- Complications
- Association of Muscle Mass Loss with Diabetes Development in Liver Transplantation Recipients
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Sejeong Lee, Minyoung Lee, Young-Eun Kim, Hae Kyung Kim, Sook Jung Lee, Jiwon Kim, Yurim Yang, Chul Hoon Kim, Hyangkyu Lee, Dong Jin Joo, Myoung Soo Kim, Eun Seok Kang
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Diabetes Metab J. 2024;48(1):146-156. Published online January 3, 2024
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DOI: https://doi.org/10.4093/dmj.2022.0100
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 Abstract
 PDF Supplementary Material PubReader  ePub
- Background
Post-transplant diabetes mellitus (PTDM) is one of the most significant complications after transplantation. Patients with end-stage liver diseases requiring transplantation are prone to sarcopenia, but the association between sarcopenia and PTDM remains to be elucidated. We aimed to investigate the effect of postoperative muscle mass loss on PTDM development.
Methods
A total of 500 patients who underwent liver transplantation at a tertiary care hospital between 2005 and 2020 were included. Skeletal muscle area at the level of the L3–L5 vertebrae was measured using computed tomography scans performed before and 1 year after the transplantation. The associations between the change in the muscle area after the transplantation and the incidence of PTDM was investigated using a Cox proportional hazard model.
Results
During the follow-up period (median, 4.9 years), PTDM occurred in 165 patients (33%). The muscle mass loss was greater in patients who developed PTDM than in those without PTDM. Muscle depletion significantly increased risk of developing PTDM after adjustment for other confounding factors (hazard ratio, 1.50; 95% confidence interval, 1.23 to 1.84; P=0.001). Of the 357 subjects who had muscle mass loss, 124 (34.7%) developed PTDM, whereas of the 143 patients in the muscle mass maintenance group, 41 (28.7%) developed PTDM. The cumulative incidence of PTDM was significantly higher in patients with muscle loss than in patients without muscle loss (P=0.034).
Conclusion
Muscle depletion after liver transplantation is associated with increased risk of PTDM development.
- Technology/Device
- Do-It-Yourself Open Artificial Pancreas System in Children and Adolescents with Type 1 Diabetes Mellitus: Real-World Data
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Min Sun Choi, Seunghyun Lee, Jiwon Kim, Gyuri Kim, Sung Min Park, Jae Hyeon Kim
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Diabetes Metab J. 2022;46(1):154-159. Published online November 23, 2021
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DOI: https://doi.org/10.4093/dmj.2021.0011
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Crossref
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Abstract
PDFSupplementary MaterialPubReader ePub
- Few studies have been conducted among Asian children and adolescents with type 1 diabetes mellitus (T1DM) using do-it-yourself artificial pancreas system (DIY-APS). We evaluated real-world data of pediatric T1DM patients using DIY-APS. Data were obtained for 10 patients using a DIY-APS with algorithms. We collected sensor glucose and insulin delivery data from each participant for a period of 4 weeks. Average glycosylated hemoglobin was 6.2%±0.3%. The mean percentage of time that glucose level remained in the target range of 70 to 180 mg/dL was 82.4%±7.8%. Other parameters including time above range, time below range and mean glucose were also within the recommended level, similar to previous commercial and DIY-APS studies. However, despite meeting the target range, unadjusted gaps were still observed between the median basal setting and temporary basal insulin, which should be handled by healthcare providers.
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Citations
Citations to this article as recorded by  - Real-world efficacy and safety of open-source automated insulin delivery for people with type 1 diabetes mellitus: Experience from mainland China
Yongwen Zhou, Mengyun Lei, Daizhi Yang, Ping Ling, Ying Ni, Hongrong Deng, Wen Xu, Xubin Yang, Benjamin John Wheeler, Jianping Weng, Jinhua Yan
Diabetes Research and Clinical Practice.2024; 218: 111910. CrossRef - Advances in Continuous Glucose Monitoring and Integrated Devices for Management of Diabetes with Insulin-Based Therapy: Improvement in Glycemic Control
Jee Hee Yoo, Jae Hyeon Kim
Diabetes & Metabolism Journal.2023; 47(1): 27. CrossRef - Open-source automated insulin delivery systems (OS-AIDs) in a pediatric population with type 1 diabetes in a real-life setting: the AWeSoMe study group experience
Judith Nir, Marianna Rachmiel, Abigail Fraser, Yael Lebenthal, Avivit Brener, Orit Pinhas-Hamiel, Alon Haim, Eve Stern, Noa Levek, Tal Ben-Ari, Zohar Landau
Endocrine.2023; 81(2): 262. CrossRef - Efficacy and safety of Android artificial pancreas system use at home among adults with type 1 diabetes mellitus in China: protocol of a 26-week, free-living, randomised, open-label, two-arm, two-phase, crossover trial
Mengyun Lei, Beisi Lin, Ping Ling, Zhigu Liu, Daizhi Yang, Hongrong Deng, Xubin Yang, Jing Lv, Wen Xu, Jinhua Yan
BMJ Open.2023; 13(8): e073263. CrossRef - Barriers to Uptake of Open-Source Automated Insulin Delivery Systems: Analysis of Socioeconomic Factors and Perceived Challenges of Caregivers of Children and Adolescents With Type 1 Diabetes From the OPEN Survey
Antonia Huhndt, Yanbing Chen, Shane O’Donnell, Drew Cooper, Hanne Ballhausen, Katarzyna A. Gajewska, Timothée Froment, Mandy Wäldchen, Dana M. Lewis, Klemens Raile, Timothy C. Skinner, Katarina Braune
Frontiers in Clinical Diabetes and Healthcare.2022;[Epub] CrossRef - Toward Personalized Hemoglobin A1c Estimation for Type 2 Diabetes
Namho Kim, Da Young Lee, Wonju Seo, Nan Hee Kim, Sung-Min Park
IEEE Sensors Journal.2022; 22(23): 23023. CrossRef
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