Evaluation of a Minimally Invasive System for Measuring Glucose Area under the Curve during Oral Glucose Tolerance Tests: Usefulness of Sweat Monitoring for Precise Measurement
Open accessAbstract
Aims: We developed a system for measuring glucose area under the curve (AUC) using minimally invasive interstitial fluid extraction technology (MIET). Sweat contamination during interstitial fluid glucose (IG) extraction affects the accuracy of glucose AUC measurement, because this technology uses extracted sodium ion levels as an internal standard. Therefore, we developed a sweat monitoring patch to reduce this effect and investigated its efficacy in volunteers undergoing oral glucose tolerance tests (OGTTs). Materials and Methods: Fifty diabetes mellitus inpatients and 10 healthy subjects undergoing the 75 g OGTT were included. Two sites on the forearm were pretreated with microneedle arrays, then hydrogels for interstitial fluid extraction were placed on the treated sites. Simultaneously, hydrogels for sweat monitoring were placed on untreated sites near the treated sites. Plasma glucose (PG) levels were measured every 30 min for 2 h to calculate reference AUC values. Using MIET, IG AUC was calculated from extracted glucose and sodium ion levels after attachment of the hydrogel for 2 h. Results: Good correlation between IG AUC measurements using MIET and reference AUCs measured using PG levels was confirmed over a wide AUC range (202–610 mg/h/dl) after correction for the sweat-induced error detected by the hydrogel patches on the nonpretreated skin. Strong correlation between IG AUC and peak glucose levels indicates that glucose spikes can be easily detected by this system. Conclusion: We confirmed the effectiveness of a sweat monitoring patch for precise AUC measurement using MIET. This novel, easy-to-use system has potential for glucose excursion evaluation in daily clinical practice.
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Although several studies have indicated that sweat glucose concentrations can correlate with concurrent blood levels, the limitations of uncontrolled conditions, contamination, irregular sampling, and low volumes can significantly impact the accuracy of collected data.
“Although several studies have indicated that sweat glucose concentrations can correlate with concurrent blood levels, these limitations can significantly impact the accuracy of collected data 64, 76,77.”
From Wearable biosensors for healthcare monitoring (2019) · cites this paper as [77]
Accurate measurement of physiologically relevant sweat glucose concentrations with epidermal biosensors faces major challenges related to uncontrolled operational conditions, glucose contamination, irregular sampling rates, and low sampling volumes.
“The accurate measurement of physiologically relevant sweat glucose concentrations with epidermal biosensors faces several major challenges related to uncontrolled operational conditions (e.g., varying temperature and pH), glucose contamination from various sources, irregular sampling rates, and low sampling volumes.”
From Wearable biosensors for healthcare monitoring (2019) · cites this paper as [77]
Cites
Inzucchi, S. E., Bergenstal, R. M., Buse, J. B., Diamant, M., Ferrannini, E., Nauck, M., Peters, A. L., Tsapas, A., Wender, R., & Matthews, D. R. (2012) · Diabetologia · doi:10.1007/s00125-012-2534-0 · Cited by 3,919 · see citing works
Management of Hyperglycemia in Type 2 Diabetes: A Patient-Centered Approach
Inzucchi, S. E., Bergenstal, R. M., Buse, J. B., Diamant, M., Ferrannini, E., Nauck, M., Peters, A. L., Tsapas, A., Wender, R., & Matthews, D. R. (2012) · Diabetes Care · doi:10.2337/dc12-0413 · Cited by 3,207 · see citing works
Basevi, V., Mario, S. D., Morciano, C., Nonino, F., & Magrini, N. (2011) · Diabetes Care · doi:10.2337/dc11-0174 · Cited by 3,058 · see citing works
Acarbose for prevention of type 2 diabetes mellitus: the STOP-NIDDM randomised trial
Chiasson, J.-L., Josse, R. G., Gomis, R., Hanefeld, M., Karasik, A., & Laakso, M. (2002) · The Lancet · doi:10.1016/s0140-6736(02)08905-5 · Cited by 2,543 · see citing works
Standards of Medical Care in Diabetes—2012
(2012) · Diabetes Care · doi:10.2337/dc12-s011 · Cited by 2,240 · see citing works
Kashiwagi, A., Kasuga, M., Araki, E., Oka, Y., Hanafusa, T., Ito, H., Tominaga, M., Oikawa, S., Noda, M., Kawamura, T., et al. (2012) · Journal of Diabetes Investigation · doi:10.1111/j.2040-1124.2012.00207.x · Cited by 902 · see citing works
Self-citationHanefeld, M., Fischer, S., Julius, U., Schulze, J., Schwanebeck, U., Schmechel, H., Ziegelasch, H. J., & Lindner, J. (1996) · Diabetologia · doi:10.1007/s001250050617 · Cited by 873 · see citing works
Hanefeld, M. (2004) · European Heart Journal · doi:10.1016/s0195-668x(03)00468-8 · Cited by 641 · see citing works
Correlation Between Sweat Glucose and Blood Glucose in Subjects with Diabetes
Moyer, J., Wilson, D., Finkelshtein, I., Wong, B., & Potts, R. (2012) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2011.0262 · Cited by 570 · see citing works
The DECODE Study Group, & on behalf of the European Diabetes Epidemiology Group (2003) · Diabetes Care · doi:10.2337/diacare.26.3.688 · Cited by 516 · see citing works
Glucose Variability; Does It Matter?
Siegelaar, S. E., Holleman, F., Hoekstra, J. B. L., & DeVries, J. H. (2010) · Endocrine Reviews · doi:10.1210/er.2009-0021 · Cited by 409 · see citing works
the DECODA Study Group, & Nakagami, T. (2004) · Diabetologia · doi:10.1007/s00125-004-1334-6 · Cited by 331 · see citing works
Technologies for Continuous Glucose Monitoring: Current Problems and Future Promises
Vaddiraju, S., Burgess, D. J., Tomazos, I., Jain, F. C., & Papadimitrakopoulos, F. (2010) · Journal of Diabetes Science and Technology · doi:10.1177/193229681000400632 · Cited by 285 · see citing works
Kashiwagi, A. (2012) · Medical Entomology and Zoology · Cited by 211 · see citing works
Self-citationGuideline for management of postmeal glucose in diabetes
1 (2013) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2012.08.002 · Cited by 182 · see citing works
Post-Meal Glucose Peaks at Home Associate with Carotid Intima-Media Thickness in Type 2 Diabetes
Esposito, K., Ciotola, M., Carleo, D., Schisano, B., Sardelli, L., Tommaso, D. D., Misso, L., Saccomanno, F., Ceriello, A., & Giugliano, D. (2008) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2007-2000 · Cited by 162 · see citing works
Detection of Hypoglycemia With the GlucoWatch Biographer
Pitzer, K. R., Desai, S. P., Dunn, T., Edelman, S. V., Jayalakshmi, Y., Kennedy, J. F., Tamada, J. A., & Potts, R. O. (2001) · Diabetes Care · doi:10.2337/diacare.24.5.881 · Cited by 124 · see citing works
An Overview of Minimally Invasive Technologies
Ginsberg, B. H. (1992) · Clinical Chemistry · doi:10.1093/clinchem/38.9.1596 · Cited by 71 · see citing works
Hussey, E. K., Clark, R. V., Amin, D. M., Kipnes, M. S., O'Connor‐Semmes, R. L., O'Driscoll, E. C., Leong, J., Murray, S. C., Dobbins, R. L., Layko, D., et al. (2010) · The Journal of Clinical Pharmacology · doi:10.1177/0091270009351879 · Cited by 55 · see citing works
Pattzi, H. M. R., Pitale, S., Salazar, M. A., Bennett, C., O'Farrell, A. M., Li, J., Cherrington, J. M., Guler, H. P., & PHX1149‐PROT202 Study Group (2010) · Diabetes Obesity and Metabolism · doi:10.1111/j.1463-1326.2010.01195.x · Cited by 41 · see citing works
Sato, T., Okada, S., Hagino, K., Asakura, Y., Kikkawa, Y., Kojima, J., Watanabe, T., Maekawa, Y., Isobe, K., Koike, R., et al. (2011) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2011.0089 · Cited by 38 · see citing works
Self-citationKilpatrick, E. S. (2009) · Journal of Diabetes Science and Technology · doi:10.1177/193229680900300405 · Cited by 37 · see citing works
Picconi, F., Flaviani, A. D., Malandrucco, I., Giordani, I., & Frontoni, S. (2012) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2012.03.006 · Cited by 36 · see citing works
Sakaguchi, K., Hirota, Y., Hashimoto, N., Ogawa, W., Sato, T., Okada, S., Hagino, K., Asakura, Y., Kikkawa, Y., Kojima, J., et al. (2012) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2011.0255 · Cited by 34 · see citing works
Self-citationChuang, H., Trieu, M., Hurley, J., Taylor, E. J., England, M. R., & Nasraway, S. A. (2008) · Journal of Diabetes Science and Technology · doi:10.1177/193229680800200410 · Cited by 33 · see citing works
Continuous Glucose Monitoring Health Outcomes
Edelman, S. V., & Bailey, T. S. (2009) · Diabetes Technology & Therapeutics · doi:10.1089/dia.2009.0012 · Cited by 19 · see citing works
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Kim, J., Campbell, A. S., de Ávila, B. E.-F., & Wang, J. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0045-y · Cited by 3,373 · see citing works
Lee, H., Choi, T. K., Lee, Y. B., Cho, H. R., Ghaffari, R., Wang, L., Choi, H. J., Chung, T. D., Lu, N., Hyeon, T., et al. (2016) · Nature Nanotechnology · doi:10.1038/nnano.2016.38 · Cited by 1,802 · see citing works
Lee, H., Song, C., Hong, Y. S., Kim, M., Cho, H. R., Kang, T., Shin, K., Choi, S. H., Hyeon, T., & Kim, D.-H. (2017) · Science Advances · doi:10.1126/sciadv.1601314 · Cited by 1,118 · see citing works
Electrochemical glucose sensors in diabetes management: an updated review (2010–2020)
Teymourian, H., Barfidokht, A., & Wang, J. (2020) · Chemical Society Reviews · doi:10.1039/d0cs00304b · Cited by 890 · see citing works
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Min, J., Tu, J., Xu, C., Lukas, H., Shin, S., Yang, Y., Solomon, S. A., Mukasa, D., & Gao, W. F. (2023) · Chemical Reviews · doi:10.1021/acs.chemrev.2c00823 · Cited by 728 · see citing works
Wearable non-invasive epidermal glucose sensors: A review
Kim, J., Campbell, A. S., & Wang, J. (2017) · Talanta · doi:10.1016/j.talanta.2017.08.077 · Cited by 585 · see citing works
A MXene‐Based Wearable Biosensor System for High‐Performance In Vitro Perspiration Analysis
Lei, Y., Zhao, W., Zhang, Y., Jiang, Q. M., He, J., Baeumner, A. J., Wolfbeis, O. S., Wang, Z. L., Salama, K. N., & Alshareef, H. N. (2019) · Small · doi:10.1002/smll.201901190 · Cited by 443 · see citing works
Xuan, X., Yoon, H. S., & Park, J. Y. (2018) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2018.02.054 · Cited by 413 · see citing works
Abellán-Llobregat, A., Jeerapan, I., Bandodkar, A., Vidal, L., Canals, A., Wang, J., & Morallón, E. (2017) · Biosensors and Bioelectronics · doi:10.1016/j.bios.2017.01.058 · Cited by 348 · see citing works
Zhao, Y., Zhai, Q., Dong, D., An, T., Gong, S. P., Shi, Q., & Cheng, W. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b00152 · Cited by 330 · see citing works
Reshaping healthcare with wearable biosensors
Smith, A. A., Li, R., & Tse, Z. T. H. (2023) · Scientific Reports · doi:10.1038/s41598-022-26951-z · Cited by 283 · see citing works
Lin, Y., Bariya, M., Nyein, H. Y. Y., Kivimäki, L., Uusitalo, S., Jansson, E., Ji, W., Yuan, Z., Happonen, T., Liedert, C., et al. (2019) · Advanced Functional Materials · doi:10.1002/adfm.201902521 · Cited by 187 · see citing works
Pu, Z., Zhang, X., Yu, H., Tu, J., Chen, H., Liu, Y., Su, X. M., Wang, R., Zhang, L., & Li, D. (2021) · Science Advances · doi:10.1126/sciadv.abd0199 · Cited by 186 · see citing works
Nonenzymatic Wearable Sensor for Electrochemical Analysis of Perspiration Glucose
Zhu, X., Ju, Y., Chen, J., Liu, D., & Liu, H. (2018) · ACS Sensors · doi:10.1021/acssensors.8b00168 · Cited by 166 · see citing works
Cao, Q., Liang, B., Tu, T., Wei, J., Lü, F., & Ye, X. (2019) · RSC Advances · doi:10.1039/c8ra09157a · Cited by 165 · see citing works
Glucose area under the curve during oral glucose tolerance test as an index of glucose intolerance
Sakaguchi, K., Takeda, K., Maeda, M., Ogawa, W., Sato, T., Okada, S., Ohnishi, Y., Nakajima, H., & Kashiwagi, A. (2015) · Diabetology International · doi:10.1007/s13340-015-0212-4 · Cited by 156 · see citing works
Self-citationPadmanathan, N., Shao, H., & Razeeb, K. M. (2018) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.7b17187 · Cited by 147 · see citing works
Choi, J., Xue, Y., Xia, W. J., Ray, T. R., Reeder, J. T., Bandodkar, A. J., Kang, D., Xu, S., Huang, Y. Y., & Rogers, J. A. (2017) · Lab on a Chip · doi:10.1039/c7lc00525c · Cited by 147 · see citing works
Glucose Sensing Using Surface-Enhanced Raman-Mode Constraining
Yang, D., Afroosheh, S., Lee, J. O., Cho, H., Kumar, S., Siddique, R. H., Narasimhan, V., Yoon, Y.-Z., Zayak, A. T., & Choo, H. (2018) · Analytical Chemistry · doi:10.1021/acs.analchem.8b03420 · Cited by 111 · see citing works
2D Materials for Skin‐Mountable Electronic Devices
Kim, J., Lee, Y., Kang, M., Hu, L., Zhao, S., & Ahn, J. (2021) · Advanced Materials · doi:10.1002/adma.202005858 · Cited by 105 · see citing works
Zhu, X., Yuan, S., Ju, Y., Yang, J. H., Zhao, C., & Liu, H. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b02328 · Cited by 105 · see citing works
Wang, Y., Guo, H., Yuan, M., Yu, J., Wang, Z., & Chen, X. (2023) · Talanta · doi:10.1016/j.talanta.2023.124362 · Cited by 69 · see citing works
Ribet, F., Bendes, A., Fredolini, C., Dobielewski, M., Böttcher, M., Beck, O., Schwenk, J. M., Stemme, G., & Roxhed, N. (2023) · Advanced Healthcare Materials · doi:10.1002/adhm.202202564 · Cited by 56 · see citing works
Chen, Q., Fu, Y., Zhang, W., Ye, S.-B., Zhang, H., Xie, F., Gong, L., Wei, Z., Jin, H., & Chen, J. (2016) · Talanta · doi:10.1016/j.talanta.2016.12.076 · Cited by 54 · see citing works
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Coyle, S. M., Curto, V. F., Benito‐Lopez, F., Florea, L., & Diamond, D. (2014) · Elsevier eBooks · doi:10.1016/b978-0-12-418662-0.00002-7 · Cited by 53 · see citing works
Crapnell, R. D., Street, R. J., Ferreira-Silva, V., Down, M. P., Peeters, M., & Banks, C. E. (2021) · Analytical Chemistry · doi:10.1021/acs.analchem.1c02472 · Cited by 47 · see citing works
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Zhou, Y., Li, L., Tong, J., Chen, X., Deng, W., Chen, Z., Xiao, X., Yin, Y., Zhou, Q., Gao, Y., et al. (2024) · Journal of Materials Chemistry B · doi:10.1039/d4tb00790e · Cited by 33 · see citing works
Hosu, O., Mirel, S., Săndulescu, R., & Cristea, C. (2017) · Analytical Letters · doi:10.1080/00032719.2017.1391826 · Cited by 31 · see citing works
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Zhang, M., Zhang, S., Wang, Q., Xu, Y., Jiang, L., Yan, Y., Li, J., Tian, Z., & Zhang, W. (2023) · Advanced Materials Technologies · doi:10.1002/admt.202300775 · Cited by 25 · see citing works
Wang, Y., Wang, Q., Chai, G., Fan, W., Shi, Q., Zhang, W., Mao, J., Xie, J., Wei, R., & Zhang, Q. (2023) · The Analyst · doi:10.1039/d3an00553d · Cited by 18 · see citing works
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Su, F., Zhang, L., Kong, X., Lee, F., Tian, Y., & Meldrum, D. R. (2017) · Sensing and Bio-Sensing Research · doi:10.1016/j.sbsr.2017.03.004 · Cited by 14 · see citing works
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Huzooree, G., Khedo, K. K., & Joonas, N. (2018) · EAI/Springer Innovations in Communication and Computing · doi:10.1007/978-3-030-00865-9_4 · Cited by 13 · see citing works
Ugi, S., Maegawa, H., Morino, K., Nishio, Y., Sato, T., Okada, S., Kikkawa, Y., Watanabe, T., Nakajima, H., & Kashiwagi, A. (2016) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2016.40.4.326 · Cited by 11 · see citing works
Self-citationLiu, L., Zhan, K., Kilpijärvi, J., Kinnunen, M. T., Zhao, Y., Zhang, Y., Yaltaye, M. W., Li, Y., Zhyvolozhnyi, A., Samoylenko, A., et al. (2026) · Microsystems & Nanoengineering · doi:10.1038/s41378-025-01152-6 · Cited by 19 · see citing works
Karim, Z., Khan, M. J., Hussain, A., Ahmed, F., & Khan, Z. H. (2024) · Scientific Reports · doi:10.1038/s41598-024-74899-z · Cited by 10 · see citing works
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Li, X., Deng, H., & Wu, K. (2022) · Science of Advanced Materials · doi:10.1166/sam.2022.4176 · Cited by 6 · see citing works
Uemura, M., Yano, Y., Suzuki, T., Yasuma, T., Sato, T., Morimoto, A., Hosoya, S., Suminaka, C., Nakajima, H., Gabazza, E. C., et al. (2017) · Diabetes & Metabolism Journal · doi:10.4093/dmj.2017.41.4.265 · Cited by 7 · see citing works
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Tarasov, S. E., Plekhanova, Y. V., Rai, M., & Reshetilov, A. N. (2021) · Springer eBooks · doi:10.1007/978-3-030-55490-3_15 · Cited by 5 · see citing works
Ribet, F., Dobielewski, M., Böttcher, M., Beck, O., Stemme, G., & Roxhed, N. (2020) · KTH Publication Database DiVA (KTH Royal Institute of Technology) · Cited by 5 · see citing works
Guan, Y., Li, Y., Zheng, Y., Zhou, D., & Xia, Z. (2025) · Microchimica Acta · doi:10.1007/s00604-025-07675-z · Cited by 1 · see citing works
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Rodríguez-Mercado, A. (2016) · doi:10.24254/cnib.16.32
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Jose, J., Muhammed Ali, V. P., Uthara, K., Mk, S., Sandeep, B. S., Anagha, C., Vijay, A., Radhakrishnan, E. K., & Pereira, M. L. G. (2026) · Elsevier eBooks · doi:10.1016/b978-0-443-18929-6.00018-9
- Authors
- Sakaguchi, K., Hirota, Y., Hashimoto, N., Ogawa, W., Hamaguchi, T., Matsuo, T., Miyagawa, J.-I., Namba, M., Sato, T., Okada, S., Tomita, K., Matsuhisa, M., Kaneto, H., Kosugi, K., Maegawa, H., Nakajima, H., & Kashiwagi, A.
- Affiliations
- Kobe University (JP)
- Hyogo Medical University (JP)
- Sysmex (Japan) (JP)
- Osaka International Cancer Institute (JP)
- Diabetes Therapeutics and Research Center, Tokushima University (JP)
- The University of Osaka (JP)
- Osaka Police Hospital (JP)
- Shiga University of Medical Science (JP)
- Corresponding author
- Sakaguchi, Kazuhiko
- ORCID
- Venue
- Journal of Diabetes Science and Technology
- Publisher
- SAGE Publications
- Published
- 2013-05
- Volume
- 7
- Issue
- 3
- Pages
- 678-688
- ISSN
- 1932-2968 (ISSN-L)
- PMC
- PMC3869136
- OpenAlex
- W2116321774
- Cited by
- 50
- References
- 26
- Citations by year
- 2026: 2 · 2025: 3 · 2024: 5 · 2023: 6 · 2022: 1 · 2021: 5 · 2020: 3 · 2019: 6 · 2018: 5 · 2017: 7 · 2016: 5 · 2015: 1 · 2014: 1
- FWCI
- 1.84
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Journal of Diabetes Science and Technology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Advancements in Transdermal Drug Delivery
- Health Sciences › Medicine › Dermatology › Skin Diseases and Diabetes
- Keywords
- glucose area under the curve, oral glucose tolerance test, interstitial glucose, microneedle arrays, hydrogel patch, glycemic excursions, diabetes mellitus
- MeSH terms
- Diabetes Mellitus, Female, Glucose, Glucose Tolerance Test, Humans, Male, Middle Aged, Monitoring, Physiologic, Self Care, Sweat, Area Under Curve, Hydrogels, Extracellular Fluid
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