Diabetes & Metabolism Journal

Original Articles

Complications
Association between Serum Cystatin C and Vascular Complications in Type 2 Diabetes Mellitus without Nephropathy: Hye Jeong Kim, Dong Won Byun, Kyoil Suh, Myung Hi Yoo, Hyeong Kyu Park; Diabetes Metab J. 2018;42(6):513-518. Published online October 15, 2018; DOI: https://doi.org/10.4093/dmj.2018.0006

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Background

Recent studies have correlated serum cystatin C (CysC) with vascular complications, but few studies have investigated this correlation in diabetes patients without nephropathy. This study aimed to evaluate if higher serum CysC levels increase the risk for vascular complications in type 2 diabetes mellitus patients with normal renal function or mild renal impairment.

Methods

A total of 806 consecutive patients with type 2 diabetes mellitus who were admitted to the diabetes center of Soonchunhyang University Hospital for blood glucose control were retrospectively reviewed. Patients with nephropathy were excluded. Subjects were categorized into quartiles of serum CysC levels (Q1, ≤0.65 mg/L; Q2, 0.66 to 0.79 mg/L; Q3, 0.80 to 0.94 mg/L; and Q4, ≥0.95 mg/L).

Results

The proportion of patients with diabetic retinopathy (DR) (P for trend <0.001), coronary heart disease (CHD) (P for trend <0.001), and stroke (P for trend <0.001) increased across the serum CysC quartiles. After adjustment for confounding factors, the highest serum CysC level remained a significant risk factor for DR (odds ratio [OR], 1.929; 95% confidence interval [CI], 1.007 to 4.144; P=0.040). Compared with Q1, a significant positive association was observed between serum CysC and CHD in Q2 (OR, 7.321; 95% CI, 1.114 to 48.114; P=0.012), Q3 (OR, 6.027; 95% CI, 0.952 to 38.161; P=0.020), and Q4 (OR, 8.122; 95% CI, 1.258 to 52.453; P=0.007). No associations were observed between CysC and stroke after additional adjustment for confounding variables.

Conclusion

Serum CysC levels are independently associated with DR and CHD, suggesting that CysC may be useful for identifying type 2 diabetes mellitus patients without nephropathy who are at high risk for vascular complications.

Citations

Citations to this article as recorded by

A systematic literature review of machine learning based risk prediction models for diabetic retinopathy progression
Tiwalade Modupe Usman, Yakub Kayode Saheed, Augustine Nsang, Abel Ajibesin, Sandip Rakshit
Artificial Intelligence in Medicine.2023; 143: 102617. CrossRef
Serum cystatin C for risk stratification of prediabetes and diabetes populations
Kun Xiong, Shiran Zhang, Pingting Zhong, Zhuoting Zhu, Yanping Chen, Wenyong Huang, Wei Wang
Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2023; 17(11): 102882. CrossRef
Serum VEGF, high-sensitivity CRP, and cystatin-C assist in the diagnosis of type 2 diabetic retinopathy complicated with hyperuricemia
Jing Wei, Jincheng Zhang, Yanan Shi, Huiqin Zhang, Yan Wu
Open Medicine.2023;[Epub] CrossRef
Diagnostic circulating biomarkers to detect vision‐threatening diabetic retinopathy: Potential screening tool of the future?
Karen Frudd, Sobha Sivaprasad, Rajiv Raman, Subramanian Krishnakumar, Yeddula Rebecca Revathy, Patric Turowski
Acta Ophthalmologica.2022;[Epub] CrossRef
Association between circulating cystatin C and hyperuricemia: a cross-sectional study
Yanjun Guo, Hangkai Huang, Yishu Chen, Chao Shen, Chengfu Xu
Clinical Rheumatology.2022; 41(7): 2143. CrossRef
Multicenter Evaluation of Diagnostic Circulating Biomarkers to Detect Sight-Threatening Diabetic Retinopathy
Sarega Gurudas, Karen Frudd, Jayapal Jeya Maheshwari, Yeddula Rebecca Revathy, Sobha Sivaprasad, Shruthi Mahalakshmi Ramanathan, Vignesh Pooleeswaran, A. Toby Prevost, Eleni Karatsai, Sandra Halim, Shruti Chandra, Paul Nderitu, Dolores Conroy, Subramanian
JAMA Ophthalmology.2022; 140(6): 587. CrossRef
A Cross-Sectional Study of Serum and Urine Fluoride in Diabetes in Fluoride Exposed Population
Sai Deepika Ram Mohan, Shashidhar Kurpad Nagaraj, Raveesha Anjanappa, Muninarayana Chandrappa
Journal of Evolution of Medical and Dental Sciences.2021; 10(11): 798. CrossRef
Cystatin C predicts the risk of incident cerebrovascular disease in the elderly
Xin Zheng, Hong-da She, Qiao-xin Zhang, Tong Si, Ku-sheng Wu, Ying-xiu Xiao
Medicine.2021; 100(28): e26617. CrossRef
Proteinuria Is Associated with Carotid Artery Atherosclerosis in Non-Albuminuric Type 2 Diabetes: A Cross-Sectional Study
Jaehyun Bae, Yong-ho Lee, Eun Seok Kang, Bong-Soo Cha, Byung-Wan Lee
Journal of Clinical Medicine.2020; 9(1): 136. CrossRef

Effectiveness of 3-Day Continuous Glucose Monitoring for Improving Glucose Control in Type 2 Diabetic Patients in Clinical Practice: Soo Kyoung Kim, Hye Jeong Kim, Taehun Kim, Kyu Yeon Hur, Sun Wook Kim, Moon-Kyu Lee, Yong-Ki Min, Kwang-Won Kim, Jae Hoon Chung, Jae Hyeon Kim; Diabetes Metab J. 2014;38(6):449-455. Published online December 15, 2014; DOI: https://doi.org/10.4093/dmj.2014.38.6.449

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38 Download
16 Web of Science
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Abstract PDF PubReader

Background

The aim of this study was to investigate whether adjusting diabetic treatment regimens according to the information obtained from a continuous glucose monitoring system (CGMS) might lead to improved glycemic control in patients with type 2 diabetes.

Methods

We reviewed the medical charts of 172 patients who used the CGMS for 1 year starting in December 2008 and the records of 1,500 patients who visited their regular outpatient clinics during December 2008. Of these patients, a total of 65 CGMS patients and 301 regular outpatients (control group) were enrolled in the study after propensity score matching. There were no differences in baseline glycated hemoglobin (HbA1c), age, and duration of diabetes between the CGMS and the control groups after propensity score matching. The changes in the HbA1c levels from baseline to 6 months were calculated.

Results

The CGMS group showed a significant improvement in the HbA1c level compared to the control group at 3 months (7.9%±1.6% vs. 7.4%±1.2%, P=0.001) and at 6 months (7.4%±1.2% vs. 7.9%±1.6%, P=0.010). There were significant differences in the treatment modality changes between the CGMS group and the control group.

Conclusion

Using a 3-day CGMS was advantageous for improving glucose control in patients with type 2 diabetes and may help these patients to optimize glycemic control in clinical practice.

Citations

Citations to this article as recorded by

Biological and Clinical Impacts of Glucose Metabolism in Pancreatic Ductal Adenocarcinoma
Zhao Liu, Hiromitsu Hayashi, Kazuki Matsumura, Norio Uemura, Yuta Shiraishi, Hiroki Sato, Hideo Baba
Cancers.2023; 15(2): 498. CrossRef
Professional continuous glucose monitoring in patients with diabetes mellitus: A systematic review and meta‐analysis
Sergio Di Molfetta, Irene Caruso, Angelo Cignarelli, Annalisa Natalicchio, Sebastio Perrini, Luigi Laviola, Francesco Giorgino
Diabetes, Obesity and Metabolism.2023; 25(5): 1301. CrossRef
American Association of Clinical Endocrinology Clinical Practice Guideline: The Use of Advanced Technology in the Management of Persons With Diabetes Mellitus
George Grunberger, Jennifer Sherr, Myriam Allende, Thomas Blevins, Bruce Bode, Yehuda Handelsman, Richard Hellman, Rosemarie Lajara, Victor Lawrence Roberts, David Rodbard, Carla Stec, Jeff Unger
Endocrine Practice.2021; 27(6): 505. CrossRef
Lack of Acceptance of Digital Healthcare in the Medical Market: Addressing Old Problems Raised by Various Clinical Professionals and Developing Possible Solutions
Jong Il Park, Hwa Young Lee, Hyunah Kim, Jisan Lee, Jiwon Shinn, Hun-Sung Kim
Journal of Korean Medical Science.2021;[Epub] CrossRef
A head‐to‐head comparison of personal and professional continuous glucose monitoring systems in people with type 1 diabetes: Hypoglycaemia remains the weak spot
Othmar Moser, Marlene Pandis, Felix Aberer, Harald Kojzar, Daniel Hochfellner, Hesham Elsayed, Melanie Motschnig, Thomas Augustin, Philipp Kreuzer, Thomas R. Pieber, Harald Sourij, Julia K. Mader
Diabetes, Obesity and Metabolism.2019; 21(4): 1043. CrossRef
Glucose monitoring in diabetes: from clinical studies to real‐world practice
Rebecca C Sagar, Afroze Abbas, Ramzi Ajjan
Practical Diabetes.2019; 36(2): 57. CrossRef
The Effectiveness of Continuous Glucose Monitoring in Patients with Type 2 Diabetes: A Systematic Review of Literature and Meta-analysis
Cindy Park, Quang A. Le
Diabetes Technology & Therapeutics.2018; 20(9): 613. CrossRef
Effects of Dapagliflozin on 24-Hour Glycemic Control in Patients with Type 2 Diabetes: A Randomized Controlled Trial
Robert R. Henry, Poul Strange, Rong Zhou, Jeremy Pettus, Leon Shi, Sergey B. Zhuplatov, Traci Mansfield, David Klein, Arie Katz
Diabetes Technology & Therapeutics.2018; 20(11): 715. CrossRef
Clinical and economic benefits of professional CGM among people with type 2 diabetes in the United States: analysis of claims and lab data
Joseph A. Sierra, Mona Shah, Max S. Gill, Zachery Flores, Hiten Chawla, Francine R. Kaufman, Robert Vigersky
Journal of Medical Economics.2018; 21(3): 225. CrossRef
Role of continuous glucose monitoring for type 2 in diabetes management and research
Robert Vigersky, Maneesh Shrivastav
Journal of Diabetes and its Complications.2017; 31(1): 280. CrossRef
Assessing the Therapeutic Utility of Professional Continuous Glucose Monitoring in Type 2 Diabetes Across Various Therapies: A Retrospective Evaluation
Jothydev Kesavadev, Robert Vigersky, John Shin, Pradeep Babu Sadasivan Pillai, Arun Shankar, Geethu Sanal, Gopika Krishnan, Sunitha Jothydev
Advances in Therapy.2017; 34(8): 1918. CrossRef
Use of Continuous Glucose Monitoring in Youth-Onset Type 2 Diabetes
Christine L. Chan
Current Diabetes Reports.2017;[Epub] CrossRef
The efficacy and safety of adding either vildagliptin or glimepiride to ongoing metformin therapy in patients with type 2 diabetes mellitus
Gyuri Kim, Sewon Oh, Sang-Man Jin, Kyu Yeon Hur, Jae Hyeon Kim, Moon-Kyu Lee
Expert Opinion on Pharmacotherapy.2017; 18(12): 1179. CrossRef
Morning Spot Urine Glucose-to-Creatinine Ratios Predict Overnight Urinary Glucose Excretion in Patients With Type 2 Diabetes
So Ra Kim, Yong-ho Lee, Sang-Guk Lee, Sun Hee Lee, Eun Seok Kang, Bong-Soo Cha, Hyun Chul Lee, Jeong-Ho Kim, Byung-Wan Lee
Annals of Laboratory Medicine.2017; 37(1): 9. CrossRef
The Contemporary Role of Masked Continuous Glucose Monitoring in a Real-Time World
Ian Blumer
Journal of Diabetes Science and Technology.2016; 10(3): 790. CrossRef
Glycemic Variability: How Do We Measure It and Why Is It Important?
Sunghwan Suh, Jae Hyeon Kim
Diabetes & Metabolism Journal.2015; 39(4): 273. CrossRef

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