUND: Moyamoya disease can lead to stroke with devastating consequences, it is necessary to find a non-invasive and effective approach to identify the occurrence of stroke. In this study, we aim to analyze the association between ultrasound parameters and ipsilateral cerebral hemisphere stroke in patients with moyamoya disease by logistic regression analysis. METHODS: In this retrospective case–control study, 88 patients with MMD (153 cerebral hemispheres) hospitalized in Beijing Tiantan Hospital, Capital Medical University from November 2020 to October 2021 were analyzed. According to the occurrence of stroke, the 153 cerebral hemispheres were divided into a stroke group and a non-stroke group. Clinical data and ultrasound parameters of the ipsilateral internal carotid artery, superficial temporal artery, maxillary artery, and posterior cerebral artery were recorded. The ultrasound parameters were divided into four groups according to interquartile range, and then they were compared between the stroke group and the non-stroke group. Those with significant differences were scored by multivariate logistic regression analysis. RESULTS: There were 75 cerebral hemispheres (49.0%) in the stroke group and 78 cerebral hemispheres (51.0%) in the non-stroke group. Logistic regression analysis showed that the internal diameter of the internal carotid artery, peak systolic velocity of the internal carotid artery and peak systolic velocity of the posterior cerebral artery were independently correlated factors for stroke in patients with MMD. The fourth quartile group of the above three ultrasound parameters was taken as the reference group, and the odds ratio of the first quartile group were 11.679 (95% CI 2.918–46.749, P = 0.001), 19.594 (95% CI 4.973–77.193, P < 0.001), and 11.657 (95% CI 3.221–42.186, P < 0.001), respectively. CONCLUSION: Ultrasound parameters are independently correlated with ipsilateral cerebral stroke in patients with MMD. Ultrasound provides a new way to identify stroke in MMD patients. Future prospective cohort studies are needed to verify the clinical value of ultrasound in identifying patients with MMD at high risk of stroke. |
format | Online Article Text |
id | pubmed-9555074 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-95550742022-10-13 Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis Zheng, Shuai Wang, Fumin Cheng, Linggang Li, Rui Zhang, Dong He, Wen Zhang, Wei Chin Neurosurg J Research BACKGROUND: Moyamoya disease can lead to stroke with devastating consequences, it is necessary to find a non-invasive and effective approach to identify the occurrence of stroke. In this study, we aim to analyze the association between ultrasound parameters and ipsilateral cerebral hemisphere stroke in patients with moyamoya disease by logistic regression analysis. METHODS: In this retrospective case–control study, 88 patients with MMD (153 cerebral hemispheres) hospitalized in Beijing Tiantan Hospital, Capital Medical University from November 2020 to October 2021 were analyzed. According to the occurrence of stroke, the 153 cerebral hemispheres were divided into a stroke group and a non-stroke group. Clinical data and ultrasound parameters of the ipsilateral internal carotid artery, superficial temporal artery, maxillary artery, and posterior cerebral artery were recorded. The ultrasound parameters were divided into four groups according to interquartile range, and then they were compared between the stroke group and the non-stroke group. Those with significant differences were scored by multivariate logistic regression analysis. RESULTS: There were 75 cerebral hemispheres (49.0%) in the stroke group and 78 cerebral hemispheres (51.0%) in the non-stroke group. Logistic regression analysis showed that the internal diameter of the internal carotid artery, peak systolic velocity of the internal carotid artery and peak systolic velocity of the posterior cerebral artery were independently correlated factors for stroke in patients with MMD. The fourth quartile group of the above three ultrasound parameters was taken as the reference group, and the odds ratio of the first quartile group were 11.679 (95% CI 2.918–46.749, P = 0.001), 19.594 (95% CI 4.973–77.193, P < 0.001), and 11.657 (95% CI 3.221–42.186, P < 0.001), respectively. CONCLUSION: Ultrasound parameters are independently correlated with ipsilateral cerebral stroke in patients with MMD. Ultrasound provides a new way to identify stroke in MMD patients. Future prospective cohort studies are needed to verify the clinical value of ultrasound in identifying patients with MMD at high risk of stroke. BioMed Central 2022-10-11 /pmc/articles/PMC9555074/ /pubmed/36221122 http://dx.doi.org/10.1186/s41016-022-00300-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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. |
spellingShingle | Research Zheng, Shuai Wang, Fumin Cheng, Linggang Li, Rui Zhang, Dong He, Wen Zhang, Wei Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
title | Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
title_full | Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
title_fullStr | Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
title_full_unstemmed | Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
title_short | Ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
title_sort | ultrasound parameters associated with stroke in patients with moyamoya disease: a logistic regression analysis |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9555074/ https://www.ncbi.nlm.nih.gov/pubmed/36221122 http://dx.doi.org/10.1186/s41016-022-00300-5 |
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