Correlation between the Atherogenic Index of Plasma and Progression of Non-target Lesion Vascular Disease Following Percutaneous Coronary Intervention using Drug-eluting Stents


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Abstract

Objective:To examine the correlation between Atherogenic Index of Plasma (AIP) levels and the progression of non-target lesion vascular disease following the deployment of drug-eluting stents (DES).

Methods:We retrospectively enrolled patients who had undergone successful treatment for CAD with DES and subsequently underwent a coronary angiography follow-up at the Cardiology Department of Tianjin Third Central Hospital from January 2017 to July 2022. The annual change in Gensini Score (GS) was calculated according to two angiographic evaluations in order to assess the progression of non-target lesion vascular disease; a change greater than 1 indicated progression, while a change of 1 or less indicated stability. AIP was calculated according to serum lipid parameters. Multivariate Logistic regression model was used to evaluate the relationship between AIP level and progression of non-target coronary artery lesions. The ROC curve analysis was performed to evaluate the diagnostic value of AIP for coronary artery non-target lesion vascular disease progression.

Results:Out of the 344 patients who were monitored over a median duration of 1.2 years, 113 exhibited progression of non-target lesion vascular disease. Initially, baseline AIP levels were notably higher in the progression group compared to the non-progression group (0.30 [0.14, 0.43] vs. 0.11 [-0.06, 0.31]), and this difference remained significant during the follow-up period (0.19 [0.06, 0.34] vs. 0.11 [-0.06, 0.22]). Multivariate logistic regression revealed that AIP is an independent predictor for the progression of non-target lesion vascular disease following DES treatment. Individuals in the highest tertile of AIP faced a considerably elevated risk compared to those in the lowest tertile (OR = 4.88, 95% CI: 2.12-11.21, p < 0.001). Moreover, utilizing receiver operating characteristic curve analysis, a 0.15 AIP level cut-off was determined for diagnosing disease progression, with a sensitivity of 73.5% and specificity of 56.7%, and an area under the curve of 0.672 (95% CI: 0.613-0.731, p < 0.01).

Conclusion:AIP significantly correlates with the progression of non-target lesion vascular disease among patients with coronary artery disease who have undergone DES treatment, establishing itself as an independent risk factor in addition to conventional predictors.

About the authors

Tian-Hua Hou

Department of Heart Center, The Third Central Clinical College of Tianjin Medical University

Email: info@benthamscience.net

Fei Wang

Department of Heart Center, The Third Central Clinical College of Tianjin Medical University

Email: info@benthamscience.net

Cui-Jun Hao

Department of Heart Center, The Third Central Clinical College of Tianjin Medical University

Email: info@benthamscience.net

Chong Zhang

Department of Heart Center, The Third Central Clinical College of Tianjin Medical University

Email: info@benthamscience.net

Meng Ning

Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Department of Heart Center, The Third Central Hospital of Tianjin

Email: info@benthamscience.net

Yi Chen

Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Department of Heart Center,, The Third Central Hospital of Tianjin

Email: info@benthamscience.net

Kun Wang

Department of Cardiology, Chengde Central Hospital,, Second Clinical College of Chengde Medical University

Email: info@benthamscience.net

Ying-Wu Liu

Department of Heart Center, The Third Central Clinical College of Tianjin Medical University

Author for correspondence.
Email: info@benthamscience.net

References

  1. Visseren FLJ, Mach F, Smulders YM, et al. 2021 ESC Guidelines on cardiovascular disease prevention in clinical practice. Eur Heart J 2021; 42(34): 3227-337. doi: 10.1093/eurheartj/ehab484 PMID: 34458905
  2. Neumann FJ, Sousa-Uva M, Ahlsson A, et al. 2018 ESC/EACTS Guidelines on myocardial revascularization. Eur Heart J 2019; 40(2): 87-165. doi: 10.1093/eurheartj/ehy394 PMID: 30165437
  3. Coughlan JJ, Aytekin A, Xhepa E, et al. Target and non-target vessel related events at 10 years post percutaneous coronary intervention. Clin Res Cardiol 2022; 111(7): 787-94. doi: 10.1007/s00392-022-01986-4 PMID: 35147767
  4. Park MW, Seung KB, Kim PJ, et al. Long-term percutaneous coronary intervention rates and associated independent predictors for progression of nonintervened nonculprit coronary lesions. Am J Cardiol 2009; 104(5): 648-52. doi: 10.1016/j.amjcard.2009.04.052 PMID: 19699339
  5. Mach F, Baigent C, Catapano AL, et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: Lipid modification to reduce cardiovascular risk. Eur Heart J 2020; 41(1): 111-88. doi: 10.1093/eurheartj/ehz455 PMID: 31504418
  6. Averna M, Stroes E, Ogura M, et al. How to assess and manage cardiovascular risk associated with lipid alterations beyond LDL. Atheroscler Suppl 2017; 26: 16-24. doi: 10.1016/S1567-5688(17)30021-1 PMID: 28434480
  7. Leatherman S, Ferguson R, Hau C, et al. Increased residual cardiovascular risk in U.S. veterans with moderately-elevated baseline triglycerides and well-controlled LDL-C levels on statins. Front Cardiovasc Med 2022; 9: 982815. doi: 10.3389/fcvm.2022.982815 PMID: 36407462
  8. Nichols GA, Philip S, Reynolds K, Granowitz CB, Fazio S. Increased residual cardiovascular risk in patients with diabetes and high versus normal triglycerides despite statin-controlled LDL cholesterol. Diabetes Obes Metab 2019; 21(2): 366-71. doi: 10.1111/dom.13537 PMID: 30225881
  9. Raposeiras-Roubin S, Rosselló X, Oliva B, et al. Triglycerides and residual atherosclerotic risk. J Am Coll Cardiol 2021; 77(24): 3031-41. doi: 10.1016/j.jacc.2021.04.059 PMID: 34140107
  10. Mascarenhas-Melo F, Palavra F, Marado D, et al. Emergent biomarkers of residual cardiovascular risk in patients with low HDL-c and/or high triglycerides and average LDL-c concentrations: Focus on HDL subpopulations, oxidized LDL, adiponectin, and uric acid. ScientificWorldJournal 2013; 2013(1): 387849. doi: 10.1155/2013/387849 PMID: 24319364
  11. Dobiás̆ová M, Frohlich J. The plasma parameter log (TG/HDL-C) as an atherogenic index: Correlation with lipoprotein particle size and esterification rate inapob-lipoprotein-depleted plasma (FERHDL). Clin Biochem 2001; 34(7): 583-8. doi: 10.1016/S0009-9120(01)00263-6 PMID: 11738396
  12. Dobiásová M, Frohlich J. The new atherogenic plasma index reflects the triglyceride and HDL-cholesterol ratio, the lipoprotein particle size and the cholesterol esterification rate: Changes during lipanor therapy. Vnitr Lek 2000; 46(3): 152-6. PMID: 11048517
  13. Nam JS, Kim MK, Park K, et al. The plasma atherogenic index is an independent predictor of arterial stiffness in healthy Koreans. Angiology 2022; 73(6): 514-9. doi: 10.1177/00033197211054242 PMID: 34693747
  14. Mangalesh S, Yadav P, Dudani S, Mahesh NK. Atherogenic index of plasma predicts coronary artery disease severity and major adverse cardiac events in absence of conventional risk factors. Coron Artery Dis 2022; 33(7): 523-30. doi: 10.1097/MCA.0000000000001166 PMID: 35811555
  15. Liu T, Liu J, Wu Z, Lv Y, Li W. Predictive value of the atherogenic index of plasma for chronic total occlusion before coronary angiography. Clin Cardiol 2021; 44(4): 518-25. doi: 10.1002/clc.23565 PMID: 33751593
  16. Abacıoğlu ÖÖ, Yıldırım A, Koyunsever NY, Karadeniz M, Kılıç S. Relationship between atherogenic index of plasma and stent thrombosis in patients with acute coronary syndrome. Anatol J Cardiol 2022; 26(2): 112-7. doi: 10.5152/AnatolJCardiol.2021.193 PMID: 35190359
  17. Zhu Y, Chen M, Liu K, et al. Atherogenic index of plasma and the risk of in-stent restenosis in patients with acute coronary syndrome beyond the traditional risk factors. J Atheroscler Thromb 2022; 29(8): 1226-35. doi: 10.5551/jat.63136 PMID: 34497172
  18. Williams B, Mancia G, Spiering W, et al. 2018 ESC/ESH Guidelines for the management of arterial hypertension. Eur Heart J 2018; 39(33): 3021-104. doi: 10.1093/eurheartj/ehy339 PMID: 30165516
  19. Blonde L, Umpierrez GE, Reddy SS, et al. American Association of Clinical Endocrinology Clinical Practice Guideline: Developing a diabetes mellitus comprehensive care plan-2022 update. Endocr Pract 2022; 28(10): 923-1049. doi: 10.1016/j.eprac.2022.08.002 PMID: 35963508
  20. Mortensen MB, Dzaye O, Steffensen FH, et al. Impact of plaque burden versus stenosis on ischemic events in patients with coronary atherosclerosis. J Am Coll Cardiol 2020; 76(24): 2803-13. doi: 10.1016/j.jacc.2020.10.021 PMID: 33303068
  21. Rampidis GP, Benetos G, Benz DC, Giannopoulos AA, Buechel RR. A guide for Gensini Score calculation. Atherosclerosis 2019; 287: 181-3. doi: 10.1016/j.atherosclerosis.2019.05.012 PMID: 31104809
  22. Patel RS, Su S, Neeland IJ, et al. The chromosome 9p21 risk locus is associated with angiographic severity and progression of coronary artery disease. Eur Heart J 2010; 31(24): 3017-23. doi: 10.1093/eurheartj/ehq272 PMID: 20729229
  23. Yin ZX, Zhou YJ, Liu XL, Han HY, Yang SW. Clinical predictors for progression of nonintervened nonculprit coronary lesions despite low-density lipoprotein cholesterol less than 1.8 mmol/l after successful stent implantation. Coron Artery Dis 2011; 22(2): 49-54. doi: 10.1097/MCA.0b013e3283423607 PMID: 21150778
  24. Zhang X, Zhang X, Li X, Feng J, Chen X. Association of metabolic syndrome with atherogenic index of plasma in an urban Chinese population: A 15-year prospective study. Nutr Metab Cardiovasc Dis 2019; 29(11): 1214-9. doi: 10.1016/j.numecd.2019.07.006 PMID: 31378627
  25. Nogay NH. Assessment of the correlation between the atherogenic index of plasma and cardiometabolic risk factors in children and adolescents: Might it be superior to the TG/HDL-C ratio? J Pediatr Endocrinol Metab 2017; 30(9): 947-55. doi: 10.1515/jpem-2016-0479 PMID: 28787273
  26. Gómez-Pérez S, Ovando-Gómez V, Hernández-Contreras AC, et al. Atherogenic indices in pediatric population in South-Southeast region of Mexico. J Trop Pediatr 2022; 68(6): fmac099. doi: 10.1093/tropej/fmac099 PMID: 36375036
  27. Nam JS, Kim MK, Nam JY, et al. Association between atherogenic index of plasma and coronary artery calcification progression in Korean adults. Lipids Health Dis 2020; 19(1): 157. doi: 10.1186/s12944-020-01317-4 PMID: 32615982
  28. Wu J, Zhou Q, Wei Z, Wei J, Cui M. Atherogenic index of plasma and coronary artery disease in the adult population: A meta-analysis. Front Cardiovasc Med 2021; 8: 817441. doi: 10.3389/fcvm.2021.817441 PMID: 34977202
  29. Wang L, Chen F, Xiaoqi C, Yujun C, Zijie L. Atherogenic index of plasma is an independent risk factor for coronary artery disease and a higher SYNTAX score. Angiology 2021; 72(2): 181-6. doi: 10.1177/0003319720949804 PMID: 32815391
  30. Li Y, Feng Y, Li S, et al. The atherogenic index of plasma (AIP) is a predictor for the severity of coronary artery disease. Front Cardiovasc Med 2023; 10: 1140215. doi: 10.3389/fcvm.2023.1140215 PMID: 37441702
  31. Balci MM, Balci KG, Ocak K, et al. Predictive value of resting fractional flow reserve and atherogenic index of plasma for evaluation of physiologically significant coronary artery lesions. Angiology 2023; 74(3): 282-7. doi: 10.1177/00033197221098280 PMID: 35500241
  32. Kim SH, Cho YK, Kim YJ, et al. Association of the atherogenic index of plasma with cardiovascular risk beyond the traditional risk factors: A nationwide population-based cohort study. Cardiovasc Diabetol 2022; 21(1): 81. doi: 10.1186/s12933-022-01522-8 PMID: 35599307
  33. Oleksiak A, Kępka C, Rucińska K, Marcinkiewicz K, Demkow M, Kruk M. High-density lipoprotein cholesterol, triglycerides, and characteristics of coronary atherosclerosis in patients with significant coronary artery disease newly diagnosed by computed tomography coronary angiography. Kardiol Pol 2023; 81(3): 273-80. doi: 10.33963/KP.a2022.0279 PMID: 36475513
  34. Takata K, Kataoka Y, Honda S, et al. The association of triglyceride/high-density lipoprotein cholesterol ratio with lipidic plaque features in diabetic patients receiving a statin: Frequency domain optical coherence tomography analysis. Heart Lung Circ 2016; 25 (Suppl. 2): S91. doi: 10.1016/j.hlc.2016.06.214
  35. Safaei A, Khosravi A, Sadeghi M, et al. Atherogenic index of plasma: A valuable novel index to distinguish patients with unstable atherogenic plaques. J Res Med Sci 2022; 27(1): 45. doi: 10.4103/jrms.jrms_590_21 PMID: 35968214
  36. Gu H, Gao Y, Wang H, et al. Sex differences in coronary atherosclerosis progression and major adverse cardiac events in patients with suspected coronary artery disease. J Cardiovasc Comput Tomogr 2017; 11(5): 367-72. doi: 10.1016/j.jcct.2017.07.002 PMID: 28754436
  37. Shui X, Chen Z, Wen Z, et al. Association of atherogenic index of plasma with angiographic progression in patients with suspected coronary artery disease. Angiology 2022; 73(10): 927-35. doi: 10.1177/00033197221080911 PMID: 35229661
  38. Won KB, Han D, Lee JH, et al. Atherogenic index of plasma and coronary artery calcification progression beyond traditional risk factors according to baseline coronary artery calcium score. Sci Rep 2020; 10(1): 21324. doi: 10.1038/s41598-020-78350-x PMID: 33288827
  39. Liu H, Liu K, Pei L, et al. Atherogenic index of plasma predicts outcomes in acute ischemic stroke. Front Neurol 2021; 12: 741754. doi: 10.3389/fneur.2021.741754 PMID: 34707558
  40. Qin Z, Zhou K, Li Y, et al. The atherogenic index of plasma plays an important role in predicting the prognosis of type 2 diabetic subjects undergoing percutaneous coronary intervention: Results from an observational cohort study in China. Cardiovasc Diabetol 2020; 19(1): 23. doi: 10.1186/s12933-020-0989-8 PMID: 32085772
  41. Dobiásová M. AIP-aterogenní index plazmy jako významný prediktor kardiovaskulárního rizika: Od výzkumu do praxe. Vnitr Lek 2006; 52(1): 64-71. PMID: 16526201

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