Diabetes & Metabolism Journal

Hae Kyung Kim (Kim HK)

3 Articles

Complications
Association of Muscle Mass Loss with Diabetes Development in Liver Transplantation Recipients: 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; Diabetes Metab J. 2024;48(1):146-156. Published online January 3, 2024; 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.

Complications
Renal Tubular Damage Marker, Urinary N-acetyl-β-D-Glucosaminidase, as a Predictive Marker of Hepatic Fibrosis in Type 2 Diabetes Mellitus: Hae Kyung Kim, Minyoung Lee, Yong-ho Lee, Eun Seok Kang, Bong-Soo Cha, Byung-Wan Lee; Diabetes Metab J. 2022;46(1):104-116. Published online July 13, 2021; DOI: https://doi.org/10.4093/dmj.2020.0273

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Graphical Abstract Abstract PDF Supplementary Material PubReader ePub

Background
Non-alcoholic steatohepatitis is closely associated with the progression of diabetic kidney disease (DKD) in type 2 diabetes mellitus (T2DM). We investigated whether urinary N-acetyl-β-D-glucosaminidase (u-NAG), an early renal tubular damage biomarker in DKD, could be related to the degree of hepatic fibrosis in patients with T2DM.
Methods
A total of 300 patients with T2DM were enrolled in this study. Hepatic steatosis and fibrosis were determined using transient elastography. The levels of urinary biomarkers, including u-NAG, albumin, protein, and creatinine, and glucometabolic parameters were measured.
Results
Based on the median value of the u-NAG to creatinine ratio (u-NCR), subjects were divided into low and high u-NCR groups. The high u-NCR group showed a significantly longer duration of diabetes, worsened hyperglycemia, and a more enhanced hepatic fibrosis index. A higher u-NCR was associated with a greater odds ratio for the risk of higher hepatic fibrosis stage (F2: odds ratio, 1.99; 95% confidence interval [CI], 1.04 to 3.82). Also, u-NCR was an independent predictive marker for more advanced hepatic fibrosis, even after adjusting for several confounding factors (β=1.58, P<0.01).
Conclusion
The elevation of u-NAG was independently associated with a higher degree of hepatic fibrosis in patients with T2DM. Considering the common metabolic milieu of renal and hepatic fibrosis in T2DM, the potential use of u-NAG as an effective urinary biomarker reflecting hepatic fibrosis in T2DM needs to be validated in the future.

Citations

Citations to this article as recorded by

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Fei Lu, Jinlei Fan, Fangxuan Li, Lijing Liu, Zhiyu Chen, Ziyu Tian, Liping Zuo, Dexin Yu
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Environmental Toxicology.2022; 37(3): 637. CrossRef
High Glycated Hemoglobin Instead of High Body Mass Index Might Increase the Urine N-Acetyl-β-D-glucosaminidase Con-Centration in Children and Adolescents with Diabetes Mellitus
Jin-Soon Suh, Kyoung Soon Cho, Seul Ki Kim, Shin-Hee Kim, Won Kyoung Cho, Min Ho Jung, Moon Bae Ahn
Life.2022; 12(6): 879. CrossRef

Technology/Device
Data Configuration and Publication Trends for the Korean National Health Insurance and Health Insurance Review & Assessment Database: Hae Kyung Kim, Sun Ok Song, Junghyun Noh, In-Kyung Jeong, Byung-Wan Lee; Diabetes Metab J. 2020;44(5):671-678. Published online October 21, 2020; DOI: https://doi.org/10.4093/dmj.2020.0207

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255 Download
68 Web of Science
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Abstract PDF PubReader ePub

Background
Big data reports related to diseases and health care for the Korean population have been published since the National Health Insurance Service (NHIS) and the Health Insurance Review & Assessment (HIRA) Service provided limited open access to their databases. Here, we reviewed the structure, content, and means of using data from the National Health Insurance (NHI) system for the benefit of Korean researchers and presented the latest publication trends in Korean healthcare data procured from the NHI and HIRA databases.
Methods
Since 2013, researchers have been able to obtain nationwide population-based studies using the NHI and HIRA databases of the insured. We searched publications using the NHI and the HIRA databases between 2013 and 2019 retrieved from PubMed.
Results
The NHI and HIRA databases provide nationwide population-based data. The total number of publications from 2014 to 2019 using NHI and HIRA databases is 2,541 and 655, respectively. A total of 5,465 endocrinology-related studies were performed during 2014 to 2019.
Conclusion
The NHIS and HIRA databases have provided tools for guidelines to approach world-leading population-based epidemiology and disease research.

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Eugene Han, Sun Ok Song, Hye Soon Kim, Kang Ju Son, Sun Ha Jee, Bong-Soo Cha, Byung-Wan Lee
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Dahye Baik, Byung-Woo Kim, Moran Ki
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How to Use Health Insurance Data Effectively for Healthcare Research
Ilsu Park
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Remnant cholesterol and the risk of cardiovascular disease in type 2 diabetes: a nationwide longitudinal cohort study
Ji Hye Huh, Kyung-do Han, Yun Kyung Cho, Eun Roh, Jun Goo Kang, Seong Jin Lee, Sung-Hee Ihm
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Metformin and Cervical Cancer Risk in Patients with Newly Diagnosed Type 2 Diabetes: A Population-Based Study in Korea
Hyun Min Kim, Min Jin Kang, Sun Ok Song
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Effect of Sex on Clinical Outcomes in Patients with Coronavirus Disease: A Population-Based Study
Kyu Hyang Cho, Sang Won Kim, Jong Won Park, Jun Young Do, Seok Hui Kang
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Increased Age of Death and Change in Causes of Death Among Persons With Diabetes Mellitus From the Korean National Health Insurance and Statistical Information Service, 2006 to 2018
Eugene Han, Sun Ok Song, Hye Soon Kim, Kang Ju Son, Sun Ha Jee, Bong-Soo Cha, Byung-Wan Lee
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Author index