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Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis

OBJECTIVE: This study aims to establish the predictive model of carotid plaque formation and carotid plaque location by retrospectively analyzing the clinical data of subjects with carotid plaque formation and normal people, and to provide technical support for screening patients with carotid plaque...

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Autores principales: Hu, Jian, Su, Fan, Ren, Xia, Cao, Lei, Zhou, Yumei, Fu, Yuhan, Tatenda, Grace, Jiang, Mingfei, Wu, Huan, Wen, Yufeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377085/
https://www.ncbi.nlm.nih.gov/pubmed/35965318
http://dx.doi.org/10.1186/s12872-022-02806-3
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author Hu, Jian
Su, Fan
Ren, Xia
Cao, Lei
Zhou, Yumei
Fu, Yuhan
Tatenda, Grace
Jiang, Mingfei
Wu, Huan
Wen, Yufeng
author_facet Hu, Jian
Su, Fan
Ren, Xia
Cao, Lei
Zhou, Yumei
Fu, Yuhan
Tatenda, Grace
Jiang, Mingfei
Wu, Huan
Wen, Yufeng
author_sort Hu, Jian
collection PubMed
description OBJECTIVE: This study aims to establish the predictive model of carotid plaque formation and carotid plaque location by retrospectively analyzing the clinical data of subjects with carotid plaque formation and normal people, and to provide technical support for screening patients with carotid plaque. METHODS: There were 4300 subjects in the ultrasound department of Maanshan People's Hospital collected from December 2013 to December 2018. We used demographic and biochemical data from 3700 subjects to establish predictive models for carotid plaque and its location. The leave-one-out cross-validated classification, 600 external data validation, and area under the receiver operating characteristic curve (AUC) were used to verify the accuracy, sensitivity, specificity, and application value of the model. RESULTS: There were significant difference of age (F = − 34.049, p < 0.01), hypertension (χ(2) = 191.067, p < 0.01), smoking (χ(2) = 4.762, p < 0.05) and alcohol (χ(2) = 8.306, p < 0.01), Body mass index (F = 15.322, p < 0.01), High-density lipoprotein (HDL) (F = 13.840, p < 0.01), Lipoprotein a (Lp a) (F = 52.074, p < 0.01), Blood Urea Nitrogen (F = 2.679, p < 0.01) among five groups. Prediction models were built: carotid plaque prediction model (Model CP); Prediction model of left carotid plaque only (Model CP Left); Prediction model of right carotid plaque only (Model CP Right). Prediction model of bilateral carotid plaque (Model CP Both). Model CP (Wilks' lambda = 0.597, p < 0.001, accuracy = 78.50%, sensitivity = 78.07%, specificity = 79.07%, AUC = 0.917). Model CP Left (Wilks' lambda = 0.605, p < 0.001, accuracy = 79.00%, sensitivity = 86.17%, specificity = 72.70%, AUC = 0.880). Model CP Right (Wilks' lambda = 0.555, p < 0.001, accuracy = 83.00%, sensitivity = 81.82%, specificity = 84.44%, AUC = 0.880). Model CP Both (Wilks' lambda = 0.651, p < 0.001, accuracy = 82.30%, sensitivity = 89.50%, specificity = 72.70%, AUC = 0.880). CONCLUSION: Demographic characteristics and blood biochemical indexes were used to establish the carotid plaque and its location discriminant models based on Fisher discriminant analysis (FDA), which has high application value in community screening. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-022-02806-3.
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spelling pubmed-93770852022-08-16 Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis Hu, Jian Su, Fan Ren, Xia Cao, Lei Zhou, Yumei Fu, Yuhan Tatenda, Grace Jiang, Mingfei Wu, Huan Wen, Yufeng BMC Cardiovasc Disord Research OBJECTIVE: This study aims to establish the predictive model of carotid plaque formation and carotid plaque location by retrospectively analyzing the clinical data of subjects with carotid plaque formation and normal people, and to provide technical support for screening patients with carotid plaque. METHODS: There were 4300 subjects in the ultrasound department of Maanshan People's Hospital collected from December 2013 to December 2018. We used demographic and biochemical data from 3700 subjects to establish predictive models for carotid plaque and its location. The leave-one-out cross-validated classification, 600 external data validation, and area under the receiver operating characteristic curve (AUC) were used to verify the accuracy, sensitivity, specificity, and application value of the model. RESULTS: There were significant difference of age (F = − 34.049, p < 0.01), hypertension (χ(2) = 191.067, p < 0.01), smoking (χ(2) = 4.762, p < 0.05) and alcohol (χ(2) = 8.306, p < 0.01), Body mass index (F = 15.322, p < 0.01), High-density lipoprotein (HDL) (F = 13.840, p < 0.01), Lipoprotein a (Lp a) (F = 52.074, p < 0.01), Blood Urea Nitrogen (F = 2.679, p < 0.01) among five groups. Prediction models were built: carotid plaque prediction model (Model CP); Prediction model of left carotid plaque only (Model CP Left); Prediction model of right carotid plaque only (Model CP Right). Prediction model of bilateral carotid plaque (Model CP Both). Model CP (Wilks' lambda = 0.597, p < 0.001, accuracy = 78.50%, sensitivity = 78.07%, specificity = 79.07%, AUC = 0.917). Model CP Left (Wilks' lambda = 0.605, p < 0.001, accuracy = 79.00%, sensitivity = 86.17%, specificity = 72.70%, AUC = 0.880). Model CP Right (Wilks' lambda = 0.555, p < 0.001, accuracy = 83.00%, sensitivity = 81.82%, specificity = 84.44%, AUC = 0.880). Model CP Both (Wilks' lambda = 0.651, p < 0.001, accuracy = 82.30%, sensitivity = 89.50%, specificity = 72.70%, AUC = 0.880). CONCLUSION: Demographic characteristics and blood biochemical indexes were used to establish the carotid plaque and its location discriminant models based on Fisher discriminant analysis (FDA), which has high application value in community screening. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12872-022-02806-3. BioMed Central 2022-08-15 /pmc/articles/PMC9377085/ /pubmed/35965318 http://dx.doi.org/10.1186/s12872-022-02806-3 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
Hu, Jian
Su, Fan
Ren, Xia
Cao, Lei
Zhou, Yumei
Fu, Yuhan
Tatenda, Grace
Jiang, Mingfei
Wu, Huan
Wen, Yufeng
Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis
title Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis
title_full Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis
title_fullStr Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis
title_full_unstemmed Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis
title_short Prediction of carotid plaque by blood biochemical indices and related factors based on Fisher discriminant analysis
title_sort prediction of carotid plaque by blood biochemical indices and related factors based on fisher discriminant analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9377085/
https://www.ncbi.nlm.nih.gov/pubmed/35965318
http://dx.doi.org/10.1186/s12872-022-02806-3
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