Clinical and Experimental Nephrology

, Volume 23, Issue 7, pp 969–981 | Cite as

A simple risk score model for predicting contrast-induced nephropathy after coronary angiography in patients with diabetes

  • Jun-feng Zeng
  • Shi-qun Chen
  • Jian-feng Ye
  • Yi Chen
  • Li Lei
  • Xiao-qi LiuEmail author
  • Yong LiuEmail author
  • Yi Wang
  • Ji-jin Lin
  • Ji-yan Chen
Original article



Contrast-induced nephropathy (CIN) is a common complication in patients undergoing coronary angiography (CAG) or percutaneous coronary intervention (PCI) and associated with poor outcome. Some previous studies have already set up models to predict CIN, but there is no model for patients with diabetes mellitus (DM) especially. Therefore, we aim to develop and validate a simple risk score for predicting the risk of CIN in patients with DM undergoing CAG/PCI.


A total of 1157 consecutive patients with DM undergoing CAG/PCI were randomly assigned to a development cohort (n = 771) and a validation cohort (n = 386). The primary endpoint was CIN, which was defined as an absolute increase in serum creatinine (SCr) by 0.5 mg/dL from the baseline within 48–72 h after contrast exposure. The independent predictors for CIN were identified by multivariate logistic regression, and the discrimination and calibration of the risk score were assessed by ROC curve and Hosmer–Lemeshow test, respectively.


The overall incidence of CIN was 45 (3.9%). The new simple risk score (Chen score), which included four independent variables (age > 75 years, acute myocardial infarction, SCr > 1.5 mg/dL, the use of intra-aortic balloon pump), exhibited a similar discrimination and predictive ability on CIN (AUC 0.813, 0.843, 0.796, P > 0.05, respectively), mortality (AUC 0.735, 0.771, 0.826, respectively) and MACEs when being compared with the classical Mehran or ACEF risk score.


Our data suggest that the new simple risk score might be a good tool for predicting CIN in patients with DM undergoing CAG/PCI.


Contrast-induced nephropathy Diabetes mellitus Risk score model Coronary angiography Percutaneous coronary intervention 


Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.

Ethical approval

The study was approved by the Ethics Research Committee of Guangdong General Hospital.

Informed consent

We provided all individual patients with the option to opt out of participation.

Supplementary material

10157_2019_1739_MOESM1_ESM.docx (31 kb)
Supplementary material 1 (DOCX 30 kb)


  1. 1.
    McCullough PA. Contrast-induced nephropathy: definitions, epidemiology, and implications. Interv Cardiol Clin. 2014;3(3):357–62.Google Scholar
  2. 2.
    Abe M, Morimoto T, Akao M, Furukawa Y, Nakagawa Y, Shizuta S, et al. Relation of contrast-induced nephropathy to long-term mortality after percutaneous coronary intervention. Am J Cardiol. 2014;114(3):362–8.CrossRefGoogle Scholar
  3. 3.
    Tsai TT, Patel UD, Chang TI, Kennedy KF, Masoudi FA, Matheny ME, et al. Contemporary incidence, predictors, and outcomes of acute kidney injury in patients undergoing percutaneous coronary interventions: insights from the NCDR Cath-PCI registry. JACC Cardiovasc Interv. 2014;7(1):1–9.CrossRefGoogle Scholar
  4. 4.
    James MT, Samuel SM, Manning MA, Tonelli M, Ghali WA, Faris P, et al. Contrast-induced acute kidney injury and risk of adverse clinical outcomes after coronary angiography: a systematic review and meta-analysis. Circ Cardiovasc Interv. 2013;6(1):37–43.CrossRefGoogle Scholar
  5. 5.
    Lakhal K, Ehrmann S, Chaari A, Laissy JP, Regnier B, Wolff M, et al. Acute Kidney Injury Network definition of contrast-induced nephropathy in the critically ill: incidence and outcome. J Crit Care. 2011;26(6):593–9.CrossRefGoogle Scholar
  6. 6.
    Ohno I, Hayashi H, Aonuma K, Horio M, Kashihara N, Okada H et al.; Japanese Society of Nephrology, Japan Radiological Society, and Japanese Circulation Society Science Advisory and Coordinating Committee. Guidelines on the use of iodinated contrast media in patients with kidney disease 2012: digest version: JSN, JRS, and JCS Joint Working Group. Clin Exp Nephrol. 2013;17(4):441–79.CrossRefGoogle Scholar
  7. 7.
    Sun G, Chen P, Wang K, Li H, Chen S, Liu J, He Y, Song F, Liu Y, Chen JY. Contrast-induced nephropathy and long-term mortality after percutaneous coronary intervention in patients with acute myocardial infarction. Angiology. 2018;15:3319718803677. Scholar
  8. 8.
    Silver SA, Shah PM, Chertow GM, Harel S, Wald R, Harel Z. Risk prediction models for contrast induced nephropathy: systematic review. BMJ. 2015;351:h4395.CrossRefGoogle Scholar
  9. 9.
    Allen DW, Ma B, Leung KC, Graham MM, Pannu N, Traboulsi M, et al. Risk prediction models for contrast-induced acute kidney injury accompanying cardiac catheterization: systematic review and meta-analysis. Can J Cardiol. 2017;33(6):724–36.CrossRefGoogle Scholar
  10. 10.
    Mehran R, Aymong ED, Nikolsky E, Lasic Z, Iakovou I, Fahy M, et al. A simple risk score for prediction of contrast-induced nephropathy after percutaneous coronary intervention. J Am Coll Cardiol. 2004;44(7):1393–9.Google Scholar
  11. 11.
    Andò G, Morabito G, de Gregorio C, Trio O, Saporito F, Oreto G. The ACEF score as predictor of acute kidney injury in patients undergoing primary percutaneous coronary intervention. Int J Cardiol. 2013;168(4):4386–7.CrossRefGoogle Scholar
  12. 12.
    Chamberlain JJ, Herman WH, Leal S, Rhinehart AS, Shubrook JH, Skolnik N, et al. Pharmacologic therapy for type 2 diabetes: synopsis of the 2017 American Diabetes Association standards of medical care in diabetes. Ann Intern Med. 2017;166(8):572–8.CrossRefGoogle Scholar
  13. 13.
    Liu Y, Chen JY, Tan N, Zhou YL, Yu DQ, Chen ZJ, et al. Safe limits of contrast vary with hydration volume for prevention of contrast-induced nephropathy after coronary angiography among patients with a relatively low risk of contrast-induced nephropathy. Circ Cardiovasc Interv. 2015;8(6):e1859.CrossRefGoogle Scholar
  14. 14.
    Cockcroft DW, Gault MH. Prediction of creatinine clearance from serum creatinine. Nephron. 1976;16(1):31–41.CrossRefGoogle Scholar
  15. 15.
    Levey AS, Greene T, Kusek JW, Beck GJ. A simplified equation to predict glomerular filtration rate from serum creatinine. J Am Soc Nephrol. 2000;11:155A (abstract).Google Scholar
  16. 16.
    Azzalini L, Spagnoli V, Ly HQ. Contrast-induced nephropathy: from pathophysiology to preventive strategies. Can J Cardiol. 2016;32(2):247–55.CrossRefGoogle Scholar
  17. 17.
    Maioli M, Toso A, Gallopin M, Leoncini M, Tedeschi D, Micheletti C, et al. Preprocedural score for risk of contrast-induced nephropathy in elective coronary angiography and intervention. J Cardiovasc Med (Hagerstown). 2010;11(6):444–9.CrossRefGoogle Scholar
  18. 18.
    Brown JR, DeVries JT, Piper WD, Robb JF, Hearne MJ, Ver LP, et al. Serious renal dysfunction after percutaneous coronary interventions can be predicted. Am Heart J. 2008;155(2):260–6.CrossRefGoogle Scholar
  19. 19.
    Ranucci M, Castelvecchio S, Menicanti L, Frigiola A, Pelissero G. Risk of assessing mortality risk in elective cardiac operations: age, creatinine, ejection fraction, and the law of parsimony. Circulation. 2009;119(24):3053–61.CrossRefGoogle Scholar
  20. 20.
    Marenzi G, Lauri G, Assanelli E, Campodonico J, De Metrio M, Marana I, et al. Contrast-induced nephropathy in patients undergoing primary angioplasty for acute myocardial infarction. J Am Coll Cardiol. 2004;44(9):1780–5.CrossRefGoogle Scholar
  21. 21.
    Ji L, Su X, Qin W, Mi X, Liu F, Tang X, et al. Novel risk score of contrast-induced nephropathy after percutaneous coronary intervention. Nephrology (Carlton). 2015;20(8):544–51.CrossRefGoogle Scholar
  22. 22.
    Tsai TT, Patel UD, Chang TI, Kennedy KF, Masoudi FA, Matheny ME, et al. Validated contemporary risk model of acute kidney injury in patients undergoing percutaneous coronary interventions: insights from the National Cardiovascular Data Registry Cath-PCI Registry. J Am Heart Assoc. 2014;3(6):71–9.CrossRefGoogle Scholar
  23. 23.
    Inohara T, Kohsaka S, Abe T, Miyata H, Numasawa Y, Ueda I, et al. Development and validation of a pre-percutaneous coronary intervention risk model of contrast-induced acute kidney injury with an integer scoring system. Am J Cardiol. 2015;115(12):1636–42.CrossRefGoogle Scholar
  24. 24.
    Gu G, Xing H, Zhou Y, Cui W. Inverse correlation between left ventricular end-diastolic pressure and contrast-induced nephropathy in patients undergoing percutaneous coronary intervention. Clin Exp Nephrol. 2018;22(4):808–14.CrossRefGoogle Scholar
  25. 25.
    Gao Y, Li D, Cheng H, Chen Y. Derivation and validation of a risk score for contrast-induced nephropathy after cardiac catheterization in Chinese patients. Clin Exp Nephrol. 2014;18(6):892–8.CrossRefGoogle Scholar
  26. 26.
    Bouzasmosquera A, Vázquezrodríguez JM, Calviñosantos R, Peteirovázquez J, Floresríos X, Marzoarivas R, et al. Contrast-induced nephropathy and acute renal failure following emergent cardiac catheterization: incidence, risk factors and prognosis. Rev Esp Cardiol. 2007;60(10):1026–34.CrossRefGoogle Scholar
  27. 27.
    Stacul F, van der Molen AJ, Reimer P, Webb JA, Thomsen HS, Morcos SK, et al. Contrast induced nephropathy: updated ESUR Contrast Media Safety Committee guidelines. Eur Radiol. 2011;21(12):2527–41.CrossRefGoogle Scholar
  28. 28.
    Bartholomew BA, Harjai KJ, Dukkipati S, Boura JA, Yerkey MW, Glazier S, et al. Impact of nephropathy after percutaneous coronary intervention and a method for risk stratification. Am J Cardiol. 2004;93(12):1515–9.CrossRefGoogle Scholar
  29. 29.
    Tziakas D, Chalikias G, Stakos D, Apostolakis S, Adina T, Kikas P, et al. Development of an easily applicable risk score model for contrast-induced nephropathy prediction after percutaneous coronary intervention: a novel approach tailored to current practice. Int J Cardiol. 2013;163(1):46–55.CrossRefGoogle Scholar
  30. 30.
    Tang EW, Wong CK, Herbison P. Global Registry of Acute Coronary Events (GRACE) hospital discharge risk score accurately predicts long-term mortality post acute coronary syndrome. Am Heart J. 2007;153(1):29–35.CrossRefGoogle Scholar

Copyright information

© Japanese Society of Nephrology 2019

Authors and Affiliations

  • Jun-feng Zeng
    • 1
    • 2
  • Shi-qun Chen
    • 1
    • 3
  • Jian-feng Ye
    • 4
  • Yi Chen
    • 1
    • 2
  • Li Lei
    • 5
  • Xiao-qi Liu
    • 6
    Email author
  • Yong Liu
    • 1
    Email author
  • Yi Wang
    • 2
  • Ji-jin Lin
    • 1
  • Ji-yan Chen
    • 1
  1. 1.Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Department of CardiologyGuangdong Cardiovascular Institute, Guangdong General Hospital, Guangdong Academy of Medical SciencesGuangzhouChina
  2. 2.School of PharmacyGuangdong Pharmaceutical UniversityGuangzhouChina
  3. 3.Zhuhai Hospital, Guangdong General Hospital (Zhuhai Golden Bay Center Hospital)ZhuhaiChina
  4. 4.Dongguan People’s HospitalDongguanChina
  5. 5.The Second School of Clinical MedicineSouthern Medical UniversityGuangzhouChina
  6. 6.Guangdong Provincial Key Laboratory of Coronary Heart Disease Prevention, Department of PharmacyGuangdong Cardiovascular Institute, Guangdong General Hospital, Guangdong Academy of Medical SciencesGuangzhouChina

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