Research Article
BibTex RIS Cite

Assessment of the relationship between insulin resistance, atherogenic index of plasma and white blood cell count: A data mining study

Year 2017, Volume: 39 Issue: 2, 479 - 486, 16.05.2017
https://doi.org/10.7197/223.v39i29491.316368

Abstract

Objective: The hyperinsulinemic-euglycemic clamp
tests considered as a gold standard method for assessing the insulin
sensitivity, whereas the application of this test in large groups is both
difficult and not practical, therefore clinicians need calculating parameters
to evaluate the insulin sensitivity. In the study we evaluated the prediction
of insulin resistance (IR) by atherogenic index of plasma (AIP) and WBC count.

Method: We retrospectively reviewed the
records of 139.934 individuals admitted to our hospital from March 2015 to
March 2016.  474 individuals were
enrolled in our study. Study population’s records such as age, gender, white
blood cell (WBC) count and the concentrations of overnight fasting blood
glucose, triglyceride (TG), total cholesterol (TCHOL), HDL-C, low density
lipoprotein cholesterol (LDL-C) and insulin were recorded from our hospital
information system.

Results: The receiver operating characteristic
curves (AUC) of AIP for predicting IR were 0.670 and 0.690 as measured by
homeostatic model assessment-insulin resistance (HOMA-IR) and insulin
sensitivity check index (QUICKI), respectively. The area under the curve (AUC)
values for predicting IR with WBC count were 0.649 and 0.652 as measured by HOMA-IR
and QUICKI, respectively.







Conlusions: Negative predictive values of AIP and
WBC were found higher than positive predictive values as measured HOMA-IR. AIP
and WBC may not serve as a predictor of IR lonely but these markers might be
used as surrogate markers may contribute to excluding IR when used in
combination with HOMA-IR and QUICKI.

References

  • 1. Steinberger J, Daniels SR; American Heart Association Atherosclerosis, Hypertension, and Obesity in the Young Committee (Council on Cardiovascular Disease in the Young); American Heart Association Diabetes Committee (Council on Nutrition, Physical Activity, and Metabolism). Obesity, insulin resistance, diabetes, and cardiovascular risk in children: an American Heart Association scientific statement from the Atherosclerosis, Hypertension, and Obesity in the Young Committee (Council on Cardiovascular Disease in the Young) and the Diabetes Committee (Council on Nutrition, Physical Activity, and Metabolism). Circulation 2003; 18: 1448-53.
  • 2. Tam CS, Xie W, Johnson WD, Cefalu WT, Redman LM, Ravussin E. Defining insulin resistance from hyperinsulinemic-euglycemic clamps. Diabetes Care 2012; 35: 1605-10.
  • 3. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000; 85: 2402-10.
  • 4. Miller WG, Thienpont LM, Van Uytfanghe K, Clark PM, Lindstedt P, Nilsson G, Steffes MW; Insulin Standardization Work Group. Toward standardization of insulin immunoassays. Clin Chem 2009; 55: 1011-8.
  • 5. Vozarova B, Weyer C, Lindsay RS, Pratley RE, Bogardus C, Tataranni PA. High white blood cell count is associated with a worsening of insulin sensitivity and predicts the development of type 2 diabetes. Diabetes 2002; 51: 455-61.
  • 6. Nakanishi N, Yoshida H, Matsuo Y, Suzuki K, Tatara K. White blood-cell count and the risk of impaired fasting glucose or Type II diabetes in middle-aged Japanese men. Diabetologia 2002; 45: 42-8.
  • 7. Yamamoto E, Sugiyama S, Hirata Y, Tokitsu T, Tabata N, Fujisue K, Sugamura K, Sakamoto K, Tsujita K, Matsumura T, Kaikita K, Hokimoto S. Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease. Atherosclerosis. 2016; 255: 210-6.
  • 8. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO, Criqui M, Fadl YY, Fortmann SP, Hong Y, Myers GL, Rifai N, Smith SC Jr, Taubert K, Tracy RP, Vinicor F. Centers for Disease Control and Prevention; American Heart Association. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: A statement for health care professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003; 28: 499-511.
  • 9. Chen LK, Lin MH, Chen ZJ, Hwang SJ, Chiou ST. Association of insulin resistance and hematologic parameters: Study of a middle-aged and elderly Chinese population in Taiwan. J Chin Med Assoc 2006; 69: 248-53.
  • 10. Lewis GF, Steiner G. Hypertriglyceridemia and its metabolic consequences as a risk factor for atherosclerotic cardiovascular disease in non-insulin-dependent diabetes mellitus. Diabetes Metab Rev 1996; 12: 37-56.
  • 11. Brinck JW, Thomas A, Lauer E, Jornayvaz FR, Brulhart-Meynet MC, Prost JC, Pataky Z, Löfgren P, Hoffstedt J, Eriksson M, Pramfalk C, Morel S, Kwak BR, van Eck M, James RW, Frias MA. Diabetes Mellitus Is Associated With Reduced High-Density Lipoprotein Sphingosine-1-Phosphate Content and Impaired High-Density Lipoprotein Cardiac Cell Protection. Arterioscler Thromb Vasc Biol 2016; 36: 817-24.
  • 12. McLaughlin T, Reaven G, Abbasi F, Lamendola C, Saad M, Waters D, Simon J, Krauss RM: Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am J Cardiol 2005, 96: 399-404.
  • 13. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med 2003; 139: 802-9.
  • 14. Kim-Dorner SJ, Deuster PA, Zeno SA, Remaley AT, Poth M: Should triglycerides and the triglycerides to high-density lipoprotein cholesterol ratio be used as surrogates for insulin resistance? Metabolism 2010; 59: 299-304.
  • 15. Mostafa SA, Davies MJ, Morris DH, Yates T, Srinivasan BT, Webb D, Brady E, Khunti K. The association of the triglyceride-to-HDL cholesterol ratio with insulin resistance in White European and South Asian men and women. PLoS One 2012; 7: e50931.
  • 16. Deng QW, Wang H, Sun CZ, Xing FL, Zhang HQ, Zuo L, Gu ZT, Yan FL. Triglyceride to high-density lipoprotein cholesterol ratio predicts worse outcomes after acute ischaemic stroke. Eur J Neurol 2017; 24: 283-91.
  • 17. Dobiasova M. Atherogenic index of plasma [log(triglycerides/HDL-cholesterol)]: theoretical and practical implications. Clin Chem 2004; 50: 1113-5.
  • 18. Yamada C, Mitsuhashi T, Hiratsuka N, Inabe F, Araida N, Takahashi E. Optimal reference interval for homeostasis model assessment of insulin resistance in a Japanese population. J Diabetes Investig 2011; 2: 373-7
  • 19. Salgado AL, CarvalhoLd, Oliveira AC, Santos VN, Vieira JG, Parise ER. Insulin resistance index (HOMA-IR) in the differentiation of patients with non-alcoholic fatty liver disease and healthy individuals. Arq Gastroenterol 2010; 47: 165-9.
  • 20. McAuley KA, Williams SM, Mann JI, Walker RJ, Ledwis-Barned NJ, Temple LA, Duncan AS. Diagnosing insulin resistance in the general population. Diabetes Care 2001; 24: 460-4.
  • 21. Jellinger PS, Mehta AE, Handelsman Y, Shepherd MD. American association of clinical endocrinologist’s guidelines for management of dyslipidemia and prevention of atherosclerosis. Endocrine Practice 2012; 18(sup 1): 3-78.
  • 22. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412-9.
  • 23. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000; 85: 2402-10.
  • 24. Kimm H, Lee SW, Lee HS, Shim KW, Cho CY, Yun JE, Jee SH. Associations between lipid measures and metabolic syndrome, insulin resistance and adiponectin. Usefulness of lipid ratios in Korean men and women. Circ J 2010; 74: 931-7.
  • 25. Kannel WB, Vasan RS, Keyes MJ, Sullivan LM, Robins SJ. Usefulness of the triglyceride-high-density lipoprotein versus the cholesterol-high-density lipoprotein ratio for predicting insulin resistance and cardiometabolic risk (from the Framingham Offspring Cohort). Am J Cardiol 2008; 101: 497-501.
  • 26. Piedrola G, Novo E, Escobar F, Garcia-Robles R. White blood cell count and insulin resistance in patients with coronary artery disease. Ann Endocrinol (Paris) 2001; 62: 7-10.
  • 27. Twig G, Afek A, Shamiss A, Derazne E, Tzur D, Gordon B, Tirosh A. White blood cells count and incidence of type 2 diabetes in young men. Diabetes Care 2013; 36: 276-82.
  • 28. Chao TT, Hsieh CH, Lin JD, Wu CZ, Hsu CH, Pei D, Chen YL, Liang YJ, Chang JB. Use of white blood cell counts to predict metabolic syndrome in the elderly: a 4 year longitudinal study. Aging Male 2014; 17: 230-7.
  • 29. Oda E, Kawai R. Comparison between high-sensitivity C-reactive protein (hs-CRP) and white blood cell count (WBC) as an inflammatory component of metabolic syndrome in Japanese. Intern Med 2010; 49: 117-24.
  • 30. Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 1988; 37: 1595-607.
  • 31. Lamarche B, Lewis GF. Atherosclerosis prevention for the next decade: risk assessment beyond low density lipoprotein cholesterol. Can J Cardiol 1998; 14: 841-51.
  • 32. Ginsberg HN. Lipoprotein physiology in nondiabetic and diabetic states. Relationship to atherogenesis. Diabetes Care 1991; 14: 839-55.
  • 33. Taskinen MR. Diabetic dyslipidaemia: from basic research to clinical practice. Diabetologia 2003; 46: 733-49.
  • 34. Howard BV. Lipoprotein metabolism in diabetes mellitus. J Lipid Res 1987; 28: 613-28
  • 35. Temelkova-Kurktschiev T, Hanefeld M. The lipid triad in type 2 diabetes—prevalence and relevance of hypertriglyceridaemia/low high-density lipoprotein syndrome in type 2 diabetes. Exp Clin Endocrinol Diabetes 2004; 112: 75-9.
  • 36. Karhapaa P, Voutilainen E, Kovanen PT, Laakso M. Insulin resistance in familial and nonfamilial hypercholesterolemia. Arterioscler Thromb 1993; 13: 41-7.
  • 37. Rashid, S, Uffelman, K, Lewis, GF. The mechanism of HDL lowering in hypertriglyceridemic, insulin resistant states. J Diabetes Complications 2002; 16: 24-28.
  • 38. Mann CJ, Yen FT, Grant AM, et al. Mechanism of plasma cholesteryl ester transfer in hypertriglyceridemia. J Clin Invest 1991; 88: 2059-66.
  • 39. Föger B, Ritsch A, Doblinger A, Wessels H, Patsch JR. Relationship of plasma cholesteryl ester transfer protein to HDL cholesterol. Studies in normotriglyceridemia and moderate hypertriglyceridemia. Arterioscler Thromb Vasc Biol 1996; 16: 1430-6.
  • 40. Talukdar S, Oh DY, Bandyopadhyay G, Li D, Xu J, McNelis J, Lu M, Li P, Yan Q, Zhu Y, Ofrecio J, Lin M, Brenner MB, Olefsky JM. Neutrophils mediate insülin resistance in mice fed a high-fat diet through secreted elastase. Nat Med 2012; 18: 1407-12.

İnsülin direncinin plazma aterojenik indeks ve beyaz küre sayısı ile ilişkisinin değerlendirilmesi: Bir veri madenciliği çalışması

Year 2017, Volume: 39 Issue: 2, 479 - 486, 16.05.2017
https://doi.org/10.7197/223.v39i29491.316368

Abstract

Amaç: Hiperglisemik
öglisemik klemp testi insülin direncinin (İD) değerlendirilmesinde altın
standart olarak kabul edilmektedir. Bununla birlikte bu testin geniş gruplarda
uygulanması zor ve pratik değildir. Bu nedenle klinisyenler İD’nin
değerlendirilmesinde hesaplamalı parametrelere ihtiyaç duymaktadır. Bu
çalışmada insulin direncinin değerlendirilebilmesinde plazma aterojenik indeks
(PAİ) ve beyaz küre (WBC) değerinin kullanılıp kullanılamayacağı tespit
edilmeye çalışılmıştır.

Yöntem: Bu
amaçla Mart 2015- 2016 yılları arasında Cumhuriyet Üniversitesi Sağlık
Hizmetleri Araştırma ve Uygulama Hastanesi’ne  başvuran 138.934 kişinin
bilgileri incelendi ve 474 kişi çalışmaya dahil edildi. Çalışma populasyonuna
ait yaş, cinsiyet, WBC sayısı, açlık glukoz, trigliserid, total kolesterol,
yüksek dansiteli lipoprotein kolesterol ve insulin düzeyi bilgileri hastane bilgi
işlem sisteminden alındı.

Bulgular: İD’nin
varlığının gösterilmesinde PAİ için elde edilen eğri altında kalan alan (AUC)
değerleri homeostatic model assessment-insuline resistance (HOMA-IR) ve
quantitative insulin sensitivity check index (QUICKI) için sırasıyla 0.670 ve
0.690 olarak tespit edildi. Bu değerler WBC için sırasıyla 0.649 ve 0.652
olarak bulundu. Ayrıca HOMA-IR değeri baz alındığında PAİ ve WBC’nin negatif prediktif değerinin pozitif prediktif
değerinden daha yüksek olduğu görüldü.







Sonuç:
İnsulin direncinin tespitinde WBC ve AIP’in tek başına kullanılabilecek
güvenilir bir belirteç olmadığı ancak bu parametrelerin HOMA-IR ve QUICKI ile
birlikte insulin direncinin dışlanmasına katkı sağlayabileceği düşünülmektedir.  

References

  • 1. Steinberger J, Daniels SR; American Heart Association Atherosclerosis, Hypertension, and Obesity in the Young Committee (Council on Cardiovascular Disease in the Young); American Heart Association Diabetes Committee (Council on Nutrition, Physical Activity, and Metabolism). Obesity, insulin resistance, diabetes, and cardiovascular risk in children: an American Heart Association scientific statement from the Atherosclerosis, Hypertension, and Obesity in the Young Committee (Council on Cardiovascular Disease in the Young) and the Diabetes Committee (Council on Nutrition, Physical Activity, and Metabolism). Circulation 2003; 18: 1448-53.
  • 2. Tam CS, Xie W, Johnson WD, Cefalu WT, Redman LM, Ravussin E. Defining insulin resistance from hyperinsulinemic-euglycemic clamps. Diabetes Care 2012; 35: 1605-10.
  • 3. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000; 85: 2402-10.
  • 4. Miller WG, Thienpont LM, Van Uytfanghe K, Clark PM, Lindstedt P, Nilsson G, Steffes MW; Insulin Standardization Work Group. Toward standardization of insulin immunoassays. Clin Chem 2009; 55: 1011-8.
  • 5. Vozarova B, Weyer C, Lindsay RS, Pratley RE, Bogardus C, Tataranni PA. High white blood cell count is associated with a worsening of insulin sensitivity and predicts the development of type 2 diabetes. Diabetes 2002; 51: 455-61.
  • 6. Nakanishi N, Yoshida H, Matsuo Y, Suzuki K, Tatara K. White blood-cell count and the risk of impaired fasting glucose or Type II diabetes in middle-aged Japanese men. Diabetologia 2002; 45: 42-8.
  • 7. Yamamoto E, Sugiyama S, Hirata Y, Tokitsu T, Tabata N, Fujisue K, Sugamura K, Sakamoto K, Tsujita K, Matsumura T, Kaikita K, Hokimoto S. Prognostic significance of circulating leukocyte subtype counts in patients with coronary artery disease. Atherosclerosis. 2016; 255: 210-6.
  • 8. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO, Criqui M, Fadl YY, Fortmann SP, Hong Y, Myers GL, Rifai N, Smith SC Jr, Taubert K, Tracy RP, Vinicor F. Centers for Disease Control and Prevention; American Heart Association. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: A statement for health care professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003; 28: 499-511.
  • 9. Chen LK, Lin MH, Chen ZJ, Hwang SJ, Chiou ST. Association of insulin resistance and hematologic parameters: Study of a middle-aged and elderly Chinese population in Taiwan. J Chin Med Assoc 2006; 69: 248-53.
  • 10. Lewis GF, Steiner G. Hypertriglyceridemia and its metabolic consequences as a risk factor for atherosclerotic cardiovascular disease in non-insulin-dependent diabetes mellitus. Diabetes Metab Rev 1996; 12: 37-56.
  • 11. Brinck JW, Thomas A, Lauer E, Jornayvaz FR, Brulhart-Meynet MC, Prost JC, Pataky Z, Löfgren P, Hoffstedt J, Eriksson M, Pramfalk C, Morel S, Kwak BR, van Eck M, James RW, Frias MA. Diabetes Mellitus Is Associated With Reduced High-Density Lipoprotein Sphingosine-1-Phosphate Content and Impaired High-Density Lipoprotein Cardiac Cell Protection. Arterioscler Thromb Vasc Biol 2016; 36: 817-24.
  • 12. McLaughlin T, Reaven G, Abbasi F, Lamendola C, Saad M, Waters D, Simon J, Krauss RM: Is there a simple way to identify insulin-resistant individuals at increased risk of cardiovascular disease? Am J Cardiol 2005, 96: 399-404.
  • 13. McLaughlin T, Abbasi F, Cheal K, Chu J, Lamendola C, Reaven G. Use of metabolic markers to identify overweight individuals who are insulin resistant. Ann Intern Med 2003; 139: 802-9.
  • 14. Kim-Dorner SJ, Deuster PA, Zeno SA, Remaley AT, Poth M: Should triglycerides and the triglycerides to high-density lipoprotein cholesterol ratio be used as surrogates for insulin resistance? Metabolism 2010; 59: 299-304.
  • 15. Mostafa SA, Davies MJ, Morris DH, Yates T, Srinivasan BT, Webb D, Brady E, Khunti K. The association of the triglyceride-to-HDL cholesterol ratio with insulin resistance in White European and South Asian men and women. PLoS One 2012; 7: e50931.
  • 16. Deng QW, Wang H, Sun CZ, Xing FL, Zhang HQ, Zuo L, Gu ZT, Yan FL. Triglyceride to high-density lipoprotein cholesterol ratio predicts worse outcomes after acute ischaemic stroke. Eur J Neurol 2017; 24: 283-91.
  • 17. Dobiasova M. Atherogenic index of plasma [log(triglycerides/HDL-cholesterol)]: theoretical and practical implications. Clin Chem 2004; 50: 1113-5.
  • 18. Yamada C, Mitsuhashi T, Hiratsuka N, Inabe F, Araida N, Takahashi E. Optimal reference interval for homeostasis model assessment of insulin resistance in a Japanese population. J Diabetes Investig 2011; 2: 373-7
  • 19. Salgado AL, CarvalhoLd, Oliveira AC, Santos VN, Vieira JG, Parise ER. Insulin resistance index (HOMA-IR) in the differentiation of patients with non-alcoholic fatty liver disease and healthy individuals. Arq Gastroenterol 2010; 47: 165-9.
  • 20. McAuley KA, Williams SM, Mann JI, Walker RJ, Ledwis-Barned NJ, Temple LA, Duncan AS. Diagnosing insulin resistance in the general population. Diabetes Care 2001; 24: 460-4.
  • 21. Jellinger PS, Mehta AE, Handelsman Y, Shepherd MD. American association of clinical endocrinologist’s guidelines for management of dyslipidemia and prevention of atherosclerosis. Endocrine Practice 2012; 18(sup 1): 3-78.
  • 22. Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF, Turner RC. Homeostasis model assessment: insulin resistance and β-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412-9.
  • 23. Katz A, Nambi SS, Mather K, Baron AD, Follmann DA, Sullivan G, Quon MJ. Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans. J Clin Endocrinol Metab 2000; 85: 2402-10.
  • 24. Kimm H, Lee SW, Lee HS, Shim KW, Cho CY, Yun JE, Jee SH. Associations between lipid measures and metabolic syndrome, insulin resistance and adiponectin. Usefulness of lipid ratios in Korean men and women. Circ J 2010; 74: 931-7.
  • 25. Kannel WB, Vasan RS, Keyes MJ, Sullivan LM, Robins SJ. Usefulness of the triglyceride-high-density lipoprotein versus the cholesterol-high-density lipoprotein ratio for predicting insulin resistance and cardiometabolic risk (from the Framingham Offspring Cohort). Am J Cardiol 2008; 101: 497-501.
  • 26. Piedrola G, Novo E, Escobar F, Garcia-Robles R. White blood cell count and insulin resistance in patients with coronary artery disease. Ann Endocrinol (Paris) 2001; 62: 7-10.
  • 27. Twig G, Afek A, Shamiss A, Derazne E, Tzur D, Gordon B, Tirosh A. White blood cells count and incidence of type 2 diabetes in young men. Diabetes Care 2013; 36: 276-82.
  • 28. Chao TT, Hsieh CH, Lin JD, Wu CZ, Hsu CH, Pei D, Chen YL, Liang YJ, Chang JB. Use of white blood cell counts to predict metabolic syndrome in the elderly: a 4 year longitudinal study. Aging Male 2014; 17: 230-7.
  • 29. Oda E, Kawai R. Comparison between high-sensitivity C-reactive protein (hs-CRP) and white blood cell count (WBC) as an inflammatory component of metabolic syndrome in Japanese. Intern Med 2010; 49: 117-24.
  • 30. Reaven GM. Banting lecture 1988. Role of insulin resistance in human disease. Diabetes 1988; 37: 1595-607.
  • 31. Lamarche B, Lewis GF. Atherosclerosis prevention for the next decade: risk assessment beyond low density lipoprotein cholesterol. Can J Cardiol 1998; 14: 841-51.
  • 32. Ginsberg HN. Lipoprotein physiology in nondiabetic and diabetic states. Relationship to atherogenesis. Diabetes Care 1991; 14: 839-55.
  • 33. Taskinen MR. Diabetic dyslipidaemia: from basic research to clinical practice. Diabetologia 2003; 46: 733-49.
  • 34. Howard BV. Lipoprotein metabolism in diabetes mellitus. J Lipid Res 1987; 28: 613-28
  • 35. Temelkova-Kurktschiev T, Hanefeld M. The lipid triad in type 2 diabetes—prevalence and relevance of hypertriglyceridaemia/low high-density lipoprotein syndrome in type 2 diabetes. Exp Clin Endocrinol Diabetes 2004; 112: 75-9.
  • 36. Karhapaa P, Voutilainen E, Kovanen PT, Laakso M. Insulin resistance in familial and nonfamilial hypercholesterolemia. Arterioscler Thromb 1993; 13: 41-7.
  • 37. Rashid, S, Uffelman, K, Lewis, GF. The mechanism of HDL lowering in hypertriglyceridemic, insulin resistant states. J Diabetes Complications 2002; 16: 24-28.
  • 38. Mann CJ, Yen FT, Grant AM, et al. Mechanism of plasma cholesteryl ester transfer in hypertriglyceridemia. J Clin Invest 1991; 88: 2059-66.
  • 39. Föger B, Ritsch A, Doblinger A, Wessels H, Patsch JR. Relationship of plasma cholesteryl ester transfer protein to HDL cholesterol. Studies in normotriglyceridemia and moderate hypertriglyceridemia. Arterioscler Thromb Vasc Biol 1996; 16: 1430-6.
  • 40. Talukdar S, Oh DY, Bandyopadhyay G, Li D, Xu J, McNelis J, Lu M, Li P, Yan Q, Zhu Y, Ofrecio J, Lin M, Brenner MB, Olefsky JM. Neutrophils mediate insülin resistance in mice fed a high-fat diet through secreted elastase. Nat Med 2012; 18: 1407-12.
There are 40 citations in total.

Details

Subjects Health Care Administration
Journal Section Basic Science Research Articles
Authors

Halef Okan Dogan

Gülhan Duman

Publication Date May 16, 2017
Acceptance Date April 28, 2017
Published in Issue Year 2017Volume: 39 Issue: 2

Cite

AMA Dogan HO, Duman G. Assessment of the relationship between insulin resistance, atherogenic index of plasma and white blood cell count: A data mining study. CMJ. May 2017;39(2):479-486. doi:10.7197/223.v39i29491.316368