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Journal of Zhejiang University SCIENCE B

, Volume 13, Issue 8, pp 631–637 | Cite as

Screening for significant atherosclerotic renal artery stenosis with a regression model in patients undergoing transradial coronary angiography/intervention

  • Li-jin Pu
  • Ying Shen
  • Rui-yan Zhang
  • Qi Zhang
  • Lin Lu
  • Feng-hua Ding
  • Jian Hu
  • Zheng-kun Yang
  • Wei-feng Shen
Article

Abstract

Objective

Early detection of atherosclerotic renal artery stenosis (ARAS) is clinically important with respect to blood pressure control, prevention of renal insufficiency, and even improving survival. We investigated whether the presence of significant ARAS (luminal diameter narrowing ≥70%) could be predicted using a logistic regression model before coronary angiography/intervention.

Methods

Initially, we developed a logistic regression model for detecting significant ARAS based upon clinical and angiographic features and biochemical measurements in a cohort of 1 813 patients undergoing transfemoral coronary and renal angiography. This model was then prospectively applied to an additional 495 patients who received transradial renal angiography to ascertain its predictive accuracy for the presence of significant ARAS.

Results

Multivariate regression analysis revealed that older age (≥65 years), resistant hypertension, type 2 diabetes, creatinine clearance (Ccr) ≤60 ml/min, and multivessel coronary disease were independent predictors for significant ARAS. A logistic regression model for detecting ARAS by incorporating conventional risk factors and multivessel coronary disease was generated as: P/(1−P)=exp(−2.618+1.112[age≥65 years]+1.891[resistant hypertension]+0.453[type 2 diabetes]+0.587[Ccr≤60 ml/min]+2.254[multivessel coronary disease]). When this regression model was prospectively applied to the additional 495 patients undergoing transradial coronary and renal angiography, significant ARAS could be detected with a sensitivity of 81.2%, specificity of 88.9%, and positive and negative predictive accuracies of 53.8% and 96.7%, respectively.

Conclusions

The logistic regression model generated in this study may be useful for screening for significant ARAS in patients undergoing transradial coronary angiography/intervention.

Key words

Renal artery stenosis Transradial coronary angiography Resistant hypertension 

CLC number

R543.5 

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Copyright information

© Zhejiang University and Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Li-jin Pu
    • 1
    • 2
  • Ying Shen
    • 1
  • Rui-yan Zhang
    • 1
  • Qi Zhang
    • 1
  • Lin Lu
    • 1
    • 2
  • Feng-hua Ding
    • 1
  • Jian Hu
    • 1
  • Zheng-kun Yang
    • 1
  • Wei-feng Shen
    • 1
    • 2
  1. 1.Department of Cardiology, Ruijin HospitalShanghai Jiao Tong University School of MedicineShanghaiChina
  2. 2.Institute of Cardiovascular DiseasesShanghai Jiao Tong University School of MedicineShanghaiChina

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