Open Access
Open Peer Review

This article has Open Peer Review reports available.

How does Open Peer Review work?

Diastolic dysfunction is associated with an increased risk of contrast-induced nephropathy: a retrospective cohort study

  • Hyang Mo Koo1,
  • Fa Mee Doh1,
  • Kwang Il Ko1,
  • Chan Ho Kim1,
  • Mi Jung Lee1,
  • Hyung Jung Oh1,
  • Seung Hyeok Han1,
  • Beom Seok Kim1,
  • Tae-Hyun Yoo1,
  • Shin-Wook Kang1 and
  • Kyu Hun Choi1Email author
BMC Nephrology201314:146

https://doi.org/10.1186/1471-2369-14-146

Received: 3 October 2012

Accepted: 8 July 2013

Published: 13 July 2013

Abstract

Background

Contrast-induced nephropathy (CIN) is the third leading cause of hospital-acquired acute kidney injury, and it is associated with poor long-term clinical outcomes. Although systolic heart failure is a well-known risk factor for CIN, no studies have yet evaluated the association between diastolic dysfunction and CIN.

Methods

We conducted a retrospective study of 735 patients who underwent percutaneous transluminal coronary angioplasty (PTCA) and had an echocardiography performed within one month of the procedure at our institute, between January 2009 and December 2010. CIN was defined as an increase of ≥ 0.5 mg/dL or ≥ 25% in serum creatinine level during the 72 hours following PTCA.

Results

CIN occurred in 64 patients (8.7%). Patients with CIN were older, had more comorbidities, and had an intra-aortic balloon pump (IABP) placed more frequently during PTCA than patients without CIN. They showed greater high-sensitivity C-reactive protein (hs-CRP) levels and lower estimated glomerular filtration rates (eGFR). Echocardiographic findings revealed lower ejection fraction and higher left atrial volume index and E/E’ in the CIN group compared with non-CIN group. When patients were classified into 3 groups according to the E/E’ values of 8 and 15, CIN occurred in 42 (21.6%) patients in the highest tertile compared with 20 (4.0%) in the middle and 2 (4.3%) in the lowest tertile (p < 0.001). In multivariate logistic regression analysis, E/E’ > 15 was identified as an independent risk factor for the development of CIN after adjustment for age, diabetes, dose of contrast media, IABP use, eGFR, hs-CRP, and echocardiographic parameters [odds ratio (OR) 2.579, 95% confidence interval (CI) 1.082-5.964, p = 0.035]. In addition, the area under the receiver operating characteristic curve of E/E’ was 0.751 (95% CI 0.684-0.819, p < 0.001), which was comparable to that of ejection fraction and left atrial volume index (0.739 and 0.656, respectively, p < 0.001).

Conclusions

This study demonstrated that, among echocardiographic variables, E/E' was an independent predictor of CIN. This in turn suggests that diastolic dysfunction may be a useful parameter in CIN risk stratification.

Keywords

Contrast-induced nephropathy Diastolic dysfunction E/E’

Background

Contrast-induced nephropathy (CIN) is one of the principal complications which develop after procedures using contrast media (CM). Although there are some differences between institutions, the most commonly used definition of CIN in clinical trials is a rise in serum creatinine of > 0.5 mg/dL or > 25% from the baseline value within 72 hours after exposure to the CM. The incidence of CIN is reported to be about 2% in the general population, 7-15% in patients undergoing percutaneous coronary intervention, whereas it increases up to 50% in high-risk patients with diabetes (DM) and renal failure [1, 2]. Recently, risk stratification and application of preventive methods against CIN further reduced the incidence of CIN. However, CIN is still an important problem in that dependence for medical procedures using CM is steadily increasing and that it is closely related with poor long-term clinical outcomes: longer hospital stay, and increased mortality and post-procedural cardiovascular complications [3, 4].

Accordingly, many investigators have tried to reveal the pathogenesis of CIN. Delineated mechanisms include intra-renal vasoconstriction, reduced renal blood flow, medullary hypoxia, oxidative stress, inflammation, endothelial dysfunction, and direct tubular-epithelial cell injury by CM [5]. At the same time, risk factors potentiating the processes explained above were proved out: renal failure, old age, DM, congestive heart failure (CHF), hypotensive event, use of intra-aortic balloon pump (IABP), and ionic/ high-osmolar CM [6].

CHF, especially in advanced stages of New York Heart Association (NYHA) class 3–4 contributes to the development of CIN primarily by decreasing renal perfusion. It is related with systolic dysfunction and low stroke volume [7]. In fact, some researches specifically pointed ejection fraction (EF) < 30-40% out as an independent predictor of CIN [8]. However, CHF per se and just a past history of heart failure increased the incidence of CIN, irrespective of EF [9, 10]. Nevertheless, no studies have yet evaluated the association between diastolic dysfunction and CIN.

The golden standard estimating diastolic function of the heart is to measure left ventricular end-diastolic pressure (LVEDP) with catheterization. However, it is invasive and not a routine practice. On the other hand, E/E’ can be assessed non-invasively with echocardiography, and is known to be less influenced by heart rate, atrial activity, or ejection fraction [11]. In addition, E/E’ levels were well correlated with LVEDP, when patients were categorized into 3 groups based on the E/E’ values of 8 and 15 [12]. E/E’ > 11 also predicted LVEDP > 15 mmHg with a sensitivity of 75% and a specificity of 93% [13]. Among various doppler estimates of diastolic function such as E, E/A, decrease in E/A with the valsalva maneuver, deceleration time (DT), and pulmonary venous atrial reversal duration, E/E’ showed the highest predictive power for LVEDP [12].

So, we aimed to investigate whether E/E’ is an independent risk factor predicting the development of CIN. Effects of E/E’ and CIN on patient mortality were also evaluated.

Methods

Ethics statement

This study was carried out in accordance with the Declaration of Helsinki and approved by the Institutional Review Board (IRB) of Yonsei University Health System Clinical Trial Center. Written consents were not required because this was a retrospective medical record-based study and personally identifiable information was anonymized.

Patients

This retrospective study included 735 patients who underwent percutaneous transluminal coronary angioplasty (PTCA) at Severance Hospital in Seoul, Korea from January 2009 to December 2010. PTCA was conducted in 6837 patients for the following reasons: 1) regular follow-up for known coronary artery occlusive disease (CAOD), 2) suspicion for CAOD based on clinical symptoms or study results (treadmill test, technetium sestamibi scan, or cardiac CT or MRI), or 3) to evaluate whether idiopathic CHF was due to ischemia. Among these, 3302 subjects who had undergone echocardiography within 1 month of PTCA were included. Exposure to other CM within 7 days of PTCA (n = 1576), an absence of data on serum creatinine during the 72 hours following the procedure (n = 503), end-stage renal disease (n = 408), underlying malignancy (n = 43), acute infection (n = 28), or age less than 18 years (n = 9) resulted in the exclusion of an additional 2567 patients.

All patients were hydrated with 0.9% saline at a rate of 1.0 mL/kg/hour for 12 hours pre- and post-exposure to the CM, according to the guidelines of our clinic. In case of an emergency procedure, hydration was initiated immediately prior to the start of angiography and continued for 24 hours after PTCA. Infusion rate was reduced to 0.5 mL/kg/hour when pulmonary edema was noted or ejection fraction was less than 30%.

Non-ionic, dimeric, and iso-osmolar contrast agent (iodixanol: Visipaque, GE Healthcare, Amersham, United Kingdom) was used for PTCA. A hypotensive event was defined as systolic blood pressure < 80 mmHg for at least 1 hour requiring inotropic therapy or IABP insertion within 24 hours of procedure, as described by Mehran et al. [14].

Data collection

Demographic and clinical data at the time of the PTCA were collected through medical chart review. Laboratory findings which were reported 24 hours prior to the PTCA and measured in overnight fasting status, were set as baseline values. CIN was defined as an increase of ≥ 0.5 mg/dL or ≥ 25% in serum creatinine level during the 72 hours following PTCA, that could not be better explained by alternative etiologies. We also used a second definition of CIN according to the Acute Kidney Injury Network (AKIN) criteria: a rise in serum creatinine ≥ 0.3 mg/dL within 48 hours of procedure [3, 15]. Oliguria was not considered because all patients were hydrated and some of them used diuretics.

Hemoglobin, albumin, blood urea nitrogen, creatinine, serum cholesterol, triglycerides, and glucose levels were measured by an Advia 2120 Hematology Analyzer (Siemens Health-care Diagnostics, Deerfield, Illinois). High-sensitivity C-reactive protein (hs-CRP) levels were measured with a BN II analyzer (Dade Behring, Newark, DE, USA) using the latex-enhanced immunonephelometric method. The estimated glomerular filtration rate (eGFR) was calculated using the Modification of Diet in Renal Disease (MDRD) equation [16].

Cardiac status and echocardiographic parameters

Records of PTCA were reviewed for the urgency of the procedure, amount of CM used, interventional strategy, and the number of coronary arteries involved. We also investigated whether any patients had undergone coronary artery bypass graft surgery previously.

Echocardiography was performed with a SONOS 7500 (Philips Ultrasound, Bothell, WA, USA) according to the recommendations of the American Society of Echocardiography (ASE). Inter-ventricular septal thickness (IVSs, IVSd), posterior wall thickness (PWTs, PWTd), left ventricular end-diastolic dimension (LVDd), and left ventricular end-systolic dimension (LVDs) were measured in 2-dimensional M-mode. Pulsed wave doppler was applied to check velocities in the 4-chamber apical view. Volume sampling was positioned at the tip of the mitral valve to measure early LV filling velocity (E) and left atrial contraction velocity (A). Tissue doppler was then conducted with the volume sampling repositioning at the septal annulus of the mitral valve to measure early (E’) and late (A’) diastolic mitral annular velocities.

LV systolic function was defined by EF. The EF was calculated by the modified Simpson’s method, subtracting LVDs from LVDd. LV mass (LVM) was estimated using the Devereux modified ASE cube formula [17], and the LV mass index (LVMI) was calculated by dividing LVM by body surface area.
LVM = 0.8 × [ 1.04 × ( IVSd + LVDd + PWTd ) 3 LVDd 3 ] + 0.6 ( gm )

E/E’ and E/A were calculated to represent diastolic function. DT, the time between peak E wave and the upper deceleration slope extrapolated to zero line, was also determined. In 23 patients exhibiting atrial fibrillation (n = 21, 3.1% in non-CIN group and n = 2, 3.1% in CIN group), average measurements from 10 cardiac cycles were used [11].

Left atrial volume index (LAVI), a marker of volume status, was estimated with the biplane Simpson’s method using the diameters of the LA, which were measured 3 times at the parasternal long axis view (anterior-posterior, superior-inferior) and the 4 chamber view (medio-lateral).

Inter-reader reliability, intra-reader reliability, and reader drift analyses were performed on a random sample of 3% of the entire cohort. The intra-class correlation coefficients for the echocardiographic measures were 0.845 for EF, 0.765 for LVMI, and 0.753 for LAVI.

Statistical analysis

Statistical analysis was performed with the Statistical Package for the Social Sciences (SPSS) for Windows, version 18.0 (Chicago, IL, USA). Data are expressed as a mean ± standard deviation for continuous variables, and as a number and percentage for categorical variables. Normality of distribution was examined by the Shapiro-Wilk test.

We compared the demographic, laboratory, and echocardiographic parameters of patients with CIN with those of patients without CIN using the Student’s t-test, Mann–Whitney U test, or chi-square test. Either ANOVA or the Kruskal-Wallis test was performed to compare the 3 groups, which were classified according to the E/E’ values of 8 and 15. Univariate and multivariate binary logistic regression analyses were conducted to identify risk factors predicting the development of CIN. We also performed receiver operating characteristic (ROC) analysis to confirm the predictive accuracy of echocardiographic parameters for CIN. All-cause mortality was compared between patients using 4 groupings that were based on the presence or absence of diastolic dysfunction (E/E’ > 15) and CIN, by Kaplan-Meier and log-rank test. A p-value of less than 0.05 was considered statistically significant.

Results

Baseline characteristics between patients with CIN and those without CIN

Baseline characteristics of the study subjects are detailed in Table 1. The mean age was 64.8 ± 10.6 years and 69.9% were male. The mean values of eGFR and E/E’ were 74.5 ± 20.5 mL/min/1.73m2 and 13.3 ± 5.3, respectively. A total of 64 patients (8.7%) developed CIN.
Table 1

Baseline characteristics of study subjects

Variables

All (n = 735)

CIN (n = 64)

No CIN

p

(n = 671)

Age (years)

64.8 ± 10.6

70.8 ± 10.5

64.2 ± 10.5

<0.001

Sex (male)

514 (69.9%)

39 (60.9%)

475 (70.8%)

0.101

BMI (kg/m2)

24.5 ± 3.3

22.7 ± 3.3

24.7 ± 3.3

<0.001

Systolic BP (mmHg)

119.6 ± 15.1

119.5 ± 21.6

119.6 ± 14.4

0.979

Diastolic BP (mmHg)

71.9 ± 9.9

69.0 ± 14.2

72.2 ± 9.3

0.119

Hypertension

475 (64.6%)

52 (81.3%)

423 (63.0%)

0.004

Diabetes mellitus

250 (34.0%)

39 (60.9%)

211 (31.4%)

<0.001

Previous CABG

23 (3.1%)

5 (7.8%)

18 (2.7%)

0.042

Emergency/ urgent procedure

160 (21.8%)

23 (35.9%)

137 (20.4%)

0.004

Interventional strategy

   

0.521

 Ballooning

23 (3.1%)

1 (1.6%)

22 (3.3%)

 

 Ballooning + Stent insertion

614 (83.5%)

52 (81.3%)

562 (83.8%)

 

 Ballooning + Stent insertion + Thrombus suction

98 (13.3%)

11 (17.2%)

87 (13.0%)

 

3-vessel disease

241 (32.8%)

39 (60.9%)

202 (30.1%)

<0.001

Hypotensive event

90 (12.2%)

25 (39.1%)

65 (9.7%)

<0.001

IABP use

32 (4.4%)

16 (25.0%)

16 (2.4%)

<0.001

Total volume of CM (mL)

237.0 ± 74.5

222.8 ± 71.4

238.1 ± 74.7

0.179

Volume of CM per weight (mL/kg)

3.69 ± 1.31

4.09 ± 1.86

3.66 ± 1.25

0.179

N-acetylcysteine

233 (33.5%)

15 (42.9%)

218 (33.0%)

0.230

BUN (mg/dL)

18.0 ± 7.3

24.2 ± 11.2

17.4 ± 6.6

<0.001

Creatinine (mg/dL)

1.08 ± 0.41

1.50 ± 0.75

1.04 ± 0.33

<0.001

eGFR (mL/min/1.73m2)

74.5 ± 20.5

54.5 ± 25.8

76.4 ± 18.9

<0.001

Hemoglobin (g/dL)

13.2 ± 1.8

11.5 ± 2.1

13.3 ± 1.7

<0.001

Albumin (g/dL)

4.31 ± 0.48

3.85 ± 0.61

4.35 ± 0.44

<0.001

hs-CRP (mg/L)

10.18 ± 28.84

34.11 ± 47.95

7.84 ± 24.77

<0.001

Cholesterol (mg/dL)

164.5 ± 43.5

167.5 ± 56.5

164.3 ± 42.2

0.722

Triglyceride (mg/dL)

140.0 ± 82.3

126.0 ± 87.7

141.3 ± 81.7

0.035

Glucose (mg/dL)

124.6 ± 46.3

156.2 ± 71.3

121.6 ± 42.1

<0.001

Ejection fraction (%)

57.5 ± 13.4

48.8 ± 12.8

58.6 ± 12.7

<0.001

E/E'

13.3 ± 5.3

18.2 ± 7.0

12.9 ± 4.9

<0.001

E/A

0.94 ± 0.48

0.95 ± 0.37

0.94 ± 0.49

0.630

Deceleration time (ms)

204.6 ± 50.1

182.5 ± 50.5

206.7 ± 49.7

<0.001

LV mass (g)

213.6 ± 95.7

233.1 ± 56.2

211.9 ± 98.4

0.001

LV mass index (g/m2)

126.3 ± 88.6

144.0 ± 28.9

124.7 ± 91.9

<0.001

LVDd (mm)

50.0 ± 5.0

51.2 ± 5.6

49.9 ± 4.9

0.030

LA volume index (mL/m2)

28.3 ± 9.7

33.4 ± 11.6

27.8 ± 9.4

<0.001

Abbreviations: BMI body mass index; BP blood pressure; BUN blood urea nitrogen; CABG coronary artery bypass graft; CIN contrast-induced nephropathy; CM contrast media; eGFR estimated glomerular filtration rate; hs-CRP high sensitivity C-reactive protein; IABP intra-aortic balloon pump; LA left atrium; LV left ventricle; LVDd left ventricular end-diastolic dimension.

When patients were dichotomized into CIN and non-CIN groups, the CIN group was older and had lower body mass index (BMI) than the non-CIN group. The prevalence of hypertension, DM, emergency/ urgent procedure, three-vessel coronary artery disease (3-VD), previous coronary artery bypass graft surgery, and IABP use during the PTCA was significantly higher in the CIN group compared to the non-CIN group. Within the laboratory findings, patients with CIN demonstrated eGFR, hemoglobin, and albumin levels that were significantly lower, while hs-CRP levels were significantly higher compared to the non-CIN group. Echocardiographic findings revealed that the EF and DT were decreased, while E/E’ (18.2 ± 7.0 vs. 12.9 ± 4.9, p < 0.001), LVMI, LVDd, and LAVI were significantly increased in patients with CIN.

When patients were classified into three groups based on the E/E’ values of 8 and 15, CIN occurred in 42 (21.6%) patients in the highest tertile compared with 20 (4.0%) in the middle and 2 (4.3%) in the lowest tertile (p < 0.001). In addition, patients in the highest tertile were older and had more hypertension, DM, and 3-VD. They also experienced more hypotensive events and had IABPs placed more frequently during procedure than patients in the middle and lowest tertiles. Among the echocardiographic parameters, LVMI, LVDd, and LAVI were significantly increased in the highest tertile (Table 2).
Table 2

Differences in variables according to tertiles of E/E

Variables

E/E’ ≤ 8

8 < E/E’ ≤ 15

E/E’ > 15

p

(n = 47)

(n = 494)

(n = 194)

Age (years)

57.0 ± 9.5

63.4 ± 10.3

70.1 ± 9.6

0.036

Sex (male)

42 (89.4%)

375 (75.9%)

97 (50.0%)

<0.001

BMI (kg/m2)

23.7 ± 2.3

24.7 ± 3.3

24.4 ± 3.6

0.061

Systolic BP (mmHg)

115.3 ± 13.6

119.9 ± 14.0

119.9 ± 17.9

0.018

Diastolic BP (mmHg)

71.3 ± 9.4

72.6 ± 9.4

70.4 ± 10.8

0.150

Hypertension

21 (44.7%)

305 (61.7%)

149 (76.8%)

<0.001

Diabetes mellitus

12 (25.5%)

154 (31.2%)

84 (43.3%)

0.005

Previous CABG

0 (0.0%)

13 (2.6%)

10 (5.2%)

0.130

Emergency/ urgent procedure

5 (10.6%)

103 (20.9%)

52 (26.8%)

0.038

Interventional strategy

   

0.680

 Ballooning

1 (2.1%)

14 (2.8%)

8 (4.1%)

 

 Ballooning + Stent insertion

42 (89.4%)

415 (84.0%)

157 (80.9%)

 

 Ballooning + Stent insertion + Thrombus suction

4 (8.5%)

65 (13.2%)

29 (14.9%)

 

3-vessel disease

12 (25.5%)

134 (27.1%)

95 (49.0%)

<0.001

Hypotensive event

3 (6.4%)

45 (9.1%)

42 (21.6%)

<0.001

IABP use

0 (0.0%)

11 (2.2%)

21 (10.8%)

<0.001

Total volume of CM (mL)

236.6 ± 89.4

237.9 ± 75.0

234.6 ± 69.1

0.956

Volume of CM per weight (mL/kg)

3.53 ± 1.19

3.62 ± 1.22

3.92 ± 1.53

0.176

N-acetylcysteine

24 (25.3%)

144 (33.2%)

65 (39.2%)

0.071

CIN

2 (4.3%)

20 (4.0%)

42 (21.6%)

<0.001

BUN (mg/dL)

15.6 ± 3.5

17.3 ± 6.3

20.2 ± 9.6

0.112

Creatinine (mg/dL)

1.02 ± 0.25

1.04 ± 0.32

1.21 ± 0.57

0.848

eGFR (mL/min/1.73m2)

82.9 ± 17.9

77.4 ± 18.7

64.9 ± 22.4

0.071

Hemoglobin (g/dL)

13.9 ± 1.3

13.4 ± 1.7

12.3 ± 1.9

0.058

Albumin (g/dL)

4.45 ± 0.43

4.39 ± 0.41

4.06 ± 0.54

0.308

hs-CRP (mg/L)

6.85 ± 29.80

7.67 ± 24.10

17.20 ± 36.50

<0.001

Cholesterol (mg/dL)

161.7 ± 42.7

164.6 ± 42.9

165.4 ± 45.7

0.570

Triglyceride (mg/dL)

143.9 ± 95.3

142.5 ± 85.1

132.4 ± 70.4

0.742

Glucose (mg/dL)

116.6 ± 41.3

121.8 ± 41.6

133.7 ± 56.6

0.205

Ejection fraction (%)

61.0 ± 10.0

59.4 ± 12.1

52.7 ± 14.4

0.578

E/E'

6.7 ± 0.8

11.2 ± 2.1

20.4 ± 4.9

<0.001

E/A

0.98 ± 0.38

0.90 ± 0.50

1.01 ± 0.44

0.065

Deceleration time (ms)

207.5 ± 46.1

207.9 ± 49.5

195.6 ± 52.0

0.699

LV mass (g)

188.6 ± 41.6

212.1 ± 108.2

223.6 ± 64.5

0.014

LV mass index (g/m2)

107.2 ± 22.6

121.5 ± 57.0

143.5 ± 145.8

0.003

LVDd (mm)

48.4 ± 3.5

49.8 ± 4.7

50.8 ± 5.8

0.014

LA volume index (mL/m2)

22.3 ± 4.8

26.6 ± 7.9

34.1 ± 11.9

<0.001

Abbreviations: BMI body mass index; BP blood pressure; BUN blood urea nitrogen; CABG coronary artery bypass graft; CIN contrast-induced nephropathy; CM contrast media; eGFR estimated glomerular filtration rate; hs-CRP high sensitivity C-reactive protein; IABP intra-aortic balloon pump; LA left atrium; LV left ventricle; LVDd left ventricular end-diastolic dimension.

Risk factors for the development of CIN

Logistic regression analysis showed that higher E/E’ level [odds ratio (OR) 1.147, 95% confidence interval (CI) 1.101-1.194, p < 0.001 as a continuous variable/ OR 6.519, 95% CI 3.774-11.260, p < 0.001 as a categorical variable] was a significant risk factor for CIN (Table 3). After adjustment for age, BMI, hypertension, DM, emergency/ urgent procedure, 3-VD, volume of CM per weight, use of IABP, eGFR < 60 mL/min/1.73m2, hemoglobin, albumin, and hs-CRP, E/E’ still remained as an independent risk factor (OR 1.091, 95% CI 1.026-1.159, p = 0.005 as a continuous variable/ OR 3.435, 95% CI 1.522-7.755, p = 0.003 as a categorical variable). In successive models, further adjustments were made with other echocardiographic parameters, EF and LAVI. E/E’ > 15 was found to be a final determinant of CIN (OR 2.579, 95% CI 1.082-5.964, p = 0.035) (Table 4).
Table 3

Univariate logistic regression analysis for contrast-induced nephropathy

Variables

OR

95% CI

p

Age > 75 years (vs. ≤ 75 years)

2.837

1.038-1.097

<0.001

BMI (kg/m2)

0.808

0.738-0.886

<0.001

Hypertension

2.541

1.330-4.852

0.005

Diabetes mellitus

3.401

2.006-55.766

<0.001

Emergency/ urgent procedure

2.187

1.269-3.767

0.005

(vs. elective procedure)

   

3-vessel disease (vs. < 3-vessel involvement)

3.622

2.135-6.145

<0.001

IABP use (vs. non-IABP use)

16.872

7.670-37.113

<0.001

Volume of CM per weight (mL/kg)

1.250

1.024-1.526

0.028

eGFR < 60 mL/min/1.73m2

11.343

6.434-19.997

<0.001

(vs. eGFR ≥ 60 mL/min/1.73m2)

   

Hemoglobin (g/dL)

0.571

0.490-0.664

<0.001

Albumin (g/dL)

0.179

0.111-0.289

<0.001

hs-CRP (mg/L)

1.017

1.010-1.023

<0.001

E/E'

1.147

1.101-1.194

<0.001

E/E' > 15 (vs. E/E’ ≤ 15)

6.519

3.774-11.260

<0.001

EF ≤ 40% (vs. EF > 40%)

5.142

2.907-9.096

<0.001

LAVI > 35 mL/m2 (vs. LAVI ≤ 35 mL/m2)

3.865

2.230-6.700

<0.001

Data are presented as odds ratios (OR) and 95% confidence intervals (CI).

Abbreviations: BMI body mass index; IABP intra-aortic balloon pump; CM contrast media; eGFR estimated glomerular filtration rate; hs-CRP, high sensitivity C-reactive protein; EF ejection fraction; LAVI left atrial volume index.

Table 4

Odds ratios and 95% confidence intervals for contrast-induced nephropathy according to the E/Elevels (Multivariate logistic regression analysis)

 

E/E’

OR

95% CI

p

aModel 1

1.091

1.026-1.159

0.005

bModel 2

3.435

1.522-7.755

0.003

cModel 3

3.344

1.456-7.682

0.004

dModel 4

2.579

1.082-5.964

0.035

a Model 1 (odds ratio per 1 increase in E/E’) : adjusted for age (> 75 years vs. ≤ 75 years), BMI, hypertension, diabetes, emergent/ urgent procedure, 3-vessel disease, IABP use, volume of CM per weight, eGFR (< 60 mL/min/1.73m2 vs. eGFR ≥ 60 mL/min/1.73m2), hemoglobin, albumin, and hs-CRP.

b Model 2 (odds ratio for E/E’ > 15 vs. E/E’ ≤ 15) : adjusted for age (> 75 years vs. ≤ 75 years), BMI, hypertension, diabetes, emergent/ urgent procedure, 3-vessel disease, IABP use, volume of CM per weight, eGFR (< 60 mL/min/1.73m2 vs. eGFR ≥ 60 mL/min/1.73m2), hemoglobin, albumin, and hs-CRP.

c Model 3 (odds ratio for E/E’ > 15 vs. E/E’ ≤ 15) : adjusted for Model 2 plus ejection fraction (≤ 40% vs. > 40%).

d Model 4 (odds ratio for E/E’ > 15 vs. E/E’ ≤ 15) : adjusted for Model 3 plus left atrial volume index (> 35 vs. ≤ 35).

Abbreviations: BMI body mass index; IABP intra-aortic balloon pump; CM contrast media; eGFR estimated glomerular filtration rate; hs-CRP high sensitivity C-reactive protein.

Defining CIN as an increase in serum creatinine ≥ 0.3 mg/dL from the baseline value, according to the AKIN criteria, did not change the independent role of E/E’ for the prediction of CIN (OR 2.456, 95% CI 1.046-6.217, p = 0.044) (see Additional file 1).

In subgroup analysis, CIN occurred most often in patients in the highest tertile of E/E’ irrespective of diabetes status (n = 15, 13.6% in non-DM group, p < 0.001/ n = 27, 32.1% in DM group, p < 0.001). A similar finding was observed in patients with an eGFR < 60 mL/min/1.73m2 (n = 35, 47.3% in the highest tertile of E/E’, p < 0.001), although there was no difference in the development of CIN among the three tertiles of E/E’ in patients with an eGFR ≥ 60 mL/min/1.73m2 (p = 0.199) (Figure 1).
Figure 1

Relationship between diastolic dysfunction and the incidence of CIN according to the presence of diabetes or renal dysfunction. CIN developed most frequently in patients in the highest tertile of E/E’ in all subgroups, except for patients with an eGFR ≥ 60 mL/min/1.73m2.

Receiver operating characteristic analysis of E/E’ for the development of CIN

To estimate the predictive accuracy of the echocardiographic parameters for the development of CIN, ROC analysis was performed. The area under the curve (AUC) for E/E’, EF, and LAVI were 0.75 (95% CI 0.68-0.82, p < 0.001), 0.74 (95% CI 0.67-0.81, p < 0.001), and 0.66 (95% CI 0.58-0.74, p < 0.001), respectively (Figure 2).
Figure 2

Receiver operating characteristic curves for the development of CIN according to the echocardiographic variables (EF, E/ E’, and LAVI). The AUCs of EF, E/E, and LAVI were 0.74, 0.75, and 0.66, respectively (p < 0.001).

When AKIN criteria were applied, estimated AUC of E/E’ for CIN was 0.79 (95% CI 0.73-0.85, p < 0.001) (see Additional file 2).

Survival analysis in CIN and diastolic dysfunction

During a mean follow-up of 17.9 months, 30 patients died. The most common causes of death were cardiovascular disease (n = 16, 53.5%), followed by infection (n = 12, 40%).

Kaplan-Meier analysis showed higher mortality rates in patients who developed CIN (n = 18, 28.1% vs. n = 11, 1.6%). In addition, there was a tendency toward higher mortality in those with diastolic dysfunction and CIN (n = 14, 33.3%) (Figure 3). The two-year survival rates were 98.1% in patients without CIN or diastolic dysfunction, 95.8% in patients with diastolic dysfunction but no CIN, 72.6% in subjects with CIN and normal diastolic function, and 58.1% in patients with both CIN and diastolic dysfunction (p < 0.001).
Figure 3

Kaplan-Meier analysis for cumulative hazard of patient mortality. There was a tendency toward higher mortality in patients with diastolic dysfunction (E/E’ > 15) and/or CIN (p < 0.001).

Comparison of E/E’ with previous risk scoring systems for CIN

We reclassified our patients according to the risk stratification systems suggested by Mehran et al. [14] and Bartholomew et al. [4]. The incidence of CIN was well proportional to both risk scores. Predictive performances for CIN, estimated by AUC on ROC analysis, were about 80% with previous methods and 75% with E/E’ (see Additional file 3).

Discussion

This study showed that patients with CIN exhibited a lower EF and higher E/E’ and LAVI on echocardiography. In addition, the highest tertile of E/E’ was associated with a significantly increased risk of CIN, beyond the well-known risk factors such as DM and renal failure. This implicates that diastolic dysfunction may be a useful parameter for predicting the development of CIN.

There are both patient-related and patient-unrelated factors in the risk stratification systems for CIN. Patient-related factors include chronic kidney disease (CKD), DM, emergency/ urgent procedure, IABP use, CHF, age > 75 years, hypertension, anemia, a hypotensive episode, and LVEF < 40%. Patient-unrelated factors include using ionic and hyper-osmolar contrast agent, and high volume of CM [9, 14]. These factors play a role in the development of CIN primarily by reducing effective renal blood flow, consequently causing hypoxic change and the synthesis of reactive oxygen species. Development of CIN has also been attributed to increased sympathetic tone, renin-angiotensin-aldosterone system (RAAS) activation, the overproduction of many humoral factors such as vasopressin, catecholamines, endothelin, and pro-inflammatory cytokines, and decreased nitric oxide (NO) levels. These hemodynamic and neurohumoral alterations can cause vascular endothelial cell damage and hypertrophic change in the vascular smooth muscle cells, thus further aggravating blood flow disturbances [5, 18].

Although CHF is a well-proven risk factor for CIN, only low ejection fraction has previously been studied, among various components of heart failure such as diastolic dysfunction, ventricular hypertrophy, and volume overload [7, 8, 19]. This has likely been because a decreased effective circulatory volume is considered the primary event in the development of CIN, in patients with CHF [20, 21]. However, the statistical significance of EF disappeared in the multivariate logistic regression analysis, whereas E/E’ remained a significant risk factor for CIN (see Additional file 4). ROC analysis also showed a considerable predictive accuracy for E/E’, which was comparable to that of EF (Figure 2). Moreover, most studies demonstrated that EF only affects CIN rates in patients with severe CHF of NYHA class 3–4 or an EF < 30-40%. Given that CIN occurs in higher rates in CHF patients with lower severity, this suggests that the hemodynamic compromise status in milder stages of heart failure cannot be properly represented by EF [8]. Actually, CIN occurred in 18.2% of patients with EF < 40%, and 7.8% of patients with EF ≥ 40% in our study. However, when patients with severe CHF were excluded, E/E’ still was an independent risk factor for CIN (OR 2.593, 95% CI 1.014-6.633, p = 0.041, data not shown). This finding suggests that diastolic dysfunction may be a more reliable parameter to represent the hemodynamic and neurohumoral alterations observed in CHF.

Studies conducted in patients with CHF and preserved LVEF showed a proportional increase in renal failure according to the diastolic dysfunction [22]. The stiffer the LV, the faster the eGFR declined [23]. The main reasons for this include reduced LV functional reserve, resting/ exercise-exacerbated systolic dysfunction, and chronotropic incompetence, which are responsible for the decrease in blood flow. These result in insufficient tissue perfusion and an ischaemic injury to the kidney [2426]. Initially, LV hypertrophy occurs to compensate for the stiffness of the LV, by increasing stroke volume. But pathologic proliferation, fibrotic deposition, and calcification of the ventricle become evident, and LV compliance eventually decreases [27]. The same vicious cycle in hemodynamics is thought to be the chief mechanism for a higher E/E’ causing CIN. The adverse effect of diastolic dysfunction on patient mortality is partly attributed to these unfavorable geometric changes in the LV (Figure 3).

On the other hand, the neurohumoral changes occurring during the development of CIN further aggravate diastolic dysfunction. Angiotension II and aldosterone promote the growth/ proliferation of both cardiomyocytes and non-myocyte cells like fibroblasts [28]. Pro-inflammatory cytokines such as TNF-α and IL-6 stimulate collagen production by fibroblasts, and bring about a myocardio-depressive effect [29]. We also demonstrated elevated hs-CRP levels in patients in the highest tertile of E/E’ (Table 2). In addition, increased sympathetic tone activates the β-catenin pathway in the cardiomyocytes through the recruitment of Akt (protein kinase B). This up-regulates the production of osteoblastogenic proteins, further aggravating diastolic function [30]. Through these mutual effects on hemodynamic and neurohumoral status, higher E/E’ is thought to cause acute kidney injury when patients with CHF are exposed to the CM.

Furthermore, it should be noted that older age and increased prevalences of hypertension, DM, and 3-VD were present in subjects with diastolic dysfunction (Table 2). These comorbidities are well-proven risk factors, and may potentiate the relationship between diastolic dysfunction and CIN. In DM, advanced glycation endproduct (AGE) mediates the crosslinking of collagen fibres in the myocardium [31]. It also causes an inflammation in the renal vascular system after binding to the receptor of AGE (RAGE), through activation of NADPH oxidase, MAP kinase, and the NF-κB pathway [32, 33]. Because insulin and c-peptide are known to evoke the overexpression of inducible endothelial NO synthase, impaired pancreatic secretion is also expected to increase E/E’ and exacerbate renal hemodynamics [34, 35]. Actually, several studies demonstrated an improved ejection fraction/ diastolic function after correcting for these metabolic abnormalities in diabetic CKD patients with a kidney-pancreas co-transplantation [36, 37]. Underlying hypertension and CKD also strengthen the linkage between diastolic dysfunction and CIN through the effects of uremic toxin [38, 39], pressure overload, RAAS activation, and markedly elevated expression of humoral mediators such as catecholamines, endothelin, and parathyroid hormone [40].

There are several shortcomings to our study. Because this was a retrospective study, limited data were available, which may have affected the conclusion by type II error. Second, as estimating LVEDP during the PTCA was not a routine practice in our institute, LVEDP and their relationships with E/E’ and CIN could not be presented. However, in other small cohort of 55 patients who measured LVEDP during the PTCA in our hospital, E/E’ levels were well correlated with LVEDP (r = 0.78, p < 0.001). The ROC analysis demonstrated that the predictive accuracy of E/E’ for LVEDP > 15mmHg was 0.88 (p < 0.001, 95% CI 0.794-0.981). E/E’ > 15 had 81% sensitivity and 86% specificity for LVEDP > 15 mmHg (see Additional file 5). These results correspond closely with previous studies by Sohn et al. and Ommen et al. [1113]. Moreover, E/E’ can be measured non-invasively prior to PTCA, and warns the physicians to estimate LVEDP during procedure and to monitor patients’ renal function carefully after procedure, in advance, when levels are elevated. Third, as only patients who were suspected to have CAOD and had undergone an echocardiography were included, selection bias may have existed. Higher incidence rate of CIN in our study group compared to that in previous studies conducted in the general population supports this [1]. However, considering that interventional procedures using intravascular CM are most closely related with the development of CIN, and most patients requiring such procedures have underlying cardiac disease and DM, the results of present study can be applied to the high-risk patients planning for the angioplasty. The uncontrolled use of medications with vasomotor action or that modulate the neurohumoral axis is another limitation. However, former clinical trials using RAAS blockade, statins, calcium channel blockers, beta-blockers, and diuretics failed to derive a common consensus as to their effects on CIN [4143]. Lastly, as it was a single-center study, further large-scale, randomized controlled multicenter trials are needed to confirm and assess the clinical applicability of our findings.

Conclusions

In conclusion, we demonstrated that, among echocardiographic parameters, E/E’ can be a useful predictor for the development of CIN. To our knowledge, this is the first study suggesting that assessment of diastolic dysfunction should play a role in the risk stratification for CIN.

Abbreviations

AGE: 

Advanced glycation endproduct

AKIN: 

Acute Kidney Injury Network

ANP: 

Atrial natriuretic peptide

ASE: 

American Society of Echocardiography

AUC: 

Area under the curve

BMI: 

Body mass index

CAOD: 

Coronary artery occlusive disease

CHF: 

Congestive heart failure

CI: 

Confidence interval

CIN: 

Contrast-induced nephropathy

CKD: 

Chronic kidney disease

CM: 

Contrast media

DT: 

Deceleration time

EF: 

Ejection fraction

eGFR: 

Estimated glomerular filtration rate

Hs-CRP: 

High-sensitivity C-reactive protein

IABP: 

Intra-aortic balloon pump

IVS: 

Interventricular septal thickness

LAVI: 

Left atrial volume index

LVDd: 

Left ventricular end-diastolic dimension

LVDs: 

Left ventricular end-systolic dimension

LVEDP: 

Left ventricular end-diastolic pressure

LVM: 

Left ventricular mass

LVMI: 

Left ventricular mass index

MDRD: 

Modification of Diet in Renal Disease

NO: 

Nitric oxide

NYHA: 

New York Heart Association

OR: 

Odds ratio

PTCA: 

Percutaneous transluminal coronary angioplasty

PWT: 

Posterior wall thickness

RAAS: 

Renin-angiotensin-aldosterone system

ROC: 

Receiver operating characteristic

3-VD: 

Three-vessel coronary artery disease.

Declarations

Authors’ Affiliations

(1)
Department of Internal Medicine, College of Medicine, Yonsei University

References

  1. Goldfarb S, McCullough PA, McDermott J, Gay SB: Contrast-induced acute kidney injury: specialty-specific protocols for interventional radiology, diagnostic computed tomography radiology, and interventional cardiology. Mayo Clin Proc Mayo Clin. 2009, 84: 170-179.View ArticlePubMedGoogle Scholar
  2. Finn WF: The clinical and renal consequences of contrast-induced nephropathy. Nephrol, Dial, Transplantat. 2006, 21: i2-10.View ArticleGoogle Scholar
  3. McCullough PA: Contrast-induced acute kidney injury. J Am Coll Cardiol. 2008, 51: 1419-1428.View ArticlePubMedGoogle Scholar
  4. Bartholomew BA, Harjai KJ, Dukkipati S, Boura JA, Yerkey MW, Glazier S, Grines CL, O'Neill WW: Impact of nephropathy after percutaneous coronary intervention and a method for risk stratification. Am J Cardiol. 2004, 93: 1515-1519.View ArticlePubMedGoogle Scholar
  5. Goldenberg I, Matetzky S: CMAJ: Can Med Assoc J = Journal de l'Association Medicale Canadienne. 2005, 172: 1461-1471.View ArticleGoogle Scholar
  6. Mehran R, Nikolsky E: Contrast-induced nephropathy: definition, epidemiology, and patients at risk. Kidney Int Suppl. 2006, 100: 11-15.View ArticleGoogle Scholar
  7. Rosenstock JL, Gilles E, Geller AB, Panagopoulos G, Mathew S, Malieckal D, DeVita MV, Michelis MF: Impact of heart failure on the incidence of contrast-induced nephropathy in patients with chronic kidney disease. Int Urol Nephrol. 2010, 42: 1049-1054.View ArticlePubMedGoogle Scholar
  8. Nikolsky E, Mehran R, Turcot D, Aymong ED, Mintz GS, Lasic Z, Lansky AJ, Tsounias E, Moses JW, Stone GW, et al: Impact of chronic kidney disease on prognosis of patients with diabetes mellitus treated with percutaneous coronary intervention. Am J Cardiol. 2004, 94: 300-305.View ArticlePubMedGoogle Scholar
  9. Pannu N, Wiebe N, Tonelli M: Prophylaxis strategies for contrast-induced nephropathy. JAMA. 2006, 295: 2765-2779.View ArticlePubMedGoogle Scholar
  10. Barrett BJ, Parfrey PS: Clinical practice. Preventing nephropathy induced by contrast medium. New Engl J Med. 2006, 354: 379-386.View ArticlePubMedGoogle Scholar
  11. Nagueh SF, Appleton CP, Gillebert TC, Marino PN, Oh JK, Smiseth OA, Waggoner AD, Flachskampf FA, Pellikka PA, Evangelisa A: Recommendations for the evaluation of left ventricular diastolic function by echocardiography. Eur J Echocardiogr. 2009, 10: 165-193.View ArticlePubMedGoogle Scholar
  12. Ommen SR, Nishimura RA, Appleton CP, Miller FA, Oh JK, Redfield MM, Tajik AJ: Clinical utility of Doppler echocardiography and tissue Doppler imaging in the estimation of left ventricular filling pressures: A comparative simultaneous Doppler-catheterization study. Circulation. 2000, 102: 1788-1794.View ArticlePubMedGoogle Scholar
  13. Sohn DW, Song JM, Zo JH, Chai IH, Kim HS, Chun HG, Kim HC: Mitral annulus velocity in the evaluation of left ventricular diastolic function in atrial fibrillation. J Am Soc Echocardiogr. 1999, 12: 927-931.View ArticlePubMedGoogle Scholar
  14. Mehran R, Aymong ED, Nikolsky E, Lasic Z, Iakovou I, Fahy M, Mintz GS, Lansky AJ, Moses JW, Stone GW, et al: A simple risk score for prediction of contrast-induced nephropathy after percutaneous coronary intervention: development and initial validation. J Am Coll Cardiol. 2004, 44: 1393-1399.PubMedGoogle Scholar
  15. Mehta RL, Kellum JA, Shah SV, Molitoris BA, Ronco C, Warnock DG, Levin A: Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care. 2007, 11: R31-View ArticlePubMedPubMed CentralGoogle Scholar
  16. Levey AS, Bosch JP, Lewis JB, Greene T, Rogers N, Roth D: A more accurate method to estimate glomerular filtration rate from serum creatinine: a new prediction equation. Modification of Diet in Renal Disease Study Group. Ann Intern Med. 1999, 130: 461-470.View ArticlePubMedGoogle Scholar
  17. Devereux RB, Alonso DR, Lutas EM, Gottlieb GJ, Campo E, Sachs I, Reichek N: Echocardiographic assessment of left ventricular hypertrophy: comparison to necropsy findings. Am J Cardiol. 1986, 57: 450-458.View ArticlePubMedGoogle Scholar
  18. Tumlin J, Stacul F, Adam A, Becker CR, Davidson C, Lameire N, McCullough PA: Pathophysiology of contrast-induced nephropathy. Am J Cardiol. 2006, 98: 14K-20K.View ArticlePubMedGoogle Scholar
  19. Dangas G, Iakovou I, Nikolsky E, Aymong ED, Mintz GS, Kipshidze NN, Lansky AJ, Moussa I, Stone GW, Moses JW, et al: Contrast-induced nephropathy after percutaneous coronary interventions in relation to chronic kidney disease and hemodynamic variables. Am J Cardiol. 2005, 95: 13-19.View ArticlePubMedGoogle Scholar
  20. Heyman SN, Rosenberger C, Rosen S: Regional alterations in renal haemodynamics and oxygenation: a role in contrast medium-induced nephropathy. Nephrol, Dial, Transplant. 2005, 20 (Suppl 1): i6-11.View ArticleGoogle Scholar
  21. Gami AS, Garovic VD: Contrast nephropathy after coronary angiography. Mayo Clin Proc Mayo Clin. 2004, 79: 211-219.View ArticlePubMedGoogle Scholar
  22. Victor BM, Barron JT: Diastolic heart failure versus diastolic dysfunction: difference in renal function. Clin Cardiol. 2010, 33: 770-774.View ArticlePubMedGoogle Scholar
  23. de Sa DD C, Hodge DO, Slusser JP, Redfield MM, Simari RD, Burnett JC, Chen HH: Progression of preclinical diastolic dysfunction to the development of symptoms. Heart. 2010, 96: 528-532.View ArticleGoogle Scholar
  24. Borlaug BA, Olson TP, Lam CS, Flood KS, Lerman A, Johnson BD, Redfield MM: Global cardiovascular reserve dysfunction in heart failure with preserved ejection fraction. J Am Coll Cardiol. 2010, 56: 845-854.View ArticlePubMedPubMed CentralGoogle Scholar
  25. Borlaug BA, Paulus WJ: Heart failure with preserved ejection fraction: pathophysiology, diagnosis, and treatment. Eur Heart J. 2011, 32: 670-679.View ArticlePubMedGoogle Scholar
  26. Phan TT, Abozguia K, Nallur Shivu G, Mahadevan G, Ahmed I, Williams L, Dwivedi G, Patel K, Steendijk P, Ashrafian H, et al: Heart failure with preserved ejection fraction is characterized by dynamic impairment of active relaxation and contraction of the left ventricle on exercise and associated with myocardial energy deficiency. J Am Coll Cardiol. 2009, 54: 402-409.View ArticlePubMedGoogle Scholar
  27. Afshinnia F, Spitalewitz S, Chou SY, Gunsburg DZ, Chadow HL: Left ventricular geometry and renal function in hypertensive patients with diastolic heart failure. Am J Fidney Dis. 2007, 49: 227-236.View ArticleGoogle Scholar
  28. Gajarsa JJ, Kloner RA: Left ventricular remodeling in the post-infarction heart: a review of cellular, molecular mechanisms, and therapeutic modalities. Heart Fail Rev. 2011, 16: 13-21.View ArticlePubMedGoogle Scholar
  29. Melendez GC, McLarty JL, Levick SP, Du Y, Janicki JS, Brower GL: Interleukin 6 mediates myocardial fibrosis, concentric hypertrophy, and diastolic dysfunction in rats. Hypertension. 2010, 56: 225-231.View ArticlePubMedPubMed CentralGoogle Scholar
  30. Fang D, Hawke D, Zheng Y, Xia Y, Meisenhelder J, Nika H, Mills GB, Kobayashi R, Hunter T, Lu Z: Phosphorylation of beta-catenin by AKT promotes beta-catenin transcriptional activity. J Biol Chem. 2007, 282: 11221-11229.View ArticlePubMedPubMed CentralGoogle Scholar
  31. Hartog JW, Voors AA, Bakker SJ, Smit AJ, Van Veldhuisen DJ: Advanced glycation end-products (AGEs) and heart failure: pathophysiology and clinical implications. Eur J Heart Fail. 2007, 9: 1146-1155.View ArticlePubMedGoogle Scholar
  32. Basta G, Schmidt AM, De Caterina R: Advanced glycation end products and vascular inflammation: implications for accelerated atherosclerosis in diabetes. Cardiovasc Res. 2004, 63: 582-592.View ArticlePubMedGoogle Scholar
  33. Meerwaldt R, Links T, Zeebregts C, Tio R, Hillebrands JL, Smit A: The clinical relevance of assessing advanced glycation endproducts accumulation in diabetes. Cardiovasc Diabetol. 2008, 7: 29-View ArticlePubMedPubMed CentralGoogle Scholar
  34. Kamikawa A, Ishii T, Shimada K, Makondo K, Inanami O, Sakane N, Yoshida T, Saito M, Kimura K: Proinsulin C-peptide abrogates type-1 diabetes-induced increase of renal endothelial nitric oxide synthase in rats. Diabetes Metab Res Rev. 2008, 24: 331-338.View ArticlePubMedGoogle Scholar
  35. Nordquist L, Brown R, Fasching A, Persson P, Palm F: Proinsulin C-peptide reduces diabetes-induced glomerular hyperfiltration via efferent arteriole dilation and inhibition of tubular sodium reabsorption. Am J Physiol Renal Physiol. 2009, 297: F1265-1272.View ArticlePubMedPubMed CentralGoogle Scholar
  36. Fiorina P, La Rocca E, Astorri E, Lucignani G, Rossetti C, Fazio F, Giudici D, Di Carlo V, Cristallo M, Pozza G, Secchi A: Reversal of left ventricular diastolic dysfunction after kidney-pancreas transplantation in type 1 diabetic uremic patients. Diabetes Care. 2000, 23: 1804-1810.View ArticlePubMedGoogle Scholar
  37. Perseghin G, Fiorina P, De Cobelli F, Scifo P, Esposito A, Canu T, Danna M, Gremizzi C, Secchi A, Luzi L, Del Maschio A: Cross-sectional assessment of the effect of kidney and kidney-pancreas transplantation on resting left ventricular energy metabolism in type 1 diabetic-uremic patients: a phosphorous-31 magnetic resonance spectroscopy study. J Am Coll Cardiol. 2005, 46: 1085-1092.View ArticlePubMedGoogle Scholar
  38. Stewart GA, Gansevoort RT, Mark PB, Rooney E, McDonagh TA, Dargie HJ, Stuart R, Rodger C, Jardine AG: Electrocardiographic abnormalities and uremic cardiomyopathy. Kidney Int. 2005, 67: 217-226.View ArticlePubMedGoogle Scholar
  39. Lekawanvijit S, Adrahtas A, Kelly DJ, Kompa AR, Wang BH, Krum H: Does indoxyl sulfate, a uraemic toxin, have direct effects on cardiac fibroblasts and myocytes?. Eur Heart J. 2010, 31: 1771-1779.View ArticlePubMedGoogle Scholar
  40. Dickhout JG, Carlisle RE, Austin RC: Interrelationship between cardiac hypertrophy, heart failure, and chronic kidney disease: endoplasmic reticulum stress as a mediator of pathogenesis. Circ Res. 2011, 108: 629-642.View ArticlePubMedGoogle Scholar
  41. Zhang L, Lu Y, Wu B, Zhang S, Jiang H, Ge J, Chen H: Efficacy of statin pretreatment for the prevention of contrast-induced nephropathy: a meta-analysis of randomised controlled trials. Int J Clin Pract. 2011, 65: 624-630.View ArticlePubMedGoogle Scholar
  42. Gleeson TG, Bulugahapitiya S: Contrast-induced nephropathy. AJR Am J Roentgenol. 2004, 183: 1673-1689.View ArticlePubMedGoogle Scholar
  43. Kiski D, Stepper W, Brand E, Breithardt G, Reinecke H: Impact of renin-angiotensin-aldosterone blockade by angiotensin-converting enzyme inhibitors or AT-1 blockers on frequency of contrast medium-induced nephropathy: a post-hoc analysis from the Dialysis-versus-Diuresis (DVD) trial. Nephrol, Dial, Transplant. 2010, 25: 759-764.View ArticleGoogle Scholar
  44. Pre-publication history

    1. The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2369/14/146/prepub

Copyright

© Koo et al.; licensee BioMed Central Ltd. 2013

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Advertisement