The DOI matches its Crossref record; 38 of the 40 references it cites were found in a registry or an index.
Low-grade inflammation may play a role in the etiology of the metabolic syndrome in patients with coronary heart disease: the HIFMECH study
Abstract
Risk of coronary heart disease has been related to insulin resistance, but the mechanism for this is incompletely understood. Variables attributed to insulin resistance are associated with low-grade inflammation. A case-control study was performed of 469 male myocardial infarction (MI) survivors aged < 60 years and 575 control subjects recruited from centers in northern and southern Europe. Principal factor analysis was used to explore correlations between insulin resistance and inflammatory variables. Three factors resulted: (a) "Metabolic Syndrome" (insulin/proinsulin/ triglyceride/body mass index [BMI]); (b) "Inflammation" (fibrinogen/C-reactive protein [CRP]/interleukin-6 [IL-6]); and (c) "Blood Pressure" (systolic and diastolic blood pressure). The "Metabolic Syndrome" factor was related to the "Inflammation" factor (largely independently of obesity), the "Blood Pressure" factor, smoking, and south location (all P < or = .0002). There were significant relationships between all 3 factors and case status (P < or = .0002). Markers of low-grade inflammation are strongly related to metabolic syndrome variables independently of obesity. This raises the possibility that links between insulin resistance and cardiovascular disease could, in part, represent common consequences of low-grade inflammation.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“MetS consists of elements that do not aggregate by chance alone and are causally inter-related, and each element contributes independently to an increased risk for ASCVD (3).”
From The CardioMetabolic Health Alliance (2015) · cites this paper as [3]
Citations
Cites
Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C. (1985) · Diabetologia · doi:10.1007/bf00280883 · Cited by 31,502
Role of Insulin Resistance in Human Disease
Reaven, G. M. (1988) · Diabetes · doi:10.2337/diab.37.12.1595 · Cited by 12,154
Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men
Ridker, P. M., Cushman, M., Stampfer, M. J., Tracy, R. P., & Hennekens, C. H. (1997) · New England Journal of Medicine · doi:10.1056/nejm199704033361401 · Cited by 5,504
The metabolic syndrome and total and cardiovascular disease mortality in middle-aged men
Lakka, H.-M. (2002) · JAMA · doi:10.1001/jama.288.21.2709 · Cited by 5,033
Banting lecture 1988. Role of insulin resistance in human disease.
Reaven, G. (1988) · Diabetes · doi:10.2337/diabetes.37.12.1595 · Cited by 3,801
Hotamisligil, G. S., Arner, P., Caro, J. F., Atkinson, R. L., & Spiegelman, B. M. (1995) · Journal of Clinical Investigation · doi:10.1172/jci117936 · Cited by 3,543
A step-by-step approach to using the SAS system for factor analysis and structural equation modeling
(1995) · Choice Reviews Online · doi:10.5860/choice.33-0366 · Cited by 3,359
Yudkin, J. S., Stehouwer, C. D. A., Emeis, J. J., & Coppack, S. W. (1999) · Arteriosclerosis, Thrombosis, and Vascular Biology · doi:10.1161/01.atv.19.4.972 · Cited by 2,465
Self-citationRidker, P. M., Rifai, N., Stampfer, M. J., & Hennekens, C. H. (2000) · Circulation · doi:10.1161/01.cir.101.15.1767 · Cited by 2,429
Chronic Subclinical Inflammation as Part of the Insulin Resistance Syndrome
Festa, A., D’Agostino, R., Howard, G., Mykkänen, L., Tracy, R. P., & Haffner, S. M. (2000) · Circulation · doi:10.1161/01.cir.102.1.42 · Cited by 2,366
Flagged first, then by citations
2 of the 40 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 101–153 of 153
Ekholm, M., Kahan, T., Jörneskog, G., Brinck, J. W., & Wallén, N. H. (2015) · Journal of the Renin-Angiotensin-Aldosterone System · doi:10.1177/1470320315575848 · Cited by 13
Moncayo, R., & Moncayo, H. (2007) · BMC Musculoskeletal Disorders · doi:10.1186/1471-2474-8-17 · Cited by 13
Salobir, B., & Šabović, M. (2006) · Blood Coagulation & Fibrinolysis · doi:10.1097/01.mbc.0000245298.64644.0a · Cited by 12
Dysregulation of monocyte biology in metabolic syndrome
Jialal, I., Devaraj, S., & Rajamani, U. (2014) · Expert Review of Endocrinology & Metabolism · doi:10.1586/17446651.2014.890046 · Cited by 12
Tsoukas, M. A., Farr, O. M., & Mantzoros, C. S. (2013) · Metabolism · doi:10.1016/j.metabol.2013.09.003 · Cited by 11
Song, Y., Ma, Y., Zhang, K., Zhang, W., Xiong, G., Qi, T., Shi, J., Qiu, H., Zhang, J., Han, F., et al. (2023) · Biochemical and Biophysical Research Communications · doi:10.1016/j.bbrc.2023.08.008 · Cited by 11
Yin, H., Chen, W., Dong, L., Zhou, S., Qu, Q., Zhang, N., & He, X. (2022) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-022-00880-3 · Cited by 11
Weiss, R., & Caprio, S. (2008) · Endocrine Research · doi:10.1080/07435800802080211 · Cited by 10
Pang, H., Zhang, C., Liu, F., Gong, X., Jin, X., & Su, C. (2016) · Medicina Intensiva · doi:10.1016/j.medin.2016.10.008 · Cited by 9
Lee, I., Lin, T. M., Lee, W., Ou, H., Chien, Y.-H., Lee, W.-L., Tang, Y., Yang, C.-H., & Sheu, W. H. (2005) · Metabolism · doi:10.1016/j.metabol.2005.05.012 · Cited by 8
Ragab, M., Hassan, H., Zaytoun, T., Refai, W., Rocks, B. F., & Elsammak, M. (2005) · PubMed Central · Cited by 8
González‐Muniesa, P., Bing, C., & Trayhurn, P. (2010) · Hormone and Metabolic Research · doi:10.1055/s-0030-1255119 · Cited by 8
Javorský, M., Kozárová, M., Salagovic, J., & Tkáč, I. (2006) · Physiological Research · doi:10.33549/physiolres.930704 · Cited by 8
Rezania, K., Soliven, B. C., Rezai, K. A., & Roos, R. P. (2011) · Medical Hypotheses · doi:10.1016/j.mehy.2010.12.012 · Cited by 8
Sarmiento-Cobos, M. F., Alemán, R., Gómez, C. O., Montorfano, L. M., Wasser, E. J., Menzo, E. L., Szomstein, S., & Rosenthal, R. J. (2020) · Surgery for Obesity and Related Diseases · doi:10.1016/j.soard.2020.09.018 · Cited by 7
Pathogenesis and Biomarkers of Metabolic Syndrome
Hurza, V., Vatashchuk, M., & Bayliak, M. M. (2022) · Journal of Vasyl Stefanyk Precarpathian National University · doi:10.15330/jpnu.8.4.7-19 · Cited by 7
Dietary patterns in relation to inflammation in shift workers
Khorasaniha, R., Siassi, F., Khajehnasiri, F., Qorbani, M., & Sotoudeh, G. (2019) · BMJ Military Health · doi:10.1136/jramc-2018-001119 · Cited by 5
Soliman, G. Z. A. (2005) · The Egyptian Journal of Hospital Medicine · doi:10.21608/ejhm.2005.18050 · Cited by 5
Kim, U. J., Choi, E. J., Park, H., Lee, H. A., Park, B., Kim, H., Hong, Y., Jung, S., & Park, H. (2022) · Nutrients · doi:10.3390/nu14112339 · Cited by 5
Mayes, T., Gottschlich, M. M., Khoury, J. C., Simakajornboon, N., & Kagan, R. J. (2013) · Journal of Burn Care & Research · doi:10.1097/bcr.0b013e3182a2a89c · Cited by 4
Lee, I., Lee, W., Ou, H., Huang, C., & Sheu, W. H. (2009) · Metabolism · doi:10.1016/j.metabol.2008.10.019 · Cited by 4
Lee, M. G., Jeong, M. H., Ahn, Y., Chae, S. C., Hur, S., Hong, T. J., Kim, Y. J., Seong, I. W., Chae, J. K., Rhew, J. Y., et al. (2012) · International Journal of Cardiology · doi:10.1016/j.ijcard.2012.03.102 · Cited by 4
Ghazizadeh, H., Yaghooti‐Khorasani, M., Darroudi, S., Esmaily, H., Sharifan, P., Tayefi, M., Seyedi, S. M. R., Mohammadi‐Bajgiran, M., Zirak, R. G., Tavallaie, S., et al. (2020) · Obesity Medicine · doi:10.1016/j.obmed.2020.100277 · Cited by 4
Shafeeq, N. K., Hussein, T. A., & Abass, E. A. (2021) · Ibn AL- Haitham Journal For Pure and Applied Science · doi:10.30526/34.3.2675 · Cited by 5
The Role of C-reactive Protein as a Inflammation-related Factor in Metabolic Syndrome
Park, J. S., Kim, Y. J., Lee, J. G., Kim, Y., Lee, S. Y., Min, H., & Cho, B. M. (2009) · Korean Journal of Family Medicine · doi:10.4082/kjfm.2009.30.6.449 · Cited by 3
Zhang, X.-T., Qiu, W.-Y., Huang, J.-J., Pang, X., Su, Y., Ye, J.-L., Zhou, S., Tang, Z.-X., Wang, R.-M., & Su, R.-S. (2024) · Journal of diabetes and its complications · doi:10.1016/j.jdiacomp.2024.108805 · Cited by 3
Does high sensitive CRP improve cardiovascular risk prediction in metabolic syndrome among the aged?
Salminen, M. J., Kuoppamäki, M., Vahlberg, T. J., Räihä, I. J., Irjala, K. M. A., & Kivelä, S. (2013) · Scandinavian Cardiovascular Journal · doi:10.3109/14017431.2013.798427 · Cited by 3
The Marie-Josée and Henry R. Kravis Center for Clinical Cardiovascular Health at Mount Sinai Heart
Johnson, J. H., Al‐Kazaz, M., & Mechanick, J. I. (2020) · Springer eBooks · doi:10.1007/978-3-030-48088-2_27 · Cited by 2
Inflammation, Atherosclerosis, and Psychological Factors
Suarez, E. C. (2022) · Springer eBooks · doi:10.1007/978-0-387-85960-6_35 · Cited by 2
Association of plasma fibrinogen and development of complications in type 2 diabetes mellitus
Patel, H. V., Sumple, R. S., Pooja Harshitha, K., & Sumple, K. R. (2023) · International Journal of Research in Medical Sciences · doi:10.18203/2320-6012.ijrms20231315 · Cited by 3
Li, J., Song, S.-J., Xu, J.-P., Zhao, X., Xu, Z., Sun, X.-J., Wang, L. F., & Yang, X. (2014) · Herz · doi:10.1007/s00059-014-4103-4 · Cited by 2
A case of acanthosis nigricans in a HIV-infected patient
Iacovelli, A., Mezzaroma, I., Paolo, M. D., Soda, G., Vincentiis, L. D., & Palange, P. (2020) · BMC Infectious Diseases · doi:10.1186/s12879-020-05089-1 · Cited by 2
Friebe, H., & Peters, A. (2005) · Der Orthopäde · doi:10.1007/s00132-005-0821-x · Cited by 2
Petrović, I., Milosavljević, M. N., & Pejčić, A. V. (2026) · Medical Sciences · doi:10.3390/medsci14020303 · Cited by 1
Han, G. (2015) · DigitalCommons@UNMC · Cited by 1
Oxidative Stress, Uric Acid, Vascular Inflammation in Non-Smoking Metabolic Syndrome Patients
Grigore, C., Stoian, I. A.-M., Grigore, O., Dawkins, L., Isacoff, D., Bruckner, I., & Davila, C. (2010) · Cited by 1
Shiga, T. (2016) · PubMed · Cited by 1
Verma, A., Chandra, U. K., Verma, S., Jhavar, D., & Badole, S. (2019) · International Journal of Advances in Medicine · doi:10.18203/2349-3933.ijam20195242 · Cited by 1
Pang, H., Zhang, C., Liu, F., Gong, X., Jin, X., & Su, C. (2017) · Medicina Intensiva (English Edition) · doi:10.1016/j.medine.2016.10.012 · Cited by 1
Leukocyte Count as Chronic Inflammation Markers in Type 2 Diabetes Patients
Durmuş, E., Aypak, C., & Görpelioğlu, S. (2017) · Ankara Medical Journal · doi:10.17098/amj.364164 · Cited by 1
Marı́n-Garcı́a, J. (2011) · Springer eBooks · doi:10.1007/978-1-4419-9461-5_18 · Cited by 1
Regulation of obesity-associated inflammation and colon tumorigenesis by resveratrol and adiponectin
Boddicker, R. L. (2011) · Iowa State University Digital Repository (Iowa State University) · doi:10.31274/etd-180810-2602 · Cited by 1
Weiss, R., & Caprio, S. (2008) · CRC Press eBooks · doi:10.3109/9781420047981-9 · Cited by 1
Inflammation and Genetics of Inflammation in Cardiovascular Diseases
Bucová, M. (2011) · InTech eBooks · doi:10.5772/21071
Women's Hearts - Ischaemic Heart Disease and Stress Management in Women
Claesson, M. (2006) · KTH Publication Database DiVA (KTH Royal Institute of Technology)
Development of an aptamer based lateral flow test strip for a diabetes biomarker
Moabelo, K. L. (2019) · University of the Western Cape Electronic Theses and Dissertations Repository (University of the Western Cape)
Jiang, B. W. L., & Ag, S. B. (2011)
Whole-body systems approaches for gut microbiota-targeted, preventive healthcare
Zhaoa, I., & Shena, J. (2010)
Advances in Anti-inflammatory Therapies for Cardiovascular Disease and Atherosclerosis
Noman, A. A., Sejuti, S. R., Anuva, N. J., Nabin, M. N. R., Noman, M. J. I., Islam, M. H., Rahman, A., Tanme, T. A., Afrose, F., Hosen, M. N., et al. (2025) · Current Signal Transduction Therapy · doi:10.2174/0115743624366056250407071501
Mukhtar, R. (2013) · The University of Bath Online Publications Store (The University of Bath)
Telomere length in cardiovascular disease and type 2 diabetes
Salpea, K. D. (2011) · UCL Discovery (University College London)
Obesity and adipose tissue expansion in Ossabaw swine
Faris, R. J. (2013) · Iowa State University Digital Repository (Iowa State University) · doi:10.31274/etd-180810-3143
Metadata
- Authors
- Yudkin, J. S., Juhan-Vague, I., Hawe, E., Humphries, S. E., di Minno, G., Margaglione, M., Tremoli, E., Kooistra, T., Morange, P. E., Lundman, P., Mohamed-Ali, V, & Hamsten, A.
- Affiliations
- University College London (GB)
- The Royal Free Hospital (GB)
- Casa Sollievo della Sofferenza (IT)
- University of Milan (IT)
- Netherlands Organisation for Applied Scientific Research (NL)
- Hôpital de la Timone (FR)
- Karolinska University Hospital (SE)
- Corresponding author
- Yudkin, J.S
- Venue
- Metabolism
- Publisher
- Elsevier BV
- Published
- 2004-07
- Volume
- 53
- Issue
- 7
- Pages
- 852-857
- ISSN
- 0026-0495 (ISSN-L)
- OpenAlex
- W2123585924
- Cited by
- 153
- References
- 40
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 2 · 2022: 7 · 2021: 2 · 2020: 4 · 2019: 6 · 2018: 2 · 2017: 4 · 2016: 4 · 2015: 7 · 2014: 8 · 2013: 9 · 2012: 4
- FWCI
- 11.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Metabolism (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Topics
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Adipokines, Inflammation, and Metabolic Diseases
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Oncology › Inflammatory Biomarkers in Disease Prognosis
- Keywords
- low-grade inflammation, metabolic syndrome, coronary artery disease, insulin resistance, myocardial infarction survivors, C-reactive protein, fibrinogen, interleukin-6, blood pressure, obesity
- MeSH terms
- Aged, Blood Pressure, Coronary Disease, Europe, Factor Analysis, Statistical, Fibrinolysis, Humans, Inflammation, Male, Middle Aged, Myocardial Infarction, Risk Factors, Cohort Studies, Body Mass Index, Cluster Analysis, Survivors, Thrombophilia, Metabolic Syndrome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review