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Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus
We investigated segmental phase angles (PAs) in the four limbs using a multi-frequency bioimpedance analysis (MF-BIA) technique for noninvasively diagnosing diabetes mellitus. We conducted a meal tolerance test (MTT) for 45 diabetic and 45 control subjects stratified by age, sex and body mass index...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766497/ https://www.ncbi.nlm.nih.gov/pubmed/29330426 http://dx.doi.org/10.1038/s41598-017-18913-7 |
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author | Jun, Min-Ho Kim, Soochan Ku, Boncho Cho, JungHee Kim, Kahye Yoo, Ho-Ryong Kim, Jaeuk U. |
author_facet | Jun, Min-Ho Kim, Soochan Ku, Boncho Cho, JungHee Kim, Kahye Yoo, Ho-Ryong Kim, Jaeuk U. |
author_sort | Jun, Min-Ho |
collection | PubMed |
description | We investigated segmental phase angles (PAs) in the four limbs using a multi-frequency bioimpedance analysis (MF-BIA) technique for noninvasively diagnosing diabetes mellitus. We conducted a meal tolerance test (MTT) for 45 diabetic and 45 control subjects stratified by age, sex and body mass index (BMI). HbA1c and the waist-to-hip-circumference ratio (WHR) were measured before meal intake, and we measured the glucose levels and MF-BIA PAs 5 times for 2 hours after meal intake. We employed a t-test to examine the statistical significance and the area under the curve (AUC) of the receiver operating characteristics (ROC) to test the classification accuracy using segmental PAs at 5, 50, and 250 kHz. Segmental PAs were independent of the HbA1c or glucose levels, or their changes caused by the MTT. However, the segmental PAs were good indicators for noninvasively screening diabetes In particular, leg PAs in females and arm PAs in males showed best classification accuracy (AUC = 0.827 for males, AUC = 0.845 for females). Lastly, we introduced the PA at maximum reactance (PAmax), which is independent of measurement frequencies and can be obtained from any MF-BIA device using a Cole-Cole model, thus showing potential as a useful biomarker for diabetes. |
format | Online Article Text |
id | pubmed-5766497 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57664972018-01-17 Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus Jun, Min-Ho Kim, Soochan Ku, Boncho Cho, JungHee Kim, Kahye Yoo, Ho-Ryong Kim, Jaeuk U. Sci Rep Article We investigated segmental phase angles (PAs) in the four limbs using a multi-frequency bioimpedance analysis (MF-BIA) technique for noninvasively diagnosing diabetes mellitus. We conducted a meal tolerance test (MTT) for 45 diabetic and 45 control subjects stratified by age, sex and body mass index (BMI). HbA1c and the waist-to-hip-circumference ratio (WHR) were measured before meal intake, and we measured the glucose levels and MF-BIA PAs 5 times for 2 hours after meal intake. We employed a t-test to examine the statistical significance and the area under the curve (AUC) of the receiver operating characteristics (ROC) to test the classification accuracy using segmental PAs at 5, 50, and 250 kHz. Segmental PAs were independent of the HbA1c or glucose levels, or their changes caused by the MTT. However, the segmental PAs were good indicators for noninvasively screening diabetes In particular, leg PAs in females and arm PAs in males showed best classification accuracy (AUC = 0.827 for males, AUC = 0.845 for females). Lastly, we introduced the PA at maximum reactance (PAmax), which is independent of measurement frequencies and can be obtained from any MF-BIA device using a Cole-Cole model, thus showing potential as a useful biomarker for diabetes. Nature Publishing Group UK 2018-01-12 /pmc/articles/PMC5766497/ /pubmed/29330426 http://dx.doi.org/10.1038/s41598-017-18913-7 Text en © The Author(s) 2018 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Jun, Min-Ho Kim, Soochan Ku, Boncho Cho, JungHee Kim, Kahye Yoo, Ho-Ryong Kim, Jaeuk U. Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
title | Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
title_full | Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
title_fullStr | Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
title_full_unstemmed | Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
title_short | Glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
title_sort | glucose-independent segmental phase angles from multi-frequency bioimpedance analysis to discriminate diabetes mellitus |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5766497/ https://www.ncbi.nlm.nih.gov/pubmed/29330426 http://dx.doi.org/10.1038/s41598-017-18913-7 |
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