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. 2015 Aug 27:351:h4395.
doi: 10.1136/bmj.h4395.

Risk prediction models for contrast induced nephropathy: systematic review

Samuel A Silver  1 , Prakesh M Shah  2 , Glenn M Chertow  3 , Shai Harel  4 , Ron Wald  5 , Ziv Harel  6
Affiliations

Risk prediction models for contrast induced nephropathy: systematic review

Samuel A Silver et al. BMJ. .

Erratum in

Abstract

Objectives: To look at the available literature on validated prediction models for contrast induced nephropathy and describe their characteristics.

Design: Systematic review.

Data sources: Medline, Embase, and CINAHL (cumulative index to nursing and allied health literature) databases.

Review methods: Databases searched from inception to 2015, and the retrieved reference lists hand searched. Dual reviews were conducted to identify studies published in the English language of prediction models tested with patients that included derivation and validation cohorts. Data were extracted on baseline patient characteristics, procedural characteristics, modelling methods, metrics of model performance, risk of bias, and clinical usefulness. Eligible studies evaluated characteristics of predictive models that identified patients at risk of contrast induced nephropathy among adults undergoing a diagnostic or interventional procedure using conventional radiocontrast media (media used for computed tomography or angiography, and not gadolinium based contrast).

Results: 16 studies were identified, describing 12 prediction models. Substantial interstudy heterogeneity was identified, as a result of different clinical settings, cointerventions, and the timing of creatinine measurement to define contrast induced nephropathy. Ten models were validated internally and six were validated externally. Discrimination varied in studies that were validated internally (C statistic 0.61-0.95) and externally (0.57-0.86). Only one study presented reclassification indices. The majority of higher performing models included measures of pre-existing chronic kidney disease, age, diabetes, heart failure or impaired ejection fraction, and hypotension or shock. No prediction model evaluated its effect on clinical decision making or patient outcomes.

Conclusions: Most predictive models for contrast induced nephropathy in clinical use have modest ability, and are only relevant to patients receiving contrast for coronary angiography. Further research is needed to develop models that can better inform patient centred decision making, as well as improve the use of prevention strategies for contrast induced nephropathy.

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Conflict of interest statement

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; SAS is supported by a postdoctoral fellowship through the Kidney Research Scientist Core Education and National Training Program (cofunded by the Kidney Foundation of Canada, Canadian Society of Nephrology, and Canadian Institutes of Health Research); no financial relationships with any organisations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.

Figures

None
Flow diagram of included studies. CIN=contrast induced nephropathy
See this image and copyright information in PMC

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