Application of 17 Contrast-Induced Acute Kidney Injury Risk Prediction Models

Serif, Levent; Chalikias, Georgios K.; Didagelos, Matthaios; Stakos, Dimitrios; Kikas, Petros; Thomaidis, Adina; Lantzouraki, Asimina; Ziakas, Antonios; Tziakas, Dimitrios

doi:10.1159/000506379

Cited by 9 publications

(9 citation statements)

References 36 publications

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“…Published predictive models for CI-AKI are not excelling and show conflicting results in external validation studies. [31,32] An interesting common aspect is the high NPV, as seen in our study. We applied two scored based models and saw an increment in AUC by including urinary NGAL/creatinine ratios.…”

Section: Plos Onesupporting

confidence: 76%

Biomarkers in the prediction of contrast media induced nephropathy – the BITCOIN study

et al. 2020

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Background Subjects with chronic kidney disease are at increased risk for contrast-induced acute kidney injury (CI-AKI). Risk stratification is traditionally based on glomerular filtration rate (GFR) and proteinuria. The present trial examines, whether tubular and inflammatory biomarkers are able to identify subjects at increased risk as well. Methods We performed a prospective study in 490 patients undergoing coronary angiography. An increase of serum creatinine concentration ≥ 0.3 mg/dl from baseline to day 2–3 was defined as primary endpoint (CI-AKI). Urinary neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), and calprotectin were assessed < 24h before coronary angiography. Prognostic accuracy was assessed by receiver operating characteristics (ROC) calculations. Results 30 (6.1%) patients suffered from CI-AKI (27 AKIN stage I, 3 AKIN stage II, 0 AKIN stage III). Those subjects who developed CI-AKI had 3.1 fold higher baseline urinary NGAL/creatinine ratios than those without CI-AKI (60.8 [IQR 18.7–93.1] μg/mg vs. 19.9 [IQR 12.3–38.9] μg/mg, p = 0.001). In those subjects without clinically overt CKD (eGFR > 60 ml/min, urinary albumin creatinine ratio <30 mg/g), the NGAL/creatinine ratio was 2.6 higher in CI-AKI vs. no CI-AKI (47.8 [IQR 11.8–75.3] vs. 18.6 [IQR 11.7–36.3] μg/mg). No significant differences were obtained for KIM-1 and calprotectin (p>0.05 each). ROC analyses revealed an area under the curve (AUC) of 0.68 (95% CI 0.60–0.81) for NGAL/creatinine. An NGAL/creatinine ratio < 56.4 μg/mg has a negative predictive value of 96.5%. Conclusions The present study is the largest investigation on the use of urinary biomarkers for CI-AKI risk stratification so far. It shows that NGAL provides prognostic information beyond the glomerular biomarkers eGFR and proteinuria.

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Section: Plos Onesupporting

confidence: 76%

Biomarkers in the prediction of contrast media induced nephropathy – the BITCOIN study

et al. 2020

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“…In 2004, Mehran et al ( 49 ) proposed one the first objective risk score for CI-AKI risk combining eight variables: systolic blood pressure < 80 mm Hg, intra-aortic balloon pump, NYHA class III/IV, age >75 years, anemia defined by baseline hematocrit value <39% for men and <36% for women, diabetes mellitus, CM volume (1 point for every 100 ml) and estimated glomerular filtration rate less than 60 ml/min/1.73 m 2 (more points for more severe reduction of kidney function). This risk score is presently used in many catheterization laboratories and has been repeatedly externally validated ( 50 , 51 ). The risk score by Mehran et al involves some parameters that can be obtained only during the procedure and make the clinical application of the score challenging.…”

Section: Risk Stratification and Predictionmentioning

confidence: 99%

Contrast-induced acute kidney injury and its contemporary prevention

Sůva¹,

Kala²,

Poloczek³

et al. 2022

Front. Cardiovasc. Med.

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The complexity and application range of interventional and diagnostic procedures using contrast media (CM) have recently increased. This allows more patients to undergo procedures that involve CM administration. However, the intrinsic CM toxicity leads to the risk of contrast-induced acute kidney injury (CI-AKI). At present, effective therapy of CI-AKI is rather limited. Effective prevention of CI-AKI therefore becomes crucially important. This review presents an in-depth discussion of CI-AKI incidence, pathogenesis, risk prediction, current preventive strategies, and novel treatment possibilities. The review also discusses the difference between CI-AKI incidence following intraarterial and intravenous CM administration. Factors contributing to the development of CI-AKI are considered in conjunction with the mechanism of acute kidney damage. The need for ultimate risk estimation and the prediction of CI-AKI is stressed. Possibilities of CI-AKI prevention is evaluated within the spectrum of existing preventive measures aimed at reducing kidney injury. In particular, the review discusses intravenous hydration regimes and pre-treatment with statins and N-acetylcysteine. The review further focuses on emerging alternative imaging technologies, alternative intravascular diagnostic and interventional procedures, and new methods for intravenous hydration guidance; it discusses the applicability of those techniques in complex procedures and their feasibility in current practise. We put emphasis on contemporary interventional cardiology imaging methods, with a brief discussion of CI-AKI in non-vascular and non-cardiologic imaging and interventional studies.

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“…These three risk models showed less discrimination capability. Perhaps, due to the difference in CA-AKI definition from the original studies 9,22,25 . Because c-statistics is a function of sensitivity and specificity of risk score, differences in the definition of CA-AKI can affect its value 7 .…”

Section: Discussionmentioning

confidence: 99%

“…The third external validation exhibited a low capability of discriminating power with c-statistic 0.502, even though the study was performed in the same setting as in the first external validation at different times (Supplementary Table 2A.) 9 . Our finding also demonstrated low discriminatory ability with c-statistic 0.530 in Tziakas' model.…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, several CA-AKI risk prediction models to identify patients at high risk for developing CA-AKI after angiography or angioplasty have been developed. However, the lack of extensive external validations limits generalizability and clinical acceptance [7][8][9] . Since 2012 the Kidney Disease Improving Global Outcomes (KDIGO) has updated the definition for CA-AKI.…”

Section: Introductionmentioning

confidence: 99%

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Performance of contrast-associated acute kidney injury predictive risk models in Thai cardiac angiography or angioplasty patients

Sutheechai¹,

Lailakdamrong²,

Sudchada³

2022

Pharm Sci Asia

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Several risk prediction models of Contrast-associated acute kidney injury (CA-AKI) in patients undergoing cardiac angiography or angioplasty are available. However, the lack of extensive external validations limits generalizability and clinical acceptance. This study conducted the external validation of three CA-AKI predictive risk models (Chen's, Inohara's, and Tziakas' risk models) and determined the incidence of CA-AKI in Thai patients undergoing cardiac angiography or angioplasty. A total of 647 medical records of patients who underwent elective cardiac angiography (n=446) and angioplasty (n=201) were reviewed. Fifty-five percent were male, mean age 62.6±10.2 years, and mean estimated glomerular filtration rate (eGFR) 69.93±24.30 ml/min/1.73 m2). Incidents of CA-AKI, defined as an absolute increase of serum creatinine of at least 0.3 mg/dL within 48 hours or a relative increase of at least 50% within seven days after the procedure, were collected. The results showed that 78 patients (12.1%) had developed CA-AKI. Chen's, Inohara's, and Tziakas' predictive risk models exhibited low discriminative ability with c-statistic of 0.571, 0.551, and 0.530, respectively. Due to low discriminative capability, these risk models may have low sensitivity to predict CA-AKI in Thai patients undergoing elective cardiac angiography or angioplasty.

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Application of 17 Contrast-Induced Acute Kidney Injury Risk Prediction Models

Cited by 9 publications

References 36 publications

Biomarkers in the prediction of contrast media induced nephropathy – the BITCOIN study

Biomarkers in the prediction of contrast media induced nephropathy – the BITCOIN study

Contrast-induced acute kidney injury and its contemporary prevention

Performance of contrast-associated acute kidney injury predictive risk models in Thai cardiac angiography or angioplasty patients

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