Skip Navigation
Skip to contents

Diabetes Metab J : Diabetes & Metabolism Journal

Search
OPEN ACCESS

Search

Page Path
HOME > Search
5 "Coronary heart disease"
Filter
Filter
Article category
Keywords
Publication year
Authors
Original Articles
Agreement between Framingham Risk Score and United Kingdom Prospective Diabetes Study Risk Engine in Identifying High Coronary Heart Disease Risk in North Indian Population
Dipika Bansal, Ramya S. R. Nayakallu, Kapil Gudala, Rajavikram Vyamasuni, Anil Bhansali
Diabetes Metab J. 2015;39(4):321-327.   Published online July 8, 2015
DOI: https://doi.org/10.4093/dmj.2015.39.4.321
  • 3,159 View
  • 30 Download
  • 11 Web of Science
  • 12 Crossref
AbstractAbstract PDFPubReader   
Background

The aim of the study is to evaluate the concurrence between Framingham Risk score (FRS) and United Kingdom Prospective Diabetes Study (UKPDS) risk engine in identifying coronary heart disease (CHD) risk in newly detected diabetes mellitus patients and to explore the characteristics associated with the discrepancy between them.

Methods

A cross-sectional study involving 489 subjects newly diagnosed with type 2 diabetes mellitus was conducted. Agreement between FRS and UKPDS in classifying patients as high risk was calculated using kappa statistic. Subjects with discrepant scores between two algorithms were identified and associated variables were determined.

Results

The FRS identified 20.9% subjects (range, 17.5 to 24.7) as high-risk while UKPDS identified 21.75% (range, 18.3 to 25.5) as high-risk. Discrepancy was observed in 17.9% (range, 14.7 to 21.7) subjects. About 9.4% had high risk by UKPDS but not FRS, and 8.6% had high risk by FRS but not UKPDS. The best agreement was observed at high-risk threshold of 20% for both (κ=0.463). Analysis showed that subjects having high risk on FRS but not UKPDS were elderly females having raised systolic and diastolic blood pressure. Patients with high risk on UKPDS but not FRS were males and have high glycosylated hemoglobin.

Conclusion

The FRS and UKPDS (threshold 20%) identified different populations as being at high risk, though the agreement between them was fairly good. The concurrence of a number of factors (e.g., male sex, low high density lipoprotein cholesterol, and smoking) in both algorithms should be regarded as increasing the CHD risk. However, longitudinal follow-up is required to form firm conclusions.

Citations

Citations to this article as recorded by  
  • Endocan is Related to Increased Cardiovascular Risk in Type 2 Diabetes Mellitus Patients
    Aleksandra Klisic, Jelena Kotur-Stevuljevic, Ana Ninic
    Metabolic Syndrome and Related Disorders.2023; 21(7): 362.     CrossRef
  • Estimated risk of cardiovascular events and long-term complications: The projected future of diabetes patients in Delhi from the DEDICOM-II survey
    Swapnil Rawat, Ramasheesh Yadav, Siddhi Goyal, Jitender Nagpal
    Diabetes & Metabolic Syndrome: Clinical Research & Reviews.2023; 17(11): 102880.     CrossRef
  • Cardiovascular Biomarkers and Calculated Cardiovascular Risk in Orally Treated Type 2 Diabetes Patients: Is There a Link?
    Aleksandra Markova, Mihail Boyanov, Deniz Bakalov, Atanas Kundurdjiev, Adelina Tsakova
    Hormone and Metabolic Research.2021; 53(01): 41.     CrossRef
  • Risk of coronary heart disease and stroke based on United Kingdom prospective diabetes study in type 2 DM patients in Medan
    R Amelia, J Harahap, H Wijaya, I I Fujiati
    IOP Conference Series: Earth and Environmental Science.2021; 912(1): 012081.     CrossRef
  • Cardiovascular/stroke risk prevention: A new machine learning framework integrating carotid ultrasound image-based phenotypes and its harmonics with conventional risk factors
    Ankush Jamthikar, Deep Gupta, Narendra N. Khanna, Luca Saba, John R. Laird, Jasjit S. Suri
    Indian Heart Journal.2020; 72(4): 258.     CrossRef
  • Current Data Regarding the Relationship between Type 2 Diabetes Mellitus and Cardiovascular Risk Factors
    Cosmin Mihai Vesa, Loredana Popa, Amorin Remus Popa, Marius Rus, Andreea Atena Zaha, Simona Bungau, Delia Mirela Tit, Raluca Anca Corb Aron, Dana Carmen Zaha
    Diagnostics.2020; 10(5): 314.     CrossRef
  • Artificial intelligence framework for predictive cardiovascular and stroke risk assessment models: A narrative review of integrated approaches using carotid ultrasound
    Ankush D. Jamthikar, Deep Gupta, Luca Saba, Narendra N. Khanna, Klaudija Viskovic, Sophie Mavrogeni, John R. Laird, Naveed Sattar, Amer M. Johri, Gyan Pareek, Martin Miner, Petros P. Sfikakis, Athanasios Protogerou, Vijay Viswanathan, Aditya Sharma, Georg
    Computers in Biology and Medicine.2020; 126: 104043.     CrossRef
  • Additive and Synergistic Cardiovascular Disease Risk Factors and HIV Disease Markers' Effects on White Matter Microstructure in Virally Suppressed HIV
    Maëliss Calon, Kritika Menon, Andrew Carr, Roland G. Henry, Caroline D. Rae, Bruce J. Brew, Lucette A. Cysique
    JAIDS Journal of Acquired Immune Deficiency Syndromes.2020; 84(5): 543.     CrossRef
  • Performance evaluation of 10-year ultrasound image-based stroke/cardiovascular (CV) risk calculator by comparing against ten conventional CV risk calculators: A diabetic study
    Narendra N. Khanna, Ankush D. Jamthikar, Deep Gupta, Andrew Nicolaides, Tadashi Araki, Luca Saba, Elisa Cuadrado-Godia, Aditya Sharma, Tomaz Omerzu, Harman S. Suri, Ajay Gupta, Sophie Mavrogeni, Monika Turk, John R. Laird, Athanasios Protogerou, Petros P.
    Computers in Biology and Medicine.2019; 105: 125.     CrossRef
  • Cardiovascular risk estimated by UKPDS risk engine algorithm in diabetes
    Nebojsa Kavaric, Aleksandra Klisic, Ana Ninic
    Open Medicine.2018; 13(1): 610.     CrossRef
  • Differential Association of Metabolic Risk Factors with Open Angle Glaucoma according to Obesity in a Korean Population
    Hyun-Ah Kim, Kyungdo Han, Yun-Ah Lee, Jin A Choi, Yong-Moon Park
    Scientific Reports.2016;[Epub]     CrossRef
  • The Association between Diabetic Retinopathy and Framingham Risk Score in Koreans with Type II Diabetes
    Da Yeong Kim, Su Jeong Song, Jeong Hun Bae, Cheol-Young Park, Eun-Jung Rhee
    Journal of the Korean Ophthalmological Society.2016; 57(5): 779.     CrossRef
Smaller Mean LDL Particle Size and Higher Proportion of Small Dense LDL in Korean Type 2 Diabetic Patients
Sunghwan Suh, Hyung-Doo Park, Se Won Kim, Ji Cheol Bae, Alice Hyun-Kyung Tan, Hye Soo Chung, Kyu Yeon Hur, Jae Hyeon Kim, Kwang-Won Kim, Moon-Kyu Lee
Diabetes Metab J. 2011;35(5):536-542.   Published online October 31, 2011
DOI: https://doi.org/10.4093/dmj.2011.35.5.536
  • 5,113 View
  • 39 Download
  • 15 Crossref
AbstractAbstract PDFPubReader   
Background

Small dense low density lipoprotein (sdLDL) has recently emerged as an important risk factor of coronary heart disease.

Methods

The mean LDL particle size was measured in 203 patients with type 2 diabetes mellitus (T2DM) and 212 matched subjects without diabetes using polyacrylamide tube gel electrophoresis. Major vascular complications were defined as stroke, angiographically-documented coronary artery disease or a myocardial infarction. Peripheral vascular stenosis, carotid artery stenosis (≥50% in diameter) or carotid artery plaque were considered minor vascular complications. Overall vascular complications included both major and minor vascular complications.

Results

Diabetic patients had significantly smaller mean-LDL particle size (26.32 nm vs. 26.49 nm) and a higher percentage of sdLDL to total LDL compared to those of subjects without diabetes (21.39% vs. 6.34%). The independent predictors of sdLDL in this study were serum triglyceride level and body mass index (odds ratio [OR], 1.020 with P<0.001 and OR 1.152 with P<0.027, respectively). However, no significant correlations were found between sdLDL and major vascular complications (P=0.342), minor vascular complications (P=0.573) or overall vascular complications (P=0.262) in diabetic subjects.

Conclusion

Diabetic patients had a smaller mean-LDL particle size and higher proportion of sdLDL compared to those of subjects without diabetes. Obese diabetic patients with hypertriglyceridemia have an increased risk for atherogenic small dense LDL. However, we could not verify an association between LDL particle size and vascular complications in this study.

Citations

Citations to this article as recorded by  
  • Evaluation of measured and calculated small dense low-density lipoprotein in capillary blood and association with the metabolic syndrome
    Sara Deza, Inmaculada Colina, Oscar Beloqui, José Ignacio Monreal, Estéfani Martínez-Chávez, Julia Maroto-García, Carmen Mugueta, Alvaro González, Nerea Varo
    Clinica Chimica Acta.2024; 557: 117897.     CrossRef
  • Nrf2 Signaling Pathway as a Key to Treatment for Diabetic Dyslipidemia and Atherosclerosis
    Michelle Yi, Arvin John Toribio, Yusuf Muhammad Salem, Michael Alexander, Antoney Ferrey, Lourdes Swentek, Ekamol Tantisattamo, Hirohito Ichii
    International Journal of Molecular Sciences.2024; 25(11): 5831.     CrossRef
  • Association between measured or calculated small dense low‐density lipoprotein cholesterol and oxidized low‐density lipoprotein in subjects with or without type 2 diabetes mellitus
    Hyun‐Ki Kim, Jinyoung Hong, Sunyoung Ahn, Woochang Lee, Sail Chun, Won‐Ki Min
    Journal of Clinical Laboratory Analysis.2023;[Epub]     CrossRef
  • The association of apolipoprotein in the risk of ST-elevation myocardial infarction in patients with documented coronary artery disease
    Astuti Giantini, Nur Gifarani Pratiwi, Renan Sukmawan, Joedo Prihartono, Suzanna Immanuel, Merci Monica Pasaribu, Sri Suryo Adiyanti, Yusuf Bahasoan
    International Journal of Cardiology Cardiovascular Risk and Prevention.2023; 18: 200194.     CrossRef
  • Atherogenic Index of Plasma and Its Association with Risk Factors of Coronary Artery Disease and Nutrient Intake in Korean Adult Men: The 2013–2014 KNHANES
    Hye Ran Shin, SuJin Song, Jin Ah Cho, Sun Yung Ly
    Nutrients.2022; 14(5): 1071.     CrossRef
  • The Atherogenic Index of Plasma: A Powerful and Reliable Predictor for Coronary Artery Disease in Patients With Type 2 Diabetes
    Kuo Zhou, Zheng Qin, Jinfan Tian, Kongyong Cui, Yunfeng Yan, Shuzheng Lyu
    Angiology.2021; 72(10): 934.     CrossRef
  • Direct bilirubin is associated with low-density lipoprotein subfractions and particle size in overweight and centrally obese women
    Y.-J. Kwon, H.-S. Lee, J.-W. Lee
    Nutrition, Metabolism and Cardiovascular Diseases.2018; 28(10): 1021.     CrossRef
  • Correlation between Cholesterol, Triglycerides, Calculated, and Measured Lipoproteins: Whether Calculated Small Density Lipoprotein Fraction Predicts Cardiovascular Risks
    Sikandar Hayat Khan, Nadeem Fazal, Athar Abbas Gilani Shah, Syed Mohsin Manzoor, Naveed Asif, Aamir Ijaz, Najmusaqib Khan Niazi, Muhammad Yasir
    Journal of Lipids.2017; 2017: 1.     CrossRef
  • Effects of Small Dense LDL in Diabetic Nephropathy in Females with Type 2 Diabetes Mellitus
    Seongyul Ryu, Youngwoo Kim, Mee Kyoung Kim, Hyuk-Sang Kwon, Ki-Hyun Baek, Ki-Ho Song, Kyung-Jin Yun
    Journal of Lipid and Atherosclerosis.2016; 5(1): 11.     CrossRef
  • Prepregnancy Adverse Lipid Profile and Subsequent Risk of Gestational Diabetes
    Emily S. Han, Ronald M. Krauss, Fei Xu, Sneha B. Sridhar, Assiamira Ferrara, Charles P. Quesenberry, Monique M. Hedderson
    The Journal of Clinical Endocrinology & Metabolism.2016; 101(7): 2721.     CrossRef
  • Meta-analysis of Atherogenic Index of Plasma and other lipid parameters in relation to risk of type 2 diabetes mellitus
    Xiao-Wei Zhu, Fei-Yan Deng, Shu-Feng Lei
    Primary Care Diabetes.2015; 9(1): 60.     CrossRef
  • Higher levels of small dense low‐density lipoprotein (LDL) are associated with cardiac autonomic neuropathy in patients with Type 2 diabetes
    E.‐H. Jang, Y.‐M. Park, J. Hur, M.‐K. Kim, S.‐H. Ko, K.‐H. Baek, K.‐H. Song, K.‐W. Lee, H.‐S. Kwon
    Diabetic Medicine.2013; 30(6): 694.     CrossRef
  • Sleep Status and Low-Density Lipoprotein Particle Size in a General Japanese Female Population: The Mima Study
    Kazuhiko Kotani, Kokoro Tsuzaki, Shinji Fujiwara, Naoki Sakane
    Medical Principles and Practice.2013; 22(5): 510.     CrossRef
  • Serum small-dense LDL abnormalities in chronic renal disease patients
    M. Chu, A. Y. M. Wang, I. H. S. Chan, S. H. Chui, C. W. K. Lam
    British Journal of Biomedical Science.2012; 69(3): 99.     CrossRef
  • Small Dense Low-density Lipoprotein and Cardiovascular Disease
    Sunghwan Suh, Moon-Kyu Lee
    Journal of Lipid and Atherosclerosis.2012; 1(1): 1.     CrossRef
Comparison of the Predictability of Cardiovascular Disease Risk According to Different Metabolic Syndrome Criteria of American Heart Association/National Heart, Lung, and Blood Institute and International Diabetes Federation in Korean Men.
Do Young Lee, Eun Jung Rhee, Eun Suk Choi, Ji Hoon Kim, Jong Chul Won, Cheol Young Park, Won Young Lee, Ki Won Oh, Sung Woo Park, Sun Woo Kim
Korean Diabetes J. 2008;32(4):317-327.   Published online August 1, 2008
DOI: https://doi.org/10.4093/kdj.2008.32.4.317
  • 2,766 View
  • 19 Download
  • 7 Crossref
AbstractAbstract PDF
BACKGROUND
We compared the prevalences of two criteria of metabolic syndrome, that is, American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) and International Diabetes Federation (IDF), in Korean male adults and compared the predictability of insulin resistance and future cardiovascular diseases using Framingham Risk Score. METHODS: In total 23,467 male adults (mean age 43.3 years) who participated in medical check-up in 2005, the prevalences of metabolic syndrome according to AHA/NHLBI and IDF criteria and the presence of insulin resistance, defined by the highest quartile of Homeostasis Model Assessment of insulin resistance index (HOMA-IR), were compared. The relative risk (calculated risk/average risk) for 10-year risk for coronary artery disease (CHD) assessed by Framingham Risk Score were compared. RESULTS: 5.8% of the subjects had diabetes mellitus. 20.7% and 13.2%of the subjects had metabolic syndrome defined by AHA/NHLBI and IDF criteria, and the two criteria showed high agreement with kappa value of 0.737 (P < 0.01). More subjects in IDF-defined group had insulin resistance compared with AHA/NHLBI definition (59.8 vs. 54%, P < 0.01). The odds ratio for increased relative risk (> 1.0) for 10-year CHD were higher in AHA/NHLBI-defined subjects compared with IDF-defined subject (3.295 vs. 3.082). The Kappa values for the analysis of agreement between each criteria and prediction of insulin resistance or cardiovascular disease risk, were too low for comparison. CONCLUSION: In Korean males, the prevalence for metabolic syndrome defined by AHA/NHLBI criteria was higher than those defined by IDF criteria. IDF criteria detected more subjects with insulin resistance, but didn't have better predictability for CHD compared with AHA/NHLBI criteria.

Citations

Citations to this article as recorded by  
  • Attention Aware Deep Learning Approaches for an Efficient Stress Classification Model
    Muhammad Zulqarnain, Habib Shah, Rozaida Ghazali, Omar Alqahtani, Rubab Sheikh, Muhammad Asadullah
    Brain Sciences.2023; 13(7): 994.     CrossRef
  • Statistics and Deep Belief Network-Based Cardiovascular Risk Prediction
    Jaekwon Kim, Ungu Kang, Youngho Lee
    Healthcare Informatics Research.2017; 23(3): 169.     CrossRef
  • Relationship between Abdominal Fat Area Measured by Screening Abdominal Fat CT and Metabolic Syndrome in Asymptomatic Korean Individuals
    Dae Woong Park, Noh Hyuck Park, Ji Yeon Park, Seon-Jeong Kim
    Journal of the Korean Society of Radiology.2017; 77(1): 1.     CrossRef
  • Data-Mining-Based Coronary Heart Disease Risk Prediction Model Using Fuzzy Logic and Decision Tree
    Jaekwon Kim, Jongsik Lee, Youngho Lee
    Healthcare Informatics Research.2015; 21(3): 167.     CrossRef
  • Implication of high‐body‐fat percentage on cardiometabolic risk in middle‐aged, healthy, normal‐weight adults
    Ji Young Kim, Sang‐Hwan Han, Bong‐Min Yang
    Obesity.2013; 21(8): 1571.     CrossRef
  • Cardio-Metabolic Features of Type 2 Diabetes Subjects Discordant in the Diagnosis of Metabolic Syndrome
    Sa Rah Lee, Ying Han, Ja Won Kim, Ja Young Park, Ji Min Kim, Sunghwan Suh, Mi-Kyoung Park, Hye-Jeong Lee, Duk Kyu Kim
    Diabetes & Metabolism Journal.2012; 36(5): 357.     CrossRef
  • Comparison of Cardiovascular Health Status and Health Behaviors in Korean Women based on Household Income
    Young-Joo Park, Nah-Mee Shin, Ji-Won Yoon, Jiwon Choi, Sook-Ja Lee
    Journal of Korean Academy of Nursing.2010; 40(6): 831.     CrossRef
Value of Coronary Calcium Score in Type 2 Diabetics.
Ji Eun Lee, Mi Jung Eun, Kyung Ah Chun, Jae Hong Kim, Ji Sung Yoon, Ihn Ho Cho, Kyu Chang Won, Hyoung Woo Lee
Korean Diabetes J. 2006;30(4):303-311.   Published online July 1, 2006
DOI: https://doi.org/10.4093/jkda.2006.30.4.303
  • 2,447 View
  • 17 Download
AbstractAbstract PDF
BACKGROUND
Cardiovascular disease including coronary heart disease (CHD) is the most common cause of morbidity and mortality in patients with diabetes. But traditional risk factor assessment is limited to predict CHD in asymptomatic high-risk individuals. In this study, relationship between coronary calcium score (CCS) and CHD was evaluated to determine value of coronary artery calcification detected by multi-slice spiral computed tomography to predict CHD in high risk asymptomatic patients with type 2 diabetes. METHODS: 127 patients were enrolled who admitted in Yeungnam University Hospital between December 2004 and May 2005. Standard cardiovascular risk factors and the CCS measured by multi-slice spiral computed tomography were assessed. RESULTS: Enrolled subjects were consisted of 56 subjects with diabetes and 71 subjects without diabetes. The mean CCS was significantly greater in patients with diabetes than without diabetics (P < 0.01). In both groups, patients with higher CCS had higher prevalence of CHD (P < 0.05). In all subjects, LDL cholesterol levels and CCS were significantly associated in multi-variate analysis (P < 0.05). In patients without diabetes, age was only associated with presence of CHD (P < 0.05). CCS was only associated with CHD in patients with diabetes, even after adjusting for the effects of age, LDL cholesterol and CRP (P < 0.05). CONCLUSION: Therefore, multi-slice spiral computed tomography can non-invasively and accurately detect coronary calcification. By detection of coronary artery calcification, it may be possible to predict coronary heart disease early in high-risk asymptomatic patients with type 2 diabetes.
The Association of Pro12Ala Polymorphism in PPAR-gamma Gene with Coronary Artery Disease in Korean Subjects.
Chang Hee Kwon, Eun Jung Rhee, Se Yeon Kim, Eun Ran Kim, Chang Uk Chon, Chan Hee Jung, Ji Ho Yun, Byung Jin Kim, Ki Chul Sung, Bum Su Kim, Won Young Lee, Ki Won Oh, Jin Ho Kang, Sun Woo Kim, Man Ho Lee, Jung Roe Park
Korean Diabetes J. 2006;30(2):122-129.   Published online March 1, 2006
DOI: https://doi.org/10.4093/jkda.2006.30.2.122
  • 2,351 View
  • 16 Download
AbstractAbstract PDF
BACKGROUND
PPAR-gamma, a member of nuclear family, which is involved in the differentiation of adipose tissue, is reported to be associated in the pathogenesis of type 2 diabetes mellitus, insulin resistance and atherosclerosis. We conducted a research to see whether the prevalence of coronary artery disease is associated with Pro12Ala polymorphism in exon B of PPAR-gamma in Korean adults. METHODS: The study was conducted in 161 subjects (97 males, 64 females, mean age 57 year old) who underwent coronary angiogram due to chest pain. We assessed cardiovascular risk factors in all subjects, such as blood pressure, body mass index (BMI), fasting blood sugar and serum lipid profiles. Subjects were divided into four groups as normal, 1-vessel, 2-vessel and 3-vessel disease according to the number of stenosed coronary arteries. Genotypings of Pro12Ala polymorphism were done with Real-time polymerase chain reaction. RESULTS: Allelic frequency for proline was 0.957 and 0.043 for alanine, and they were in compliance with Hardy-Weinberg equilibrium (P = 0.85). 79 subjects (43.5%) had normal coronary artery, 52 subjects (31%), 1-vessel disease, 24 subjects (14.9%), 2-vessel disease and 15 subjects (9.3%), 3-vessel disease. When the cardiovascular risk factors were compared among these four groups, there were no meaningful differences except the age and high-density lipoprotein cholesterol levels, which were lost after adjustment for age and BMI. There were no significant differences in the prevalence or severity of coronary artery diseases according to the different genotypes of Pro12Ala polymorphism. CONCLUSIONS: There was no significantassociation between Pro12Ala polymorphism in exon B of PPAR-gamma and prevalence or severity of coronary artery disease in Korean adults. It is considered that further studies on the correlation between Pro12Ala polymorphism and coronary artery disease should be carried out in larger Korean population in the future

Diabetes Metab J : Diabetes & Metabolism Journal
Close layer