Severity of coronary artery disease is associated with contrast induced nephropathy in patients with impaired renal function

2020 ◽  
Vol 27 (1) ◽  
pp. 164
Author(s):  
Serhat Sigirci ◽  
Ahmet Gurdal ◽  
Kadriye Kilickesmez
Keyword(s):  
Coronary Artery Disease ◽  
Renal Function ◽  
Coronary Artery ◽  
Impaired Renal Function ◽  
Contrast Induced Nephropathy ◽  
Artery Disease

scholarly journals Impaired renal function impacts negatively on vascular stiffness in patients with coronary artery disease

2013 ◽  
Vol 14 (1) ◽  
Author(s):  
Sabrina H Rossi ◽  
Emily P McQuarrie ◽  
William H Miller ◽  
Ruth M Mackenzie ◽  
Jane A Dymott ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Renal Function ◽  
Coronary Artery ◽  
Impaired Renal Function ◽  
Vascular Stiffness ◽  
Artery Disease

scholarly journals A Predictive Model Based on a New CI-AKI Definition to Predict Contrast Induced Nephropathy in Patients With Coronary Artery Disease With Relatively Normal Renal Function

2021 ◽  
Vol 8 ◽  
Author(s):  
Hanjun Mo ◽  
Fang Ye ◽  
Danxia Chen ◽  
Qizhe Wang ◽  
Ru Liu ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Renal Function ◽  
Statistical Analysis ◽  
Coronary Artery ◽  
High Risk ◽  
Risk Score ◽  
Normal Renal Function ◽  
Contrast Induced Nephropathy ◽  
Artery Disease ◽  
New Criteria

Background: Contrast induced nephropathy (CIN) is a common complication in patients receiving intravascular contrast media. In 2020, the American College of Radiology and the National Kidney Foundation issued a new contrast induced acute kidney injury (CI-AKI) criteria. Therefore, we aimed to explore the potential risk factors for CIN under the new criteria, and develop a predictive model for patients with coronary artery disease (CAD) with relatively normal renal function (NRF).Methods: Patients undergoing coronary angiography or percutaneous coronary intervention at Zhongshan Hospital, Fudan University between May 2019 and April 2020 were consecutively enrolled. Eligible candidates were selected for statistical analysis. Univariate and multivariate logistic regression analyses were used to identify the predictive factors. A stepwise method and a machine learning (ML) method were used to construct a model based on the Akaike information criterion. The performance of our model was evaluated using the area under the receiver operating characteristic curves (AUC) and calibration curves. The model was further simplified into a risk score.Results: A total of 2,009 patients with complete information were included in the final statistical analysis. The results showed that the incidence of CIN was 3.2 and 1.2% under the old and new criteria, respectively. Three independent predictors were identified: baseline uric acid level, creatine kinase-MB level, and log (N-terminal pro-brain natriuretic peptide) level. Our stepwise model had an AUC of 0.816, which was higher than that of the ML model (AUC = 0.668, P = 0.09). The model also achieved accurate predictions regarding calibration. A risk score was then developed, and patients were divided into two risk groups: low risk (total score < 10) and high risk (total score ≥ 10).Conclusions: In this study, we first identified important predictors of CIN in patients with CAD with NRF. We then developed the first CI-AKI model on the basis of the new criteria, which exhibited accurate predictive performance. The simplified risk score may be useful in clinical practice to identify high-risk patients.

P1585Increased circulating galectin 1 level is associated with progression of kidney function decline in patients with suspected coronary artery disease, independent of diabetes

2019 ◽  
Vol 40 (Supplement_1) ◽  
Author(s):  
C S Kuo ◽  
R H Chou ◽  
Y W Lu ◽  
S J Lin ◽  
P H Huang
Keyword(s):  
Coronary Artery Disease ◽  
Renal Function ◽  
Coronary Artery ◽  
Coronary Angiography ◽  
Kidney Function ◽  
Suspected Coronary Artery Disease ◽  
Contrast Induced Nephropathy ◽  
Baseline Serum ◽  
Renal Function Decline ◽  
Artery Disease

Abstract Background Galectin-1 modulates acute and chronic inflammation, and is associated with glucose homeostasis and chronic renal disease. Whether serum Galectin-1 levels could predict the short-term and long-term renal outcomes after contrast exposure in patients with suspected coronary artery disease remains uncertain. Purpose This study aimed to evaluate the relationship between serum Galectin-1 levels and the incidence of contrast-induced nephropathy and to investigate the predictive role of circulating galectin-1 levels in renal function decline in patients undergoing coronary angiography. Methods In total, 798 patients who had received coronary angiography were enrolled. Serum galectin-1 levels were determined before administration of contrast media. Contrast-induced nephropathy was defined as a rise in serum creatinine of 0.5 mg/dL or a 25% increase from baseline within 48 h after the procedure. Progressive renal function decline was defined as >30% decrease in estimated glomerular filtration rate after discharge. All patients were followed up for at least one year or until the occurrence of death after coronary angiography. Results Overall, contrast-induced nephropathy occurred in 41 (5.1%) patients. During a median follow-up of 1.4±1.1 years, 80 (10.0%) cases had subsequent decline in renal function. After adjustment for demographic characteristics, kidney function, traditional risk factors, and medications, higher galectin-1 level was found to be independently associated with a higher risk for mortality and renal function decline (tertile 2, HR=3.12 95% CI,1.25–7.78; tertile 3, HR=3.25, 95% CI,1.42–7.41) but not for contrast-induced nephropathy, regardless of the presence of diabetes. Conclusions Higher baseline serum galectin-1 levels were associated with a higher risk of mortality and renal function decline in patients undergoing coronary angiography. Galectin-1 may play a pivotal role in progressive renal dysfunction, but further studies are needed to verify these results. Acknowledgement/Funding Ministry of Science and Technology of Taiwan (MOST 104-2314-B-075-047), Taipei Veterans General Hospital (V105C-0207, V106C-045, V108C-195)

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