Gender differences in the detection of carotid atherosclerosis: DUPLEX registry cross-sectional study results

Submitted: October 18, 2021
Accepted: January 22, 2022
Published: February 7, 2022
Abstract Views: 1129
PDF: 501
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Authors

The aim of this study was to assess the features of detecting carotid atherosclerosis depending on gender, age, the presence of arterial hypertension, other major diseases and conditions according to  The Duplex Registry Database. The registry sequentially included the results of duplex scanning of the carotid arteries (DSCA) of all patients who underwent it at the United Hospital with Outpatient Department in 2013 (n=2548). The incidence of carotid atherosclerosis (CAS) was higher in men than in women (58.6% (n=763) vs 45.5% (n=568), p<0.0000001). This was noted in all categories according to the gradation of stenosis, including in the category of the most severe lesion (>70%): 2.9% (n=32) vs 1.0% (n=13), p=0.003. The presence of CAD significantly increased the chances of detecting CAS in men (OR 4.47 vs 2.6, p<0.0000001). Signs more significant in their influence in women compared to men were the following: age (OR 5.3 [4.12; 6.71] p<0.0000001); arterial hypertension (OR 2.7 [2.12; 3.39] p<0.0000001) and cerebrovascular disease (OR 1.63 [1.13; 2.36] p=0.004). The OR of CAS detection for the “acute cerebrovascular accident” diagnosis in men and women differed 2 times (OR 1.2, p=0.4 vs 2.4, p=0.15). The “hypercholesterolemia” diagnosis when referred for DSCA did not show itself as a predictor of CAS detection in all study groups. Disorders of autonomic nervous system, hearing loss and screening examination showed a significant decrease in the probability of CAS detecting for the whole group (OR 0.14 [0.08;0.24] p<0.0000001; OR 0.16 [0.02;0.66] p=0.004 and OR 0.3 [0.25 0.37] p<0.0000001, respectively), so and separately for males and females. The present study revealed significant gender differences in the prevalence of carotid atherosclerosis and in the influence of various signs on an increase in the chances of its detection. The most significant signs were (OR men vs women): gender (1.3 vs 0.8), age (4.2 vs 5.3), arterial hypertension (1.8 vs 2.7), CAD (4.4 vs 2.6), cerebrovascular disease (1.26 vs 1.63).

Dimensions

Altmetric

PlumX Metrics

Downloads

Download data is not yet available.

Citations

Timmis A, Townsend N, Gale CP, et al. European Society of Cardiology: Cardiovascular Disease Statistics 2019. Eur Heart J 2020;41:12-85. DOI: https://doi.org/10.1093/eurheartj/ehaa062
Man JJ, Beckman JA, Jaffe IZ. Sex as a biological variable in atherosclerosis. Circ Res 2020;126:1297-319. DOI: https://doi.org/10.1161/CIRCRESAHA.120.315930
Kim H, Kim JY, Min PK, et al. Outcomes and associated factors of discrepant coronary and carotid atherosclerosis. Int Heart J 2020;61:1142-49. DOI: https://doi.org/10.1536/ihj.20-318
Lewington S, Whitlock G, Clarke R, et al. Blood cholesterol and vascular mortality by age, sex, and blood pressure: a meta-analysis of individual data from 61 prospective studies with 55,000 vascular deaths. Lancet 2007;370:1829-39. DOI: https://doi.org/10.1016/S0140-6736(07)61778-4
Phan HT, Gall S, Blizzard CL, et al. Sex differences in causes of death after stroke: Evidence from a national prospective registry. J Womens Health (Larchmt) 2021;30:314-23. DOI: https://doi.org/10.1089/jwh.2020.8391
Buon R, Guidolin B, Jaffre Aet al. Carotid ultrasound for assessment of nonobstructive carotid atherosclerosis in young adults with cryptogenic stroke. J Stroke Cerebrovasc Dis 2018;27:1212-6. DOI: https://doi.org/10.1016/j.jstrokecerebrovasdis.2017.11.043
Schulz UG, Rothwell PM. Sex differences in carotid bifurcation anatomy and the distribution of atherosclerotic plaque. Stroke 2001;32:1525-31. DOI: https://doi.org/10.1161/01.STR.32.7.1525
Tromba L, Tartaglia F, Blasi S, et al. Is carotid stenosis in women a gender-related condition? J Womens Health (Larchmt) 2016;25:348-54. DOI: https://doi.org/10.1089/jwh.2015.5300
López-Melgar B, Fernández-Friera L, Oliva B, et al. Subclinical atherosclerosis burden by 3D ultrasound in mid-life: The PESA study. J Am Coll Cardiol 2017;70:301-13. DOI: https://doi.org/10.1016/j.jacc.2017.05.033
Puz P, Urbanek T, Ziaja D, et al. Factors associated with the symptomatic status of carotid artery stenosis: identification in a cross-sectional study and development of a scoring system. Pol Arch Intern Med 2021;131:17-25. DOI: https://doi.org/10.20452/pamw.15676
Ershova AI, Meshkov AN, Deev AD, et al. [Atherosclerotic plaque in carotid arteries as a risk marker for cardiovascular events risk in middle aged population].[Article in Russian with English abstract]. Cardiovasc Ther Prev 2018;17:34-9. DOI: https://doi.org/10.15829/1728-8800-2018-4-34-39
Lewis TT, Van Dyke ME, Matthews KA, et al. Race/ethnicity, cumulative midlife loss, and carotid atherosclerosis in middle-aged women. Am J Epidemiol 2021;190:576-87. DOI: https://doi.org/10.1093/aje/kwaa213
European Carotid Surgery Trialists' Collaborative Group. Randomised trial of endarterectomy for recently symptomatic carotid stenosis: final results of the MRC European Carotid Surgery Trial (ECST). Lancet 1998;351:1379–87. DOI: https://doi.org/10.1016/S0140-6736(97)09292-1
Zwiebel WJ, Pellerito JS, ed. Introduction to vascular ultrasonography. 5th ed. Philadelphia: Elsevier Saunders; 2005.
Martin D, Austin H. An efficient program for computing conditional maximum likelihood estimates and exact confidence limits for a common odds ratio. Epidemiology 1991;2:359-62. DOI: https://doi.org/10.1097/00001648-199109000-00008
Martin WE, Bridgmon KD. Quantitative and statistical research methods: From hypothesis to results. Somerset: Wiley; 2012.
Ojima S, Kubozono T, Kawasoe S, et al. Gender differences in the risk factors associated with atherosclerosis by carotid intima-media thickness, plaque score, and pulse wave velocity. Heart Vessels 2021;36:934-44. DOI: https://doi.org/10.1007/s00380-021-01775-5
Li Y, Zhao D, Wang M, et al. Association of menopause with risk of carotid artery atherosclerosis. Maturitas 2021;143:171-7. DOI: https://doi.org/10.1016/j.maturitas.2020.10.007
Kaveshnikov VS, Trubacheva IA, Serebryakova VN. Factors associated with carotid plaque burden in the adult general population. Russian J Cardiol 2021;26:4379. DOI: https://doi.org/10.15829/1560-4071-2021-4379
Laclaustra M, Casasnovas JA, Fernández-Ortiz A, et al. Femoral and carotid subclinical atherosclerosis association with risk factors and coronary calcium: The AWHS study. J Am Coll Cardiol 2016;67:1263-74. DOI: https://doi.org/10.1016/j.jacc.2015.12.056
O'Rourke MF, Safar ME, Dzau V. The Cardiovascular Continuum extended: aging effects on the aorta and microvasculature. Vasc Med 2010;15:461-8. DOI: https://doi.org/10.1177/1358863X10382946
Geng Y, Liu Y, Chen Y, et al. Association of LDLc to HDLc ratio with carotid plaques in a community-based population with a high stroke risk: A cross-sectional study in China. Clin Biochem.2021;88:43-8. DOI: https://doi.org/10.1016/j.clinbiochem.2020.11.001
Woodard GA, Narla VV, Ye R, et al. Racial differences in the association between carotid plaque and aortic and coronary artery calcification among women transitioning through menopause. Menopause 2012;19:157-63. DOI: https://doi.org/10.1097/gme.0b013e318227304b
Picard F, Van Ganse E, Ducrocq G, et al. EvaluatioN of ApiXaban in strOke and systemic embolism prevention in patients with non-valvular atrial fibrillation in clinical practice setting in France, rationale and design of the NAXOS: SNIIRAM study. Clin Cardiol 2019;42:851-9. DOI: https://doi.org/10.1002/clc.23231
Timmer A, de Sordi D, Kappen S, et al. Validity of hospital ICD-10-GM codes to identify acute liver injury in Germany. Pharmacoepidemiol Drug Saf 2019;28:1344-52. DOI: https://doi.org/10.1002/pds.4855
Storesund A, Haugen AS, Hjortås M, et al. Accuracy of surgical complication rate estimation using ICD-10 codes. Br J Surg 2019;106:236-44. DOI: https://doi.org/10.1002/bjs.10985

How to Cite

Gaisenok, Oleg, and Oksana Drapkina. 2022. “Gender Differences in the Detection of Carotid Atherosclerosis: DUPLEX Registry Cross-Sectional Study Results”. Monaldi Archives for Chest Disease 92 (4). https://doi.org/10.4081/monaldi.2022.2128.