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Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula
BACKGROUND: Central venous stenosis (CVS) of radiocephalic arteriovenous fistula (RCAVF) affects RCAVF function and longevity. Ultrasound screening for CVS is limited by acoustic window. Herein, we analyzed the quantitative axillary venous (AxV) spectrum in hemodialysis patients via RCAVF, and const...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
AME Publishing Company
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848436/ https://www.ncbi.nlm.nih.gov/pubmed/35282095 http://dx.doi.org/10.21037/atm-22-160 |
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author | Xu, Xiang Zhuang, Yong Zeng, Jinshu Cai, Fanggang He, Tianmin Wu, Jie Chen, Caiming Zou, Zhenhuan Zhang, Xiaohong Lv, Guorong |
author_facet | Xu, Xiang Zhuang, Yong Zeng, Jinshu Cai, Fanggang He, Tianmin Wu, Jie Chen, Caiming Zou, Zhenhuan Zhang, Xiaohong Lv, Guorong |
author_sort | Xu, Xiang |
collection | PubMed |
description | BACKGROUND: Central venous stenosis (CVS) of radiocephalic arteriovenous fistula (RCAVF) affects RCAVF function and longevity. Ultrasound screening for CVS is limited by acoustic window. Herein, we analyzed the quantitative axillary venous (AxV) spectrum in hemodialysis patients via RCAVF, and constructed central venous stenosis index (CVSI) model based on the spectrum parameters to early detect resting asymptomatic CVS. METHODS: From August 2017 to May 2021, stage 5 chronic kidney disease (CKD) patients dialysed via RCAVF at the First Affiliated Hospital of Fujian Medical University were included in this study. No CVS-related symptoms were found and the pulsation at the arteriovenous anastomosis was normal. However, the patients had the sensation of swelling in the ipsilateral upper limb during dialysis; the venous pressure advanced upon the completion of dialysis; or both (n=52). The inclusion criteria were as follows: (I) Ultrasound (US) showed that the temporal phases of the AxV spectrum were “normal”; and (II) CVS was confirmed by digital subtraction angiography (DSA). The exclusion criteria were as follows: (I) stent placement; (II) multiple stenosis; and (III) placement of central venous catheter. A total of 37 patients participated in the analysis. Eighteen patients were included in the CVS group, and 19 cases without CVS were included in the control group. Independent sample t-test was used to screen each parameter of the AxV spectrum, and a CVSI model was constructed by principal component analysis (PCA). The receiver operating characteristic curve (ROC) was applied to analyze the diagnostic value of CVSI. RESULTS: According to the independent sample t-test, 9 parameters were found to have statistical significance (all P<0.05); they were analyzed by PCA, and the CVSI model was constructed. The ROC showed that CVSI had diagnostic value for CVS. When the cut-off value of CVSI was 7.13, the maximum value of the Youden index was 0.842, with a sensitivity of 100% and a specificity of 84.2%. CONCLUSIONS: The CVSI helps to early detect resting asymptomatic CVS and dramatically increases the detection rate of CVS. |
format | Online Article Text |
id | pubmed-8848436 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | AME Publishing Company |
record_format | MEDLINE/PubMed |
spelling | pubmed-88484362022-03-10 Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula Xu, Xiang Zhuang, Yong Zeng, Jinshu Cai, Fanggang He, Tianmin Wu, Jie Chen, Caiming Zou, Zhenhuan Zhang, Xiaohong Lv, Guorong Ann Transl Med Original Article BACKGROUND: Central venous stenosis (CVS) of radiocephalic arteriovenous fistula (RCAVF) affects RCAVF function and longevity. Ultrasound screening for CVS is limited by acoustic window. Herein, we analyzed the quantitative axillary venous (AxV) spectrum in hemodialysis patients via RCAVF, and constructed central venous stenosis index (CVSI) model based on the spectrum parameters to early detect resting asymptomatic CVS. METHODS: From August 2017 to May 2021, stage 5 chronic kidney disease (CKD) patients dialysed via RCAVF at the First Affiliated Hospital of Fujian Medical University were included in this study. No CVS-related symptoms were found and the pulsation at the arteriovenous anastomosis was normal. However, the patients had the sensation of swelling in the ipsilateral upper limb during dialysis; the venous pressure advanced upon the completion of dialysis; or both (n=52). The inclusion criteria were as follows: (I) Ultrasound (US) showed that the temporal phases of the AxV spectrum were “normal”; and (II) CVS was confirmed by digital subtraction angiography (DSA). The exclusion criteria were as follows: (I) stent placement; (II) multiple stenosis; and (III) placement of central venous catheter. A total of 37 patients participated in the analysis. Eighteen patients were included in the CVS group, and 19 cases without CVS were included in the control group. Independent sample t-test was used to screen each parameter of the AxV spectrum, and a CVSI model was constructed by principal component analysis (PCA). The receiver operating characteristic curve (ROC) was applied to analyze the diagnostic value of CVSI. RESULTS: According to the independent sample t-test, 9 parameters were found to have statistical significance (all P<0.05); they were analyzed by PCA, and the CVSI model was constructed. The ROC showed that CVSI had diagnostic value for CVS. When the cut-off value of CVSI was 7.13, the maximum value of the Youden index was 0.842, with a sensitivity of 100% and a specificity of 84.2%. CONCLUSIONS: The CVSI helps to early detect resting asymptomatic CVS and dramatically increases the detection rate of CVS. AME Publishing Company 2022-01 /pmc/articles/PMC8848436/ /pubmed/35282095 http://dx.doi.org/10.21037/atm-22-160 Text en 2022 Annals of Translational Medicine. All rights reserved. https://creativecommons.org/licenses/by-nc-nd/4.0/Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) . |
spellingShingle | Original Article Xu, Xiang Zhuang, Yong Zeng, Jinshu Cai, Fanggang He, Tianmin Wu, Jie Chen, Caiming Zou, Zhenhuan Zhang, Xiaohong Lv, Guorong Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
title | Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
title_full | Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
title_fullStr | Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
title_full_unstemmed | Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
title_short | Value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
title_sort | value of a quantitative model of axillary venous blood flow spectrum for the detection of central venous stenosis in patients undergoing hemodialysis via radiocephalic arteriovenous fistula |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8848436/ https://www.ncbi.nlm.nih.gov/pubmed/35282095 http://dx.doi.org/10.21037/atm-22-160 |
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