Endocrinol Metab.  2018 Mar;33(1):88-96. 10.3803/EnM.2018.33.1.88.

High Brachial Ankle Pulse Wave Velocity as a Marker for Predicting Coronary Artery Stenosis in Patients with Type 2 Diabetes

Affiliations
  • 1Department of Internal Medicine, Pusan National University Hospital and Biomedical Research Institute, Pusan National University School of Medicine, Busan, Korea.
  • 2Department of Internal Medicine, Inje University Busan Paik Hospital, Inje University College of Medicine, Busan, Korea.
  • 3Department of Internal Medicine, Busan St. Mary's Hospital, Busan, Korea. koje94@hanmail.net
  • 4Department of Radiology, Busan St. Mary's Hospital, Busan, Korea.

Abstract

BACKGROUND
We evaluated the ability of brachial ankle pulse wave velocity (baPWV) to predict coronary artery stenosis (CAS) in patients with type 2 diabetes, and compared the predictive power of baPWV to that of well-known cardiovascular disease (CVD) risk calculators.
METHODS
The study group included 83 consecutive patients over 30 years old with type 2 diabetes who complained of vague chest discomfort. An automatic pulse waveform analyzer was used to measure baPWV. CAS was measured using multi-slice computed tomographic (MSCT) angiography.
RESULTS
Age, maximal baPWV, duration of diabetes, current smoking, the UK Prospective Diabetes Study (UKPDS) Risk Engine score, American College of Cardiology/American Heart Association (ACC/AHA) risk estimator score, the Framingham risk calculator score, and coronary artery calcium score were greater in patients with CAS than in those without CAS. An area under the curve (AUC) indicative of a predictive value for CAS (≥20%) was found for several parameters. The AUC of maximal baPWV, the UKPDS Risk Engine, the ACC/AHA ASCVD risk estimator, and the Framingham risk calculator were 0.672 (95% confidence interval [CI], 0.554 to 0.785; P=0.010), 0.777 (95% CI, 0.675 to 0.878; P < 0.001), 0.763 (95% CI, 0.660 to 0.866; P < 0.001), and 0.736 (95% CI, 0.629 to 0.843; P < 0.001), respectively. The optimal cutoff value of baPWV for the detection of CAS was 1,650 cm/sec (sensitivity, 68.9%; specificity, 63.2%).
CONCLUSION
Maximal baPWV was closely related with CAS detected by MSCT coronary angiography in patients with type 2 diabetes. baPWV has the potential to be a useful, noninvasive screening tool for the prediction of occult CAS in patients with type 2 diabetes.

Keyword

Coronary stenosis; Diabetes mellitus; Pulse wave analysis; Vascular stiffness

MeSH Terms

Angiography
Ankle*
Area Under Curve
Calcium
Cardiovascular Diseases
Coronary Angiography
Coronary Stenosis*
Coronary Vessels*
Diabetes Mellitus
Heart
Humans
Mass Screening
Prospective Studies
Pulse Wave Analysis*
Sensitivity and Specificity
Smoke
Smoking
Thorax
Vascular Stiffness
Calcium
Smoke

Figure

  • Fig. 1 Receiver operating characteristic curve to determine the cutoff value of brachial ankle pulse wave velocity for coronary artery stenosis. The cutoff point of 1,650 cm/sec showed a sensitivity of 68.9%, a specificity of 63%, and an area under the curve of 0.672.

  • Fig. 2 Pairwise comparison of the receiver operating characteristic curves of maximal brachial ankle pulse wave velocity (baPWV) and 3 cardiovascular disease (CVD) risk estimators, assessing their predictive value for coronary artery stenosis (≥20%). No significant differences were found between maximal baPWV and the three CVD risk estimators (all P values >0.05). UKPDS, United Kingdom Prospective Diabetes Study; ACC/AHA, American College of Cardiology/American Heart Association.


Reference

1. Yoo WS, Kim HJ, Kim D, Lee MY, Chung HK. Early detection of asymptomatic coronary artery disease in patients with type 2 diabetes mellitus. Korean J Intern Med. 2009; 24:183–189.
Article
2. Pearson TA. New tools for coronary risk assessment: what are their advantages and limitations? Circulation. 2002; 105:886–892.
3. Wood D. Joint European Societies Task Force. Established and emerging cardiovascular risk factors. Am Heart J. 2001; 141:2 Suppl. S49–S57.
Article
4. van Popele NM, Grobbee DE, Bots ML, Asmar R, Topouchian J, Reneman RS, et al. Association between arterial stiffness and atherosclerosis: the Rotterdam Study. Stroke. 2001; 32:454–460.
5. Laurent S, Boutouyrie P, Asmar R, Gautier I, Laloux B, Guize L, et al. Aortic stiffness is an independent predictor of all-cause and cardiovascular mortality in hypertensive patients. Hypertension. 2001; 37:1236–1241.
Article
6. Cruickshank K, Riste L, Anderson SG, Wright JS, Dunn G, Gosling RG. Aortic pulse-wave velocity and its relationship to mortality in diabetes and glucose intolerance: an integrated index of vascular function? Circulation. 2002; 106:2085–2090.
7. Yamashina A, Tomiyama H, Takeda K, Tsuda H, Arai T, Hirose K, et al. Validity, reproducibility, and clinical significance of noninvasive brachial-ankle pulse wave velocity measurement. Hypertens Res. 2002; 25:359–364.
Article
8. Suzuki E, Kashiwagi A, Nishio Y, Egawa K, Shimizu S, Maegawa H, et al. Increased arterial wall stiffness limits flow volume in the lower extremities in type 2 diabetic patients. Diabetes Care. 2001; 24:2107–2114.
Article
9. Tomiyama H, Yamashina A, Arai T, Hirose K, Koji Y, Chikamori T, et al. Influences of age and gender on results of noninvasive brachial-ankle pulse wave velocity measurement: a survey of 12517 subjects. Atherosclerosis. 2003; 166:303–309.
10. Ha BK, Kim BG, Kim DH, Lee SI, Jung SM, Park JY, et al. Relationships between brachial-ankle pulse wave velocity and peripheral neuropathy in type 2 diabetes. Diabetes Metab J. 2012; 36:443–451.
Article
11. Hamon M, Biondi-Zoccai GG, Malagutti P, Agostoni P, Morello R, Valgimigli M, et al. Diagnostic performance of multislice spiral computed tomography of coronary arteries as compared with conventional invasive coronary angiography: a meta-analysis. J Am Coll Cardiol. 2006; 48:1896–1910.
12. Hoffmann U, Moselewski F, Nieman K, Jang IK, Ferencik M, Rahman AM, et al. Noninvasive assessment of plaque morphology and composition in culprit and stable lesions in acute coronary syndrome and stable lesions in stable angina by multidetector computed tomography. J Am Coll Cardiol. 2006; 47:1655–1662.
Article
13. Nam HJ, Jung IH, Kim J, Kim JH, Suh J, Kim HS, et al. Association between brachial-ankle pulse wave velocity and occult coronary artery disease detected by multi-detector computed tomography. Int J Cardiol. 2012; 157:227–232.
Article
14. Kim HL, Jin KN, Seo JB, Choi YH, Chung WY, Kim SH, et al. The association of brachial-ankle pulse wave velocity with coronary artery disease evaluated by coronary computed tomography angiography. PLoS One. 2015; 10:e0123164.
Article
15. Asmar R, Benetos A, Topouchian J, Laurent P, Pannier B, Brisac AM, et al. Assessment of arterial distensibility by automatic pulse wave velocity measurement: validation and clinical application studies. Hypertension. 1995; 26:485–490.
16. Lee SW, Yun KW, Yu YS, Lim HK, Bae YP, Lee BD, et al. Determinants of the brachial-ankle Pulse Wave Velocity (baPWV) in patients with type 2 diabetes mellitus. J Korean Endocr Soc. 2008; 23:253–259.
Article
17. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990; 15:827–832.
Article
18. Blacher J, Asmar R, Djane S, London GM, Safar ME. Aortic pulse wave velocity as a marker of cardiovascular risk in hypertensive patients. Hypertension. 1999; 33:1111–1117.
Article
19. Yamashina A, Tomiyama H, Arai T, Hirose K, Koji Y, Hirayama Y, et al. Brachial-ankle pulse wave velocity as a marker of atherosclerotic vascular damage and cardiovascular risk. Hypertens Res. 2003; 26:615–622.
Article
20. Nakamura U, Iwase M, Nohara S, Kanai H, Ichikawa K, Iida M. Usefulness of brachial-ankle pulse wave velocity measurement: correlation with abdominal aortic calcification. Hypertens Res. 2003; 26:163–167.
Article
21. Choi KM, Lee KW, Seo JA, Oh JH, Kim SG, Kim NH, et al. Relationship between brachial-ankle pulse wave velocity and cardiovascular risk factors of the metabolic syndrome. Diabetes Res Clin Pract. 2004; 66:57–61.
Article
22. Imanishi R, Seto S, Toda G, Yoshida M, Ohtsuru A, Koide Y, et al. High brachial-ankle pulse wave velocity is an independent predictor of the presence of coronary artery disease in men. Hypertens Res. 2004; 27:71–78.
Article
23. Tsuchiya M, Suzuki E, Egawa K, Nishio Y, Maegawa H, Inoue S, et al. Stiffness and impaired blood flow in lower-leg arteries are associated with severity of coronary artery calcification among asymptomatic type 2 diabetic patients. Diabetes Care. 2004; 27:2409–2415.
Article
24. London GM, Guerin AP. Influence of arterial pulse and reflected waves on blood pressure and cardiac function. Am Heart J. 1999; 138:220–224.
Article
25. Benetos A, Safar M, Rudnichi A, Smulyan H, Richard JL, Ducimetieere P, et al. Pulse pressure: a predictor of long-term cardiovascular mortality in a French male population. Hypertension. 1997; 30:1410–1415.
26. Millar JA, Lever AF, Burke V. Pulse pressure as a risk factor for cardiovascular events in the MRC mild hypertension trial. J Hypertens. 1999; 17:1065–1072.
Article
27. Seo WW, Chang HJ, Cho I, Yoon YY, Suh JW, Kim KI, et al. The value of brachial-ankle pulse wave velocity as a predictor of coronary artery disease in high-risk patients. Korean Circ J. 2010; 40:224–229.
Article
28. Stevens RJ, Kothari V, Adler AI, Stratton IM. United Kingdom Prospective Diabetes Study (UKPDS) Group. The UKPDS risk engine: a model for the risk of coronary heart disease in type II diabetes (UKPDS 56). Clin Sci (Lond). 2001; 101:671–679.
Article
29. Goff DC Jr, Lloyd-Jones DM, Bennett G, Coady S, D'Agostino RB, Gibbons R, et al. 2013 ACC/AHA guideline on the assessment of cardiovascular risk: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation. 2014; 129:25 Suppl 2. S49–S73.
Article
30. D'Agostino RB Sr, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, et al. General cardiovascular risk profile for use in primary care: the Framingham Heart Study. Circulation. 2008; 117:743–753.
31. Ankle Brachial Index Collaboration. Fowkes FG, Murray GD, Butcher I, Heald CL, Lee RJ, et al. Ankle brachial index combined with Framingham risk score to predict cardiovascular events and mortality: a meta-analysis. JAMA. 2008; 300:197–208.
32. Fujihara K, Suzuki H, Sato A, Ishizu T, Kodama S, Heianza Y, et al. Comparison of the Framingham risk score, UK Prospective Diabetes Study (UKPDS) Risk Engine, Japanese Atherosclerosis Longitudinal Study-Existing Cohorts Combine (JALS-ECC) and maximum carotid intima-media thickness for predicting coronary artery stenosis in patients with asymptomatic type 2 diabetes. J Atheroscler Thromb. 2014; 21:799–815.
Article
33. Schuijf JD, Bax JJ, Shaw LJ, de Roos A, Lamb HJ, van der Wall EE, et al. Meta-analysis of comparative diagnostic performance of magnetic resonance imaging and multislice computed tomography for noninvasive coronary angiography. Am Heart J. 2006; 151:404–411.
Article
34. Management of stable angina pectoris. Recommendations of the Task Force of the European Society of Cardiology. Eur Heart J. 1997; 18:394–413.
35. Mollet NR, Cademartiri F, van Mieghem CA, Runza G, McFadden EP, Baks T, et al. High-resolution spiral computed tomography coronary angiography in patients referred for diagnostic conventional coronary angiography. Circulation. 2005; 112:2318–2323.
Article
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