Reviews in Cardiovascular Medicine  2020, Vol. 21 Issue (1): 139-145     DOI: 10.31083/j.rcm.2020.01.583 Serum albumin and the risk of contrast-induced acute kidney injury after percutaneous coronary intervention Ya Wang1, Wen-Jing Sun1, Ze-Sheng Ji1, Chong-Bin Liu1, Rui Wang1, *() 1 Department of Nursing, Medical College of Nursing, Huzhou University, Huzhou, 313000, P. R. China. Abstract:

Serum creatinine and serum albumin levels were measured prior to surgery, and serum creatinine level was also measured at 72 hours following percutaneous coronary intervention in 819 (January 1st, 2015 and December 31th, 2018). According to whether patients developed contrast-induced acute kidney injury or not, they were assigned to either a contrast-induced acute kidney injury group (72 cases, 8.8%) or a non-contrast-induced acute kidney injury group (747 cases; control). Serum albumin was significantly lower in the contrast-induced acute kidney injury group than control (39.33 ± 5.09 g/l and 42.69 ± 5.19 g/l, respectively, P < 0.001). The results of a receiver-operating curve analysis indicated a serum albumin level of 40.5 g/L was the optimal cut-off value for prediction of contrast-induced acute kidney injury and according to a multivariate logistic regression analysis, serum albumin was an independent biomarker for prediction of (95% confidence interval: 0.836-0.935, odds ratio: 0.884, P < 0.001). Serum albumin, a low-cost and easily assessable laboratory protein, was independently related to a greater risk of contrast-induced acute kidney injury among patients that received percutaneous coronary intervention. It is proposed that under these circumstances SA is a potential biomarker for contrast-induced acute kidney injury.

Submitted:  21 October 2019      Accepted:  03 January 2020      Published:  30 March 2020      Fund: 
2016GY41/Natural Science Foundation of Huzhou
2016YZ04/Natural Science Foundation of Huzhou *Corresponding Author(s):  Rui Wang     E-mail:  02240@zjhu.edu.cn Service E-mail this article Add to citation manager E-mail Alert RSS Articles by authors Ya Wang    Wen-Jing Sun    Ze-Sheng Ji    Chong-Bin Liu    Rui Wang   

Figure 1.  Flowchart depicts exclusion of the patients. PCI indicates percutaneous coronary intervention; CIAKI indicates contrast-induced acute kidney injury

Table 1.  Baseline Characteristics of the Study Population.

VariablesCIAKI groupnon-CIAKI groupPn=72n = 747Age, years (mean ± SD)71 (9.2)66.8 (10.4)0.001Gender, male (%)57 (79.2)537 (71.9)0.186BMI (mean ± SD)23.3 (3.8)22.8 (4.1)0.463ACS (%)12 (16.7)115 (15.4)0.442Hypertension (%)52 (72.2)525 (70.4)0.908DM (%)23 (31.9)162 (21.7)0.048Previous PCI (%)21 (29.2)138 (18.5)0.028Cerebrovascular disease (%)3 (4.1)35 (4.7)0.842Systolic pressure (mean ± SD)138.7 (25.4)136.6 (21.1)0.41Diastolic pressure (mean ± SD)83.3 (13)80.1 (13.7)0.058LVEF (%)58.4 (9.6)62.7 (7.6)0.001Aspirin (%)19 (26.4)178 (23.8)0.849Chronic nephrosis (%)2 (2.8)7 (0.9)0.153Smoking history (%)36 (5)369 (49.4)0.949Drinking history (%)21 (29.2)179 (24)0.329Length of stay (mean ± SD)10.3 (9.6)7.9 (3.8)0.035Death in hospital (%)3 (4.2)1 (0.1)<0.001

Table 2.  Laboratory Measurements of the Study Population.

VariablesCIAKI groupnon-CIAKI groupPn=72n=747INR (mean ± SD)1.02 (0.14)0.99 (0.20)0.337D-Dimer, μg/ml (mean ± SD)0.53 (1.20)0.27 (0.43)0.07Fibrinogen, g/L (mean ± SD)4.30 (1.35)3.84 (1.02)0.005Prothrombin time, s (mean ± SD)11.42 (1.63)11.27 (3.18)0.689RDW (mean ± SD)44.99 (3.66)43.72 (3.83)0.007WBC, 10 9/L (mean ± SD)8.07 (4.23)6.93 (2.53)0.028Hb, g/L (mean ± SD)130.21 (19.39)137.80 (17.01)<0.001MCV, fl (mean ± SD)90.61 (11.57)91.14 (7.05)0.570Lymphocyte, 10 9/L (mean ± SD)1.65 (0.84)1.57 (0.71)0.393MPV, fl (mean ± SD)10.55 (1.42)10.76 (3.35)0.609CRP, mg/L (mean ± SD)15.25 (41.82)8.75 (23.09)0.257RBC, 10 12/L (mean ± SD)4.28 (0.62)4.49 (0.54)0.001Hematocrit (mean ± SD)0.39 (0.05)0.41 (0.05)0.001Platelet, 10~9/L (mean ± SD)184.79 (60.30)184.96 (51.16)0.978Neutrophil, 10~9/L (mean ± SD)5.93 (4.04)4.82 (2.36)0.026PDW,% (mean ± SD)15.66 (1.71)15.86 (1.77)0.343Kalium, mmol/L (mean ± SD)3.94 (0.51)3.95 (0.42)0.957Sodium, mmol/L (mean ± SD)141.64 (2.71)142.27 (3.06)0.09Triglyceride, mmol/L (mean ± SD)1.36 (1.03)1.63 (1.41)0.113SA, g/L (mean ± SD)39.33 (5.09)42.69 (5.19)<0.001HDL-C, mmol/L (mean ± SD)1.12 (0.33)1.21 (0.70)0.294Cholesterol, mmol/L (mean ± SD)4.17 (1.15)4.42 (1.23)0.099Bilirubin, μmol/L (mean ± SD)14.32 (6.63)13.87 (6.69)0.591Glucose, mmol/L (mean ± SD)6.40 (2.30)6.40 (2.67)0.990Urea nitrogen (mean ± SD)7.75 (3.40)6.49 (3.67)0.004LDL-C, mmol/L (mean ± SD)2.20 (0.93)2.49 (3.73)0.52BNP (mean ± SD)577.51 (785.76)203.85 (424.61)<0.001eGFR, mL/min/1.73m² (mean ± SD)80.5 (31.89)80.27(20.19)0.954

Figure 2.  Receiver-operating curve (ROC) analysis shows the optimal cutoff value of albumin for CIAKI. AUC indicates area under the curve; 95% CI, 95% confidence interval.

Figure 3.  Scatterplot graph shows the correlation between albumin and eGFR. The central line represents the regression curve. r² indicates square of correlation coefficient. eGFR, estimated glomerular filtration rate.

Table 3.  Angiography and Procedural of the Study Population.

VariablesCIAKI groupnon-CIAKI groupPn=72n=747Number of diseased vesselsInfarct-related artery (mean ± SD)2.49 (0.73)2.42 (0.77)0.457LM(%)2(2.70)45(6)0.422LAD(%)7(9.70)63(8.40)0.661LC(%)19(26.40)242(32.40)0.354RCA(%)59(81.90)568(76)0.309Stent length, mm (mean ± SD)25.45 (9.23)24.83 (8.60)0.666Stent diameter, mm (mean ± SD)3.16 (0.53)3.08 (0.48)0.317

Table 4.  Factors Predicting CIAKI on Logistic Regression Analysis.

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