A prediction model for renal artery stenosis using carotid ultrasonography measurements in patients undergoing coronary angiography

BMC Nephrology

Seong-il Choi¹  Soon Gil Kim¹  Hwan-Cheol Park¹  Jeong-Hun Shin¹  Yonggu Lee¹ 

[1] Department of Cardiology, Hanyang University Guri Hospital, Guri City, Kyeungg-do, Republic of Korea

关键词: Prediction model;    Carotid intima-media thickness;    Carotid atherosclerotic plaque;    Coronary artery disease;    Renal artery stenosis;   

Others  :  1082702
DOI  :  10.1186/1471-2369-15-60

 received in 2013-01-16, accepted in 2014-04-07,  发布年份 2014

【 摘 要 】

Background

Carotid intima-media thickness (CIMT) and carotid atherosclerotic plaque (CAP) are well-known indicators of atherosclerosis. However, few studies have reported the value of CIMT and CAP for predicting renal artery stenosis (RAS). We investigated the predictive value of CIMT and CAP for RAS and propose a model for predicting significant RAS in patients undergoing coronary angiography (CAG).

Methods

Consecutive patients who underwent renal angiography at the time of CAG in a single center in 2011 were included. RAS ≥50% was considered significant. Multiple logistic regression analysis with step-down variable selection method was used to select the best model for predicting significant RAS and bootstrap resampling was used to validate the best model. A scoring system for predicting significant RAS was developed by adding the closest integers proportional to the coefficients of the regression formula.

Results

Significant RAS was observed in 60 of 641 patients (9.6%) who underwent CAG. Hypertension, diabetes, significant coronary artery disease (CAD) and chronic kidney disease (CKD) stage ≥3 were more prevalent in patients with significant RAS. Mean age, CIMT and number of anti-hypertensive medications (AHM) were higher and body mass index (BMI) and total cholesterol level were lower in patients with significant RAS. Multiple logistic regression analysis identified significant CAD (odds ratio (OR) 5.6), unilateral CAP (OR 2.6), bilateral CAP (OR 4.9), CKD stage ≥3 (OR 4.8), four or more AHM (OR 4.8), CIMT (OR 2.3), age ≥67 years (OR 2.3) and BMI <22 kg/m² (OR 2.4) as independent predictors of significant RAS. The scoring system for predicting significant RAS, which included these predictors, had a sensitivity of 83.3% and specificity of 81.6%. The predicted frequency of the scoring system agreed well with the observed frequency of significant RAS (coefficient of determination r² = 0.957).

Conclusions

CIMT and CAP are independent predictors of significant RAS. The proposed scoring system, which includes CIMT and CAP, may be useful for predicting significant RAS in patients undergoing CAG.

【 授权许可】

   
2014 Lee et al.; licensee BioMed Central Ltd.

【 图 表 】

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【 参考文献 】

• [1]Amighi J, Schlager O, Haumer M, Dick P, Mlekusch W, Loewe C, Bohmig G, Koppensteiner R, Minar E, Schillinger M: Renal artery stenosis predicts adverse cardiovascular and renal outcome in patients with peripheral artery disease. Eur J Clin Investig 2009, 39(9):784-792.
• [2]Conlon PJ, Little MA, Pieper K, Mark DB: Severity of renal vascular disease predicts mortality in patients undergoing coronary angiography. Kidney Int 2001, 60(4):1490-1497.
• [3]Ollivier R, Boulmier D, Veillard D, Leurent G, Mock S, Bedossa M, Le Breton H: Frequency and predictors of renal artery stenosis in patients with coronary artery disease. Cardiovasc Revasc Med 2009, 10(1):23-29.
• [4]Garovic VD, Textor SC: Renovascular hypertension and ischemic nephropathy. Circulation 2005, 112(9):1362-1374.
• [5]Przewlocki T, Kablak-Ziembicka A, Tracz W, Kozanecki A, Kopec G, Rubis P, Kostkiewicz M, Roslawiecka A, Rzeznik D, Stompor T: Renal artery stenosis in patients with coronary artery disease. Kardiol Pol 2008, 66(8):856-862. discussion 863–854
• [6]White CJ, Jaff MR, Haskal ZJ, Jones DJ, Olin JW, Rocha-Singh KJ, Rosenfield KA, Rundback JH, Linas SL: Indications for renal arteriography at the time of coronary arteriography: a science advisory from the American Heart Association Committee on Diagnostic and Interventional Cardiac Catheterization, Council on Clinical Cardiology, and the Councils on Cardiovascular Radiology and Intervention and on Kidney in Cardiovascular Disease. Circulation 2006, 114(17):1892-1895.
• [7]Lorenz MW, Markus HS, Bots ML, Rosvall M, Sitzer M: Prediction of clinical cardiovascular events with carotid intima-media thickness: a systematic review and meta-analysis. Circulation 2007, 115(4):459-467.
• [8]Prabhakaran S, Singh R, Zhou X, Ramas R, Sacco RL, Rundek T: Presence of calcified carotid plaque predicts vascular events: the Northern Manhattan Study. Atherosclerosis 2007, 195(1):e197-e201.
• [9]Cohen MG, Pascua JA, Garcia-Ben M, Rojas-Matas CA, Gabay JM, Berrocal DH, Tan WA, Stouffer GA, Montoya M, Fernandez AD, Halac ME, Grinfeld LR: A simple prediction rule for significant renal artery stenosis in patients undergoing cardiac catheterization. Am Heart J 2005, 150(6):1204-1211.
• [10]Przewlocki T, Kablak-Ziembicka A, Tracz W, Kopec G, Rubis P, Pasowicz M, Musialek P, Kostkiewicz M, Kozanecki A, Stompor T, Sulowicz W, Sokolowski A: Prevalence and prediction of renal artery stenosis in patients with coronary and supraaortic artery atherosclerotic disease. Nephrol Dial Transplant 2008, 23(2):580-585.
• [11]Carmelita M, Stefania R, Luca Z, Giovanni T, Marilena DS, Sergio M, Carmelo S, Davide C, Corrado T, Pietro C: Prevalence of renal artery stenosis in patients undergoing cardiac catheterization. Intern Emerg Med 2013, 8(5):401-408.
• [12]National Kidney Foundation Chronic Kidney Disease Work Group: K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002, 39(2 Suppl 1):S1-S266.
• [13]Vittinghoff E, McCulloch CE: Relaxing the rule of ten events per variable in logistic and Cox regression. Am J Epidemiol 2007, 165(6):710-718.
• [14]Harrell FE: Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer; 2001.
• [15]Efran B, Tibshirani R: Improvements on cross validation: the .632+ bootstrap method. J Am Stat Assoc 1997, 92:548-560.
• [16]Harding MB, Smith LR, Himmelstein SI, Harrison K, Phillips HR, Schwab SJ, Hermiller JB, Davidson CJ, Bashore TM: Renal artery stenosis: prevalence and associated risk factors in patients undergoing routine cardiac catheterization. J Am Soc Nephrol 1992, 2(11):1608-1616.
• [17]Ozkan U, Oguzkurt L, Tercan F, Nursal TZ: The prevalence and clinical predictors of incidental atherosclerotic renal artery stenosis. Eur J Radiol 2009, 69(3):550-554.
• [18]Kim TN, Park MS, Lim KI, Yang SJ, Yoo HJ, Kang HJ, Song W, Seo JA, Kim SG, Kim NH, Baik SH, Choi DS, Choi KM: Skeletal muscle mass to visceral fat area ratio is associated with metabolic syndrome and arterial stiffness: the Korean Sarcopenic Obesity Study (KSOS). Diabetes Res Clin Pract 2011, 93(2):285-291.
• [19]Bowden RG, Wilson RL: Malnutrition, inflammation, and lipids in a cohort of dialysis patients. Postgrad Med 2010, 122(3):196-202.
• [20]Den Ruijter HM, Peters SA, Anderson TJ, Britton AR, Dekker JM, Eijkemans MJ, Engstrom G, Evans GW, de Graaf J, Grobbee DE, Hedblad B, Hofman A, Holewijn S, Ikeda A, Kavousi M, Kitagawa K, Kitamura A, Koffijberg H, Lonn EM, Lorenz MW, Mathiesen EB, Nijpels G, Okazaki S, O'Leary DH, Polak JF, Price JF, Robertson C, Rembold CM, Rosvall M, Rundek T, et al.: Common carotid intima-media thickness measurements in cardiovascular risk prediction: a meta-analysis. JAMA 2012, 308(8):796-803.
• [21]Horita Y, Tadokoro M, Taura K, Mishima Y, Miyazaki M, Kohno S, Kawano Y: Relationship between carotid artery intima-media thickness and atherosclerotic renal artery stenosis in type 2 diabetes with hypertension. Kidney Blood Pres Res 2002, 25(4):255-259.
• [22]Dzielinska Z, Januszewicz A, Demkow M, Makowiecka-Ciesla M, Prejbisz A, Naruszewicz M, Nowicka G, Kadziela J, Zielinski T, Florczak E, Janas J, Januszewicz M, Ruzyllo W: Cardiovascular risk factors in hypertensive patients with coronary artery disease and coexisting renal artery stenosis. J Hypertens 2007, 25(3):663-670.
• [23]Wheatley K, Ives N, Gray R, Kalra PA, Moss JG, Baigent C, Carr S, Chalmers N, Eadington D, Hamilton G, Lipkin G, Nicholson A, Scoble J: Revascularization versus medical therapy for renal-artery stenosis. N Engl J Med 2009, 361(20):1953-1962.
• [24]Bax L, Woittiez AJ, Kouwenberg HJ, Mali WP, Buskens E, Beek FJ, Braam B, Huysmans FT, Schultze Kool LJ, Rutten MJ, Doorenbos CJ, Aarts JC, Rabelink TJ, Plouin PF, Raynaud A, van Montfrans GA, Reekers JA, van den Meiracker AH, Pattynama PM, van de Ven PJ, Vroegindeweij D, Kroon AA, de Haan MW, Postma CT, Beutler JJ: Stent placement in patients with atherosclerotic renal artery stenosis and impaired renal function: a randomized trial. Ann Intern Med 2009, 150(12):840-848. W150–841
• [25]Mui KW, Sleeswijk M, van den Hout H, van Baal J, Navis G, Woittiez AJ: Incidental renal artery stenosis is an independent predictor of mortality in patients with peripheral vascular disease. J Am Soc Nephrol 2006, 17(7):2069-2074.
• [26]Riehl J, Schmitt H, Bongartz D, Bergmann D, Sieberth HG: Renal artery stenosis: evaluation with colour duplex ultrasonography. Nephrol Dial Transplant 1997, 12(8):1608-1614.
• [27]Degnan AJ, Young VE, Gillard JH: Advances in noninvasive imaging for evaluating clinical risk and guiding therapy in carotid atherosclerosis. Expert Rev Cardiovasc Ther 2012, 10(1):37-53.