PMID- 37483941 OWN - NLM STAT- MEDLINE DCOM- 20230726 LR - 20230726 IS - 2296-2565 (Electronic) IS - 2296-2565 (Linking) VI - 11 DP - 2023 TI - Profiling of patients with type 2 diabetes based on medication adherence data. PG - 1209809 LID - 10.3389/fpubh.2023.1209809 [doi] LID - 1209809 AB - INTRODUCTION: Type 2 diabetes mellitus (T2DM) is a complex, chronic disease affecting multiple organs with varying symptoms and comorbidities. Profiling patients helps identify those with unfavorable disease progression, allowing for tailored therapy and addressing special needs. This study aims to uncover different T2DM profiles based on medication intake records and laboratory measurements, with a focus on how individuals with diabetes move through disease phases. METHODS: We use medical records from databases of the last 20 years from the Department of Endocrinology and Diabetology of the University Medical Center in Maribor. Using the standard ATC medication classification system, we created a patient-specific drug profile, created using advanced natural language processing methods combined with data mining and hierarchical clustering. RESULTS: Our results show a well-structured profile distribution characterizing different age groups of individuals with diabetes. Interestingly, only two main profiles characterize the early 40-50 age group, and the same is true for the last 80+ age group. One of these profiles includes individuals with diabetes with very low use of various medications, while the other profile includes individuals with diabetes with much higher use. The number in both groups is reciprocal. Conversely, the middle-aged groups are characterized by several distinct profiles with a wide range of medications that are associated with the distinct concomitant complications of T2DM. It is intuitive that the number of profiles increases in the later age groups, but it is not obvious why it is reduced later in the 80+ age group. In this context, further studies are needed to evaluate the contributions of a range of factors, such as drug development, drug adoption, and the impact of mortality associated with all T2DM-related diseases, which characterize these middle-aged groups, particularly those aged 55-75. CONCLUSION: Our approach aligns with existing studies and can be widely implemented without complex or expensive analyses. Treatment and drug use data are readily available in healthcare facilities worldwide, allowing for profiling insights into individuals with diabetes. Integrating data from other departments, such as cardiology and renal disease, may provide a more sophisticated understanding of T2DM patient profiles. CI - Copyright (c) 2023 Markovic, Grubelnik, Zavrsnik, Blazun Vosner, Kokol, Perc, Marhl, Zavrsnik and Zavrsnik. FAU - Markovic, Rene AU - Markovic R AD - Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia. AD - Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia. FAU - Grubelnik, Vladimir AU - Grubelnik V AD - Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia. FAU - Zavrsnik, Tadej AU - Zavrsnik T AD - University Clinical Medical Centre Maribor, Maribor, Slovenia. AD - Faculty of Medicine, University of Maribor, Maribor, Slovenia. FAU - Blazun Vosner, Helena AU - Blazun Vosner H AD - Community Healthcare Center Dr. Adolf Drolc Maribor, Maribor, Slovenia. AD - Faculty of Health and Social Sciences, Slovenj Gradec, Slovenia. AD - Alma Mater Europaea - ECM, Maribor, Slovenia. FAU - Kokol, Peter AU - Kokol P AD - Faculty of Electrical Engineering and Computer Science, University of Maribor, Maribor, Slovenia. FAU - Perc, Matjaz AU - Perc M AD - Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia. AD - Alma Mater Europaea - ECM, Maribor, Slovenia. AD - Complexity Science Hub Vienna, Vienna, Austria. AD - Department of Medical Research, China Medical University Hospital, China Medical University, Taichung, Taiwan. AD - Department of Physics, Kyung Hee University, Seoul, Republic of Korea. FAU - Marhl, Marko AU - Marhl M AD - Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia. AD - Faculty of Medicine, University of Maribor, Maribor, Slovenia. AD - Faculty of Education, University of Maribor, Maribor, Slovenia. FAU - Zavrsnik, Matej AU - Zavrsnik M AD - Department of Endocrinology and Diabetology, University Medical Center Maribor, Maribor, Slovenia. FAU - Zavrsnik, Jernej AU - Zavrsnik J AD - Faculty of Natural Sciences and Mathematics, University of Maribor, Maribor, Slovenia. AD - Community Healthcare Center Dr. Adolf Drolc Maribor, Maribor, Slovenia. AD - Alma Mater Europaea - ECM, Maribor, Slovenia. AD - Science and Research Center Koper, Koper, Slovenia. LA - eng PT - Journal Article PT - Research Support, Non-U.S. Gov't DEP - 20230706 PL - Switzerland TA - Front Public Health JT - Frontiers in public health JID - 101616579 SB - IM MH - Middle Aged MH - Humans MH - Adult MH - Aged, 80 and over MH - *Diabetes Mellitus, Type 2/drug therapy MH - Comorbidity MH - Chronic Disease MH - Disease Progression MH - Medication Adherence PMC - PMC10358769 OTO - NOTNLM OT - cluster analysis OT - electronic health records OT - medication management OT - medication usage patterns OT - natural language processing OT - patient profiles OT - personalized medicine OT - type 2 diabetes mellitus COIS- The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. EDAT- 2023/07/24 06:42 MHDA- 2023/07/26 06:43 PMCR- 2023/07/06 CRDT- 2023/07/24 04:37 PHST- 2023/04/21 00:00 [received] PHST- 2023/06/21 00:00 [accepted] PHST- 2023/07/26 06:43 [medline] PHST- 2023/07/24 06:42 [pubmed] PHST- 2023/07/24 04:37 [entrez] PHST- 2023/07/06 00:00 [pmc-release] AID - 10.3389/fpubh.2023.1209809 [doi] PST - epublish SO - Front Public Health. 2023 Jul 6;11:1209809. doi: 10.3389/fpubh.2023.1209809. eCollection 2023.