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Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study
Screening and diagnosing abdominal aortic aneurysms (AAA) are currently dependent on imaging studies such as ultrasound or computed tomography angiography. All imaging studies offer distinct advantages but also suffer from inherent limitations such as examiner dependency or ionizing radiation. Bioel...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10253797/ https://www.ncbi.nlm.nih.gov/pubmed/37297921 http://dx.doi.org/10.3390/jcm12113726 |
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author | Hofmann, Amun G. Shoumariyeh, Tarik Domenig, Christoph Skrabal, Falko Kovarik, Johannes J. |
author_facet | Hofmann, Amun G. Shoumariyeh, Tarik Domenig, Christoph Skrabal, Falko Kovarik, Johannes J. |
author_sort | Hofmann, Amun G. |
collection | PubMed |
description | Screening and diagnosing abdominal aortic aneurysms (AAA) are currently dependent on imaging studies such as ultrasound or computed tomography angiography. All imaging studies offer distinct advantages but also suffer from inherent limitations such as examiner dependency or ionizing radiation. Bioelectrical impedance analysis has previously been investigated with respect to its use in the detection of several cardiovascular and renal pathologies. The present pilot study assessed the feasibility of AAA detection based on bioimpedance analysis. In this single-center exploratory pilot study, measurements were conducted among three different cohorts: patients with AAA, end-stage renal disease patients without AAA, and healthy controls. The device used in the study, CombynECG, is an open-market accessible device for segmental bioelectrical impedance analysis. The data was preprocessed and used to train four different machine learning models on a randomized training sample (80% of the full dataset). Each model was then evaluated on a test set (20% of the full dataset). The total sample included 22 patients with AAA, 16 chronic kidney disease patients, and 23 healthy controls. All four models showed strong predictive performance in the test partitions. Specificity ranged from 71.4 to 100%, while sensitivity ranged from 66.7 to 100%. The best-performing model had 100% accuracy for classification when applied to the test sample. Additionally, an exploratory analysis to approximate the maximum AAA diameter was conducted. An association analysis revealed several impedance parameters that might possess predictive ability with respect to aneurysm size. AAA detection via bioelectrical impedance analysis is technically feasible and appears to be a promising technology for large-scale clinical studies and routine clinical screening assessments. |
format | Online Article Text |
id | pubmed-10253797 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102537972023-06-10 Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study Hofmann, Amun G. Shoumariyeh, Tarik Domenig, Christoph Skrabal, Falko Kovarik, Johannes J. J Clin Med Article Screening and diagnosing abdominal aortic aneurysms (AAA) are currently dependent on imaging studies such as ultrasound or computed tomography angiography. All imaging studies offer distinct advantages but also suffer from inherent limitations such as examiner dependency or ionizing radiation. Bioelectrical impedance analysis has previously been investigated with respect to its use in the detection of several cardiovascular and renal pathologies. The present pilot study assessed the feasibility of AAA detection based on bioimpedance analysis. In this single-center exploratory pilot study, measurements were conducted among three different cohorts: patients with AAA, end-stage renal disease patients without AAA, and healthy controls. The device used in the study, CombynECG, is an open-market accessible device for segmental bioelectrical impedance analysis. The data was preprocessed and used to train four different machine learning models on a randomized training sample (80% of the full dataset). Each model was then evaluated on a test set (20% of the full dataset). The total sample included 22 patients with AAA, 16 chronic kidney disease patients, and 23 healthy controls. All four models showed strong predictive performance in the test partitions. Specificity ranged from 71.4 to 100%, while sensitivity ranged from 66.7 to 100%. The best-performing model had 100% accuracy for classification when applied to the test sample. Additionally, an exploratory analysis to approximate the maximum AAA diameter was conducted. An association analysis revealed several impedance parameters that might possess predictive ability with respect to aneurysm size. AAA detection via bioelectrical impedance analysis is technically feasible and appears to be a promising technology for large-scale clinical studies and routine clinical screening assessments. MDPI 2023-05-28 /pmc/articles/PMC10253797/ /pubmed/37297921 http://dx.doi.org/10.3390/jcm12113726 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Hofmann, Amun G. Shoumariyeh, Tarik Domenig, Christoph Skrabal, Falko Kovarik, Johannes J. Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study |
title | Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study |
title_full | Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study |
title_fullStr | Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study |
title_full_unstemmed | Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study |
title_short | Abdominal Aortic Aneurysm Detection in Bioelectrical Impedance Cardiovascular Screenings—A Pilot Study |
title_sort | abdominal aortic aneurysm detection in bioelectrical impedance cardiovascular screenings—a pilot study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10253797/ https://www.ncbi.nlm.nih.gov/pubmed/37297921 http://dx.doi.org/10.3390/jcm12113726 |
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