Some results of assessing the state of microcirculation and Type D personality traits of individuals with T1DM
N. Antonova

, P. Miteva

Abstract: Background: Monitoring physiological and biophysical parameters using wearable diagnostic devices has become increasingly relevant over the past decade. Early identification of functional and metabolic alterations at the microcirculatory level is crucial in type 1 diabetes mellitus (T1DM).
Objectives: This pilot study aims to evaluate the capabilities of dual-channel portable MFED-2 analyzers for assessing microcirculation and tissue oxygenation and to correlate the results with the Denollet Type D personality scale and the dietary habits, physical activity and work characteristics of the patients.
Materials and methods: A comparative assessment of microcirculation and oxidative metabolism in one healthy subject and three T1DM individuals was performed sequentially on the foot and wrist using MFED-2, which combines two diagnostic technologies: laser Doppler flowmetry (LDF) and fluorescence spectroscopy. The Denollet D-14 scale was used to measure social inhibition and negative affect as predictors of poor glycemic control and diabetic complications. Semi-structured interviews were used to understand the patients' history, dietary and fitness habits, and adherence to therapy.
Results: Comparative microcirculatory and metabolic profiles (case reports) showed a decrease in mean microcirculatory perfusion (M), endothelial regulatory activity (Ae) and the index of oxidative metabolism (POM) and an increase in the coefficient of variation (Kv) in T1DM group. None of the tested T1DM patients was classified as having a type D personality, and two of them had threshold values on two subscales (social inhibition and negative affect).
Conclusion: The use of portable laser analyzers on symmetrical areas of the body revealed decreased perfusion and oxidative metabolism index in the T1DM patients and increased coefficient of variation. Although the clinical richness and consistent tendencies between the tested socio-psychological variables and the obtained results were not observed, this calls for a larger sample and a broader model of investigation.
Series on Biomechanics, Vol.39, No. 4 (2025), 76-90
DOI: 10.7546/SB.09.04.2025
Keywords: diabetes mellitus type 1 (T1DM); fluorescence spectroscopy; laser Doppler flowmetry (LDF); microcirculation; oxidative metabolism; personality traits; regulatory mechanisms; wavelet analysis
| References: (click to open/close) | [1] Antonova, N., Velcheva, I., Paskova, V., 2022. Hemorheological and microvascular disturbances in patients with type 2 diabetes mellitus. Clinical Hemorheology and Microcirculation, 81(4), 325–341. DOI:10.3233/CH-221393. [2] Antonova, N. M., Paskova, V. K., Velcheva, I. V., 2021. Blood rheological and electrical properties and relationships with the microvascular tone regulation in patients with Diabetes mellitus type 2. Regional Blood Circulation and Microcirculation, 20(1), 25–33. DOI:10.24884/1682-6655-2021-20-1-25-33. [3] Paskova, V., Antonova, N., Velcheva, I., Chaushev, N., Chalakov, H., 2020. Skin blood flow regulation mechanisms in patients with Diabetes mellitus type 2. Series on Biomechanics, 34(3), 37–42. [4] Jung, F., Leithäuser, B., Landgraf, H., Jünger, M., Franzeck, U., Pries, A., Sternitzky, R., Franke, R. P., Forconi, S., Ehrly, A. M., 2013. Laser Doppler flux measurement for the assessment of cutaneous microcirculation – critical remarks. Clinical Hemorheology and Microcirculation, 55(4), 411–416. DOI:10.3233/CH-131778. [5] Mrowietz, C., Franke, R. P., Pindur, G., Wolf, U., Jung, F., 2017. Reference range and variability of Laser-Doppler-Fluxmetry. Clinical Hemorheology and Microcirculation, 67(3–4), 347–353. DOI:10.3233/CH-179215. [6] Tikhomirova, I. A., Korshunova, A. A., Lemehova, V. A., 2024. Capabilities of portable laser analyzers in assessing the state of microcirculation and its regulatory mechanisms. Regional Blood Circulation and Microcirculation, 23(4), 105–113. DOI:10.24884/1682-6655-2024-23-4-105-113. [7] Dunaev, A. V., Yanushin, V. S., Loktionova, Yu. I., Zharkikh, E. V., 2025. Capabilities of human biotissue fluorescence spectroscopy in the wearable multimodal version. Sovremennye tehnologii v medicine, 17(3), 29. DOI:10.17691/stm2025.17.3.03. [8] Saha, M., Dremin, V., Rafailov, I., Dunaev, A., Sokolovski, S., Rafailov, E., 2020. Wearable Laser Doppler Flowmetry Sensor: A Feasibility Study with Smoker and Non-Smoker Volunteers. Biosensors, 10(12), 201. DOI:10.3390/bios10120201. [9] Mikhailova, M. A., Fedorovich, A. A., Gorshkov, A. Yu., Korolev, A. I., Dadaeva, V. A., Zharkikh, E. V., Loktionova, Yu. I., Dunaev, A. V., Sidorov, V. V., Drapkina, O. M., 2023. Comparative evaluation of the parameters of laser Doppler flowmetry of the skin of healthy persons using devices of various modifications. Regional Blood Circulation and Microcirculation, 22(3), 41–50. DOI:10.24884/1682-6655-2023-22-3-41-50. [10] Loktionova, Y. I., Zharkikh, E. V., Kozlov, I. O., Zherebtsov, E. A., Bryanskaya, S. A., Zherebtsova, A. I., Sidorov, V. V., Sokolovski, S. G., Dunaev, A. V., Rafailov, E. U., 2019. Pilot studies of age-related changes in blood perfusion in two different types of skin. Proceedings of SPIE, 11065, 110650S. DOI:10.1117/12.2522968. [11] Loktionova, Yu. I., Zharkikh, E. V., Zherebtsova, A. I., Kozlov, I. O., Zherebtsov, E. A., Masalygina, G. I., Dunaev, A. V., 2019. Investigation of age-related and pathological features of microhemodynamic parameters in normal conditions and type 2 diabetes using wearable laser Doppler flowmeters. Fundamental and Applied Problems of Engineering and Technology, 6(338), 131–137. [12] Fedorovich, A. A., Markov, D. S., Malishevsky, M. V., Yudakov, O. O., Gorshkov, A. Yu., Baldin, A. V., Zhuk, D. M., Spasenov, A. Yu., Korolev, A. I., Koptelov, A. V., Drapkina, O. M., 2022. Microcirculatory disorders in the forearm skin in the acute phase of COVID-19 according to laser Doppler flowmetry. Regional Blood Circulation and Microcirculation, 21(3), 56–63. DOI:10.24884/1682-6655-2022-21-3-56-63. [13] Zharkikh, E. V., Loktionova, Y. I., Fedorovich, A. A., Gorshkov, A. Y., Dunaev, A. V., 2023. Assessment of blood microcirculation changes after COVID-19 using wearable laser Doppler flowmetry. Diagnostics, 13(5), 920. DOI:10.3390/diagnostics13050920. [14] Filina, M. A., Potapova, E. V., Makovik, I. N., Zharkikh, E. V., Dremin, V. V., Zherebtsov, E. A., Dunaev, A. V., Sidorov, V. V., Krupatkin, A. I., Alimicheva, E. A., Masalygina, G. I., Muradyan, V. F., 2020. Functional changes of blood microcirculation in the skin of the foot during heating tests in patients with diabetes. [15] Zherebtsov, E. A., Zharkikh, E. V., Loktionova, Y. I., Zherebtsova, A. I., Sidorov, V. V., Rafailov, E. U., Dunaev, A. V., 2023. Wireless dynamic light scattering sensors detect microvascular changes associated with ageing and diabetes. IEEE Transactions on Biomedical Engineering, 70(11), 3073–3081. [16] Denollet, J., Pedersen, S. S., Vrints, C. J., Conraads, V. M., 2006. Usefulness of Type D personality in predicting five-year cardiac events beyond concurrent symptoms of stress in patients with coronary heart disease. American Journal of Cardiology, 97, 970–973. [17] Denollet, J., 2005. DS14: Standard assessment of negative affectivity, social inhibition, and Type D personality. Psychosomatic Medicine, 67, 89–97. [18] Mols, F., Denollet, J., 2010. Type D personality in the general population: A systematic review. Health and Quality of Life Outcomes, 8, 9. DOI:10.1186/1477-7525-8-9. [19] McCarthy, M., Zhang, L., Monacelli, G., Ward, T., 2021. Using methods from computational decision-making to predict nonadherence to fitness goals. JMIR Research Protocols, 10(11), e29758. DOI:10.2196/29758. [20] Lin, Y. H., Chen, D. A., Lin, C., Huang, H., 2020. Type D personality is associated with glycemic control and socio-psychological factors in patients with type 2 diabetes mellitus. Psychology Research and Behavior Management, 13, 373–381. DOI:10.2147/PRBM.S245226. [21] Sigal, R., Armstrong M., Bacon S., et.al.,2028. Physical Activity and Diabetes. Canadian Journal of Diabetes, 37, 40 - 44 doi: 10.1016/j.jcjd.2013.01.018 [22] American Diabetes Association, 2004. Physical Activity/Exercise and Diabetes. Diabetes Care, 27 58–62. https://doi.org/10.2337/diacare.27.2007.S58 [23] Hayes C., Kriska A., 2008. Role of Physical Activity in Diabetes Management and Prevention. Journal of the American Dietetic Association, 108 (4), 19-23, https://doi.org/10.1016/j.jada.2008.01.016 [24]American Diabetes Association, Bantle J., Wylie-Rosett J., Albright A., Apovian C., Clark N., Franz M., Hoogwerf B., Lichtenstein A., Mayer-Davis E, Mooradian A., Wheeler M., 2010. Nutrition recommendations and interventions for diabetes: a position statement of the American Diabetes Association. Diabetes Care, 61-78. doi: 10.2337/dc08-S061. [25] Kulkarni K., Castle G.,, Gregory R., Holmes A. Leontos C., Powers M., Snetselaar L., Splett P.,, Wylie-Rosett J., 1998. Nutrition Practice Guidelines for Type 1 Diabetes Mellitus Positively Affect Dietitian Practices and Patient Outcomes, Journal of the American Dietetic Association, 98 (1), 62-70, https://doi.org/10.1016/S0002-8223(98)00017-0. [26] Pongrac Barlovic D, Harjutsalo V., Groop P., 2022. Exercise and nutrition in type 1 diabetes: Insights from the FinnDiane cohort. Front. Endocrinol, 13:1064185. doi: 10.3389/fendo.2022.1064185 [27] Vijan S., Stuart S., Fitzgerald T., Ronis D., Hayward R., Slater S., Hofer T., 2004. Barriers to following dietary recommendations in Type 2 diabetes. https://doi.org/10.1111/j.1464-5491.2004.01342.x [28] Kupper, N., Pedersen, S. S., Höfer, S., Saner, H., Oldridge, N., Denollet, J., 2013. Cross-cultural analysis of Type D personality in patients with ischemic heart disease. International Journal of Cardiology, 166(2), 327–333. DOI: 10.1016/j.ijcard.2011.10.084. [29] Rietz, M., Lehr, A., Mino, E., Lang, A., Szczerba, E., Schiemann, T., Herder, C., Saatmann, N., Geidl, W., Barbaresko, J., Neuenschwander, M., Schlesinger, S., 2022. Physical activity and risk of major diabetes-related complications in individuals with diabetes. Diabetes Care, 45(12), 3101–3111. [30] Chetoui, A., Kaoutar, K., Elmoussaoui, S., Boutahar, K., El Kardoudi, A., Chigr, F., Najimi, M., 2022. Prevalence and determinants of poor glycaemic control among Moroccan type 2 diabetes patients. International Health, 14(4), 390–397. DOI:10.1093/inthealth/ihz107. [31] Sil, K., Das, B., Pal, S., Mandal, L., 2020. A study on impact of education on diabetic control and complications. [32] Miteva, P., Alexandrova-Karamanova, A., Antonova, N., Dimitrova, E., 2024. Biopsychosocial determinants of glycemic control and microvascular health: An interdisciplinary approach. Series on Biomechanics, 38(4), 116–126. DOI:10.7546/SB.16.04.2024.
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| Date published: 2025-12-12
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