Cheol-Young Park

Dr. Cheol-Young Park

orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 January 2007 in Diabetes Research and Clinical Practice
Verified
Journal Article
Closed access
Sang Yeoup LeeSang Yeoup Lee
Sang Yeoup Lee
HPHye Soon Park
Hye Soon Park
DKDae Jung Kim
Dae Jung Kim
JHJee Hye Han
Jee Hye Han
SKSeon Mee Kim
Seon Mee Kim
HYHyung Joon Yoo
Hyung Joon Yoo

1 January 2014 in Diabetes & Metabolism Journal
Verified
Journal Article
Open access
PDF file
SSSun Ok Song
Sun Ok Song
CJChang Hee Jung
Chang Hee Jung
YSYoung Duk Song
Young Duk Song
Cheol-Young ParkCheol-Young Park
Cheol-Young Park
HKHyuk-Sang Kwon
Hyuk-Sang Kwon
BLByung Wan Lee
Byung Wan Lee
Song SO, et al. Diabetes Metab J. 2014 Oct;38(5):395-403. http://dx.doi.org/10.4093/dmj.2014.38.5.395

1 January 2012 in Diabetes & Metabolism Journal
Verified
Journal Article
Open access
PDF file
JKJun Goo Kang
Jun Goo Kang
Cheol-Young ParkCheol-Young Park
Cheol-Young Park
Kang JG, et al. Diabetes Metab J. 2012 Feb;36(1):13-25. https://doi.org/10.4093/dmj.2012.36.1.13

25 November 2020 in BMC Medicine
Verified
Journal Article
Open access
PDF file
SHSangmo Hong
Sangmo Hong
KHKyungdo Han
Kyungdo Han
Cheol-Young ParkCheol-Young Park
Cheol-Young Park
Background: The triglyceride glucose (TyG) index is an inexpensive clinical surrogate marker for insulin resistance. However, the relationship between TyG index and atherosclerotic cardiovascular disease (CVD) remains unclear. We evaluated the relationship between TyG index and CVD using a large-scale population dataset from the National Health Information Database (NHID). Methods: We performed a retrospective observational cohort study of 5,593,134 persons older than 40 years from 2009 to 2017 using the NHID. We divided the participants into TyG index quartiles. Outcome variables were stroke, myocardial infarction, and both. The incidence of outcomes was estimated for each TyG quartile over the total follow-up period. All outcomes were analyzed by Cox proportional hazards regression analysis while controlling for baseline covariates. Results: During 8.2 years of mean follow-up, stroke was diagnosed in 89,120 (1.59%), MI in 62,577 (1.12%), and both stroke and MI in 146,744 (2.62%) participants. Multivariate-adjusted hazard ratios (HRs) for patients in the highest TyG index quartile demonstrated that these patients were at higher risk for stroke (HR = 1.259; 95% confidence interval [CI] 1.233–1.286), for MI (HR = 1.313; 95% CI 1.28–1.346), and for both (HR = 1.282; 95% CI 1.261–1.303) compared with participants in the lowest TyG index quartile. These effects were independent of age, sex, smoking, alcohol consumption, physical activity, body mass index, systolic blood pressure, and total cholesterol. Conclusions: In our large population study, TyG index, a simple measure reflecting insulin resistance, was potentially useful in the early identification of individuals at high risk of experiencing a cardiovascular event.

13 February 2024 in BMJ
Verified
Journal Article
Open access
PDF file
KKKyung-Soo Kim
Kyung-Soo Kim
SHSangmo Hong
Sangmo Hong
KHKyungdo Han
Kyungdo Han
Cheol-Young ParkCheol-Young Park
Cheol-Young Park
Objective To investigate the risk of non-alcoholic fatty liver disease (NAFLD) for cardiovascular disease and all cause death in patients with type 2 diabetes mellitus (T2DM). Design Nationwide population based study. Setting Longitudinal cohort study in Korea. Participants 7 796 763 participants in the National Health Screening Programme in 2009 were divided into three groups based on NAFLD status: no NAFLD (fatty liver index<30); grade 1 NAFLD (30≤fatty liver index<60); and grade 2 NAFLD (fatty liver index≥60). Median follow-up was 8.13 years. Main outcome measures The primary outcome was incident cardiovascular disease (myocardial infarction, ischaemic stroke) or all cause death. Results Of 7 796 763 participants, 6.49% (n=505 763) had T2DM. More patients with T2DM had grade 1 NAFLD (34.06%) and grade 2 NAFLD (26.73%) than those without T2DM (grade 1 NAFLD: 21.20%; grade 2 NAFLD: 10.02%). The incidence rate (per 1000 person years) of cardiovascular disease and all cause death increased in the order of no NAFLD, grade 1 NAFLD, and grade 2 NAFLD, and the incidence rates in patients with T2DM were higher than those in patients without T2DM. The five year absolute risk for cardiovascular disease and all cause death increased in the order of no NAFLD, grade 1 NAFLD, and grade 2 NAFLD in patients without and with T2DM (no NAFLD, without T2DM: 1.03, 95% confidence interval 1.02 to 1.04, and 1.25, 1.24 to 1.26, respectively; grade 1 NAFLD, without T2DM: 1.23, 1.22 to 1.25, and 1.50, 1.48 to 1.51, respectively; grade 2 NAFLD, without T2DM: 1.42, 1.40 to 1.45, and 2.09, 2.06 to 2.12, respectively; no NAFLD, with T2DM: 3.34, 3.27 to 3.41, and 3.68, 3.61 to 3.74, respectively; grade 1 NAFLD, with T2DM: 3.94, 3.87 to 4.02, and 4.25, 4.18 to 4.33, respectively; grade 2 NAFLD, with T2DM: 4.66, 4.54 to 4.78, and 5.91, 5.78 to 6.05, respectively). Patients with T2DM and without NAFLD had a higher five year absolute risk for cardiovascular disease and all cause death than those without T2DM and with grade 2 NAFLD. Risk differences for cardiovascular disease and all cause death between no NAFLD and grade 1 or grade 2 NAFLD were higher in patients with T2DM than in those without T2DM. Conclusions NAFLD in patients with T2DM seems to be associated with a higher risk of cardiovascular disease and all cause death, even in patients with mild NAFLD. Risk differences for cardiovascular disease and all cause death between the no NAFLD group and the grade 1 or grade 2 NAFLD groups were higher in patients with T2DM than in those without T2DM.

4 June 2015 in Critical Reviews in Clinical Laboratory Sciences
Verified
Journal Article
Closed access
SPSe Eun Park
Se Eun Park
Cheol-Young ParkCheol-Young Park
Cheol-Young Park
GSGary Sweeney
Gary Sweeney
Insulin resistance in insulin target tissues including liver, skeletal muscle and adipose tissue is an early step in the progression towards type 2 diabetes. Accurate diagnostic parameters reflective of insulin resistance are essential. Longstanding tests for fasting blood glucose and HbA1c are useful and although the hyperinsulinemic euglycemic clamp remains a "gold standard" for accurately determining insulin resistance, it cannot be implemented on a routine basis. The study of adipokines, and more recently myokines and hepatokines, as potential biomarkers for insulin sensitivity is now an attractive and relatively straightforward approach. This review discusses potential biomarkers including adiponectin, RBP4, chemerin, A-FABP, FGF21, fetuin-A, myostatin, IL-6, and irisin, all of which may play significant roles in determining insulin sensitivity. We also review potential future directions of new biological markers for measuring insulin resistance, including metabolomics and gut microbiome. Collectively, these approaches will provide clinicians with the tools for more accurate, and perhaps personalized, diagnosis of insulin resistance.