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Risk of Acute Kidney Injury, Dialysis, and Mortality in Patients With Chronic Kidney Disease After Intravenous Contrast Material Exposure

Mayo Clin Proc. 2015;90(8):1046-53

Abstract

Objective

To examine the effect of intravenous iodinated contrast material administration on the subsequent development of acute kidney injury (AKI), emergent dialysis, and short-term mortality using a propensity score–adjusted analysis of computed tomographic scan recipients with chronic kidney disease (CKD).

Patients and Methods

In this institutional review board–approved retrospective study, all patients with CKD who received a contrast-enhanced (contrast group) or unenhanced (noncontrast group) computed tomographic scan from January 1, 2000, to August 1, 2013 were identified. Patients were subdivided into CKD stage III (baseline estimated glomerular filtration rate, 30-59 mL/min per 1.73 m 2 ) and CKD stage IV-V (baseline estimated glomerular filtration rate, <30 mL/min per 1.73 m 2 ) subgroups and separately underwent propensity score generation, stratification, and 1:1 matching. Rates of AKI, 30-day emergent dialysis, and mortality were compared between contrast and noncontrast groups. Sensitivity analyses examining only patients with stable prescan serum creatinine levels and incorporating intravenous fluid administration at the time of the CT scan into the model were also performed.

Results

A total of 6902 patients (4496 CKD stage III, matched: 1220 contrast and 1220 noncontrast; 2086 CKD stage IV-V, matched: 491 contrast and 491 noncontrast) were included in the study. After propensity score adjustment, rates of AKI, emergent dialysis, and mortality were not significantly higher in the contrast group than in the noncontrast group in either CKD subgroup (CKD stage III: OR, 0.65-1.00; P <.001-.99 and CKD stage IV-V: OR, 0.93-2.33; P =.22-.99). Both sensitivity analyses revealed similar results.

Conclusion

Intravenous contrast material administration was not associated with an increased risk of AKI, emergent dialysis, and short-term mortality in a cohort of patients with diminished renal function.

Abbreviations and Acronyms: AKI-acute kidney injury, AKIN-Acute Kidney Injury Network, CIN-contrast-induced nephropathy, CKD-chronic kidney disease, CT-computed tomographic, eGFR-estimated glomerular filtration rate, EMR-electronic medical record, KDOQI-Kidney Disease Outcomes Quality Initiative, -, SCr-serum creatinine.

Concern for the development of acute kidney injury (AKI) after the administration of iodinated contrast material, also known as contrast-induced nephropathy (CIN), often limits the use of contrast material in patients at risk of developing this complication. 1 2 However, recent research suggests that the incidence and severity of CIN have been overestimated by previous uncontrolled studies. 3 4 5 In these previous studies, all instances of AKI after contrast material administration were routinely ascribed to CIN, even though there are myriad causes of AKI in hospitalized patients. Controlled studies with clinically similar patients who did not receive contrast material are essential to help differentiate true CIN from contrast-independent AKI.

Two recent large retrospective studies by Davenport et al 6 and McDonald et al 7 used propensity score matching to compare contrast-enhanced computed tomographic (CT) scan recipients and clinically similar patients who underwent an unenhanced CT scan. Both studies found that the rate of AKI was similar between contrast recipients and control groups in patients with baseline estimated glomerular filtration rate (eGFR) greater than 30 mL/min per 1.73 m 2 , providing evidence that CIN may not be a clinical concern in these patients. However, disparate results were reported for patients with baseline eGFR less than 30 mL/min per 1.73 m 2 , with the study by McDonald et al reporting similar rates of AKI between the 2 groups and the study by Davenport et al reporting significantly higher rates of AKI in contrast recipients ( P <.05), suggestive of CIN. Several potential explanations for these dissimilar results have been postulated, including differences in clinical covariates included in the studies’ propensity score models, differences in the clinical and demographic characteristics of the patient populations, and whether the study included or excluded patients with unstable serum creatinine (SCr) before their CT scan. 8 9

The objectives of the present study were to perform a more rigorous propensity score analysis of CT scan recipients with renal insufficiency (eGFR, <60 mL/min per 1.73 m 2 ) and to determine the risk of AKI, emergent dialysis, and mortality after exposure to intravenous contrast material.

Patients and Methods

Study Design and Clinical Data Retrieval

Design and execution of this single-center retrospective study were subject to institutional review board oversight and Health Insurance Portability and Accountability Act privacy guidelines. The need for informed consent was waived. All clinical data were extracted from our electronic medical record (EMR) using a combination of relational database software (DDQB, IBM Corp) and manual chart review. Additional details of data retrieval and analysis are provided in the Supplemental Appendix (available online at http://www.mayoclinicproceedings.org ).

Inclusion and Exclusion Criteria

Many patients in the present study were included in previous publications that examined the incidence of AKI, emergent dialysis, and mortality in patients who received a contrast-enhanced or unenhanced CT scan. 7 10 11 We wanted to improve on these previous studies by (1) including a more comprehensive list of clinical variables related to renal insufficiency in the propensity score model to reduce confounding and better match contrast recipients and control patients; (2) performing a full chart review of the patient’s record to confirm comorbidities and medical conditions instead of relying on International Classification of Diseases, Ninth Revision ( ICD-9 ) diagnostic codes, which have been shown to be inaccurate in some cases; 12 13 14 and (3) including CT scans performed through July 2013 to better reflect current clinical practices.

Adult patients (18 years or older) were included in the present study if they (1) received an unenhanced (noncontrast group) or intravenous contrast-enhanced (contrast group) abdominal, pelvic, and thoracic CT scans from January 2000 to August 2013 at our institution; (2) had at least 2 prescan (in 24 hours before the scan) SCr results and at least 1 postscan (24-72 hours after the scan) SCr result; and (3) had a baseline eGFR of less than 60 mL/min per 1.73 m 2 at the time of the CT scan, as calculated below. Patients were excluded if they (1) had preexisting renal dialysis requirements; (2) did not have the pre- and postscan SCr results, as described above; (3) were missing any clinical variables included in the propensity score model (listed in Table 1 ); or (4) received intravenous or intra-arterial contrast material from another examination or procedure within a 14-day period of the CT scan. When a patient received multiple CT scans over the study time frame, only the last CT scan was included in the analysis to eliminate sampling bias and maximize the probability of identification of disease. Detailed information regarding inclusion and exclusion criteria is given in the Supplemental Appendix .

Variable c Contrast group Noncontrast group P
No. of scans 1220 1220  
1 Year of scan 2006 (2003-2010) 2006 (2003-2010) .24
2 Age (y) 75 (65-83) 75 (64-83) .74
3 Sex: female 631 (52) 605 (50) .29
4 White race 1108 (91) 1117 (92) .52
5 Admission     .48
Inpatient 658 (54) 686 (56)  
Emergency department/inpatient 377 (31) 361 (30)  
Outpatient 185 (15) 173 (14)  
6 ICU at the time of the scan 183 (15) 179 (15) .82
Preexisting comorbidities      
7 Diabetes mellitus 257 (21) 279 (23) .26
8 Diabetic nephropathy 40 (3.3) 42 (3.4) .82
9 Hypertension 538 (44) 567 (46) .19
10 Chronic kidney disease 371 (30) 408 (33) .08
11 Multiple myeloma 10 (0.8) 10 (0.8) .99
12 Congestive heart failure 247 (20) 261 (21) .46
13 Charlson comorbidity score 3 (1-6) 3 (2-6) .23
Conditions within 7 d of the scan      
14 AKI 115 (9.4) 120 (9.8) .72
15 Renal stone 37 (3.0) 49 (4.0) .18
16 Sepsis 56 (4.6) 59 (4.8) .77
17 Major surgery 273 (22) 246 (20) .17
Prescribed nephrotoxic medication at the time of the scan
18 Antibiotics other than vancomycin 104 (8.5) 104 (8.5) .99
19 Vancomycin 138 (11) 144 (12) .69
20 ACE inhibitors 289 (24) 295 (24) .77
21 ARBs 112 (9.2) 116 (9.5) .78
22 Chemotherapeutics 18 (1.5) 18 (1.5) .99
23 Cyclooxygenase 2 inhibitors 31 (2.5) 23 (1.9) .27
24 Loop diuretics 382 (31) 393 (32) .63
25 Hydrochlorothiazide 154 (13) 126 (10) .07
26 Immunosuppressants other than sirolimus 35 (2.9) 36 (3.0) .90
27 Sirolimus 1 (0.1) 1 (0.1) .99
28 NSAIDs 53 (4.3) 55 (4.5) .85
29 Statins 381 (31) 386 (32) .83
30 Baseline eGFR 47 (40-52) 46 (39-52) .07
31 SCr stability before the scan     .94
Stable 1083 (89) 1088 (89)  
Unstable—increasing 83 (6.8) 81 (6.6)  
Unstable—decreasing 54 (4.4) 51 (4.2)  
32 ΔSCr (SCR max -SCr min ) 0.2 (0.1-0.3) 0.2 (0.1-0.3) .71

a ACE = angiotensin-converting enzyme; AKI = acute kidney injury; ARB = angiotensin II receptor blocker; CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; ICU = intensive care unit; NSAID = nonsteroidal anti-inflammatory drug; SCr = serum creatinine.

b Data are presented as median (interquartile range) and No. (percentage) of patients unless otherwise indicated.

c Numbered variables were used to generate the propensity score model.

Table 1Demographic Characteristics of Matched CKD Stage III Cohort a , b

 

Baseline Renal Function

All SCr data associated with each CT scan record were extracted from the EMR and temporally sorted with respect to the date of the scan. Baseline eGFR was calculated for each patient from the SCr result(s) 24 hours before the CT scan using the Modification of Diet in Renal Disease equation based on the National Kidney Foundation Kidney Disease Outcomes Quality Initiative (KDOQI) recommendations, as described previously. 7 Patients were stratified by baseline eGFR into 30 to 59 mL/min per 1.73 m 2 (CKD stage III) and less than 30 mL/min per 1.73 m 2 (CKD stage IV-V) subgroups to mirror the KDOQI classification of chronic kidney disease (CKD). 15

Outcome Variables

The outcomes examined in this study were AKI, emergent dialysis, and mortality after the CT scan. Acute kidney injury was defined as an increase in maximal increase in observed SCr level of either (1) 0.5 mg/dL or more (standard AKI criteria) or (2) 0.3 mg/dL or more or 50% or more over baseline SCr level (Acute Kidney Injury Network [AKIN] criteria) in the 24 to 72 hours after the CT scan (to convert mg/dL to mmol/L, multiply by 0.0259). The former cutoff was chosen to maintain consistency with previous studies that used this definition of AKI, whereas the latter was chosen to reflect the more recent recommendations of the AKIN. 16 Cases of emergent dialysis (defined as dialysis performed in a patient who did not previously require dialysis) and death within 30 days of the CT scan were identified as described previously. 11

Propensity Score Analysis

Propensity score generation, stratification, and matching for patients in the contrast and noncontrast groups were performed using the R package MatchIt, as described previously. 10 Logistic regression models with 32 clinical variables numbered in Table 1 were separately created for the CKD stage III and IV-V subgroups. The relative influence of propensity score model covariates was determined using the R package TWANG. 17

Sensitivity Analyses of Prescan SCr Stability and Intravenous Fluid Administration

Two sensitivity analyses were performed to strengthen the confidence of our findings. In the first analysis, only patients with stable baseline renal function , defined as changes in prescan SCr level of less than 0.5 mg/dL ( Supplemental Appendix ), were subjected to stratification and matching by propensity score, as described above. This subgroup was created to remove patients with wide variability in renal function and/or undetected AKI before contrast material exposure that could potentially confound the results. In the second analysis, the amount of intravenous fluids administered to patients in the 24 hours before their CT scan was included as a covariate in the propensity score model. Only CT scans performed after December 2003 at our institution had intravenous fluid data entered into the EMR and therefore were included in this analysis. The amounts of intravenous fluids administered on the day of the CT scan and 24 hours after the CT scan were not included as covariates because they occurred after the decision to administer contrast material and therefore could potentially confound the results. These 2 post hoc covariates were instead added as adjustment covariates to a conditional logistic regression model after matching with prescan intravenous fluids and other covariates listed in Table 1 .

Statistical Analyses

Statistical analyses were performed using the R computing program (version 3.0.3). 18 Dichotomous variables were displayed as counts with percentages, categorical data were displayed as relative frequencies (%), and continuous data were presented as medians with interquartile ranges. Differences in clinical characteristics and rates of AKI, emergent dialysis, and mortality between the contrast and noncontrast groups before matching were assessed using the Wilcoxon rank sum test for continuous clinical characteristics and using the Fisher exact test or Pearson chi-square test for categorical clinical characteristics and outcomes. The collective risk of AKI, emergent dialysis, and mortality after stratification by propensity score was assessed using Cochran-Mantel-Haenszel estimates. Differences in clinical characteristics and rates of AKI, emergent dialysis, and mortality after 1:1 matching were measured using conditional logistic regression, conditioned on the unique ID assigned to each match.

Results

Study Population and Propensity Score Adjustment

A total of 6902 CT scan records (4496 CKD stage III and 2086 CKD stage IV-V) met all study inclusion criteria ( Supplemental Tables 3 and 4 , available online at http://www.mayoclinicproceedings.org ). Before propensity score adjustment, patients in the contrast and noncontrast groups had significant differences in numerous clinical variables ( P =.03-<.001), including baseline renal function, acute and chronic comorbidities, and medication use.

Propensity score distributions for both CKD subgroups are shown in Supplemental Figure 1 (available online at http://www.mayoclinicproceedings.org ). The relative influence of all covariates on the propensity score model for each CKD subgroup is shown in Supplemental Figure 2 (available online at http://www.mayoclinicproceedings.org ). The 5 most influential covariates for the CKD stage III subgroup were baseline eGFR, preexisting hypertension, age, admit type, and sex. The 5 most influential covariates for the CKD stage IV-V subgroup were baseline eGFR, preexisting CKD, prescan SCr stability, year of scan, and age.

In all study patients, the stratification of the propensity score into deciles eliminated all significant differences in all covariates between the contrast and noncontrast groups in both CKD subgroups ( Supplemental Tables 3 and 4 ). One-to-one matching based on the propensity score yielded a smaller, more rigorously matched cohort of 2440 CT scan recipients for the CKD stage III subgroup (1220 contrast and 1220 noncontrast) and a cohort of 982 matched CT scan recipients for the CKD stage IV-V subgroup (491 contrast and 491 noncontrast) ( Tables 1 and 2 ). This matching also eliminated all significant differences in all covariates between the contrast and noncontrast groups in both CKD subgroups.

Variable Contrast group Noncontrast group P
No. of scans 419 419  
Year of scan 2006 (2003-2008) 2006 (2002-2009) .82
Age (y) 70 (61-79) 71 (60-80) .93
Sex: female 270 (64) 278 (66) .54
White race 405 (97) 409 (98) .40
Year scan performed      
Admission     .38
Inpatient 347 (83) 347 (83)  
Emergency department/inpatient 52 (12) 59 (14)  
Outpatient 20 (4.8) 13 (3.1)  
ICU at the time of the scan 77 (18) 77 (18) .99
Preexisting comorbidities      
Diabetes mellitus 155 (37) 158 (38) .83
Diabetic nephropathy 21 (5.0) 25 (6.0) .56
Hypertension 341 (81) 342 (82) .93
Chronic kidney disease 201 (48) 203 (48) .87
Multiple myeloma 7 (1.7) 9 (2.2) .62
Congestive heart failure 138 (33) 152 (36) .30
Charlson comorbidity score 4 (2-8) 4 (2-8) .67
Conditions within 7 d of the scan      
AKI 252 (60) 260 (62) .54
Renal stone 7 (1.7) 7 (1.7) .99
Sepsis 57 (14) 61 (15) .69
Major surgery 58 (14) 63 (15) .62
Prescribed nephrotoxic/nephromodulatory medication at the time of the scan
Antibiotics other than vancomycin 49 (12) 60 (14) .24
Vancomycin 64 (15) 64 (15) .99
ACE inhibitors 132 (32) 136 (32) .76
ARBs 62 (15) 54 (13) .43
Chemotherapeutics 5 (1.2) 3 (0.7) .48
Cyclooxygenase 2 inhibitors 15 (3.6) 18 (4.3) .59
Loop diuretics 209 (50) 227 (54) .20
Hydrochlorothiazide 66 (16) 62 (15) .71
Immunosuppressants other than sirolimus 32 (7.6) 38 (9.1) .47
Sirolimus 5 (1.2) 7 (1.7) .57
NSAIDs 28 (6.7) 30 (7.2) .78
Statins 157 (37) 156 (37) .94
Baseline eGFR 24 (20-27) 24 (20-27) .87
SCr stability before the scan     .84
Stable 251 (60) 245 (58)  
Unstable—increasing 49 (12) 54 (13)  
Unstable—decreasing 119 (28) 120 (29)  
ΔSCr (SCR max -SCr min ) 0.3 (0.2-0.8) 0.4 (0.2-0.7) .60

a ACE = angiotensin-converting enzyme; AKI = acute kidney injury; ARB = angiotensin II receptor blocker; CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; ICU = intensive care unit; NSAID = nonsteroidal anti-inflammatory drug; SCr = serum creatinine.

b Data are presented as median (interquartile range) and No. (percentage) of patients unless otherwise indicated.

Table 2Demographic Characteristics of Matched CKD Stage IV-V Cohort a , b

 

Propensity Score–Adjusted Outcome Rates

Patient outcomes after stratification and matching by propensity score are summarized in Tables 3 and 4 . After stratification, the rate of AKI was not significantly higher in the contrast group compared with the noncontrast group in either the CKD subgroup (CKD stage III: AKIN criteria, P ≤.001; standard AKI criteria, P =.29 and CKD stage IV-V: AKIN criteria, P =.99; standard AKI criteria, P =.90). A similar pattern was observed after propensity score matching (CKD stage III: AKIN criteria, P <.001; standard AKI criteria, P =.38 and CKD stage IV-V: AKIN criteria, P =.47; standard AKI criteria, P =.92). The use of emergent dialysis was rare and not significantly different between the contrast and noncontrast groups in either CKD subgroup after stratification (CKD stage III: P =.62; CKD stage IV-V: P =.31) or matching (CKD stage III: P =.99; CKD stage IV-V: P =.22). The rate of mortality was also not significantly different between the contrast and noncontrast groups in either CKD subgroup after stratification (CKD stage III: P =.25; CKD stage IV-V: P =.89) or matching (CKD stage III: P =.06; CKD stage IV-V: P =.71).

Variable Contrast group Noncontrast group Odds ratio (95% CI) c P
Stratified analysis: no. of patients 2310 2186    
AKI d        
AKIN criteria 229 (9.9) 360 (16) 0.68 (0.55-0.84) <.001
Standard criteria 102 (4.4) 157 (7.2) 0.84 (0.63-1.14) .29
Dialysis within 30 d of the scan 5 (0.2) 26 (1.2) 0.69 (0.25-1.93) .62
Death within 30 d of the scan 177 (7.7) 275 (13) 0.86 (0.68-1.09) .25
1:1 matched analysis: no. of patients 1220 1220    
AKI d        
AKIN criteria 126 (10) 185(15) 0.65 (0.41-0.89) <.001
Standard criteria 61 (5.0) 71 (5.8) 0.86 (0.51-1.20) .38
Dialysis within 30 d of the scan 5 (0.4) 5 (0.4) 1.00 (0.24-2.24) .99
Death within 30 d of the scan 109 (8.9) 137 (11) 0.77 (0.50-1.04) .06

a AKI = acute kidney injury; AKIN = Acute Kidney Injury Network; CKD = chronic kidney disease; SCr = serum creatinine.

b Data are presented as No. (percentage) of patients unless otherwise indicated.

c Odds of contrast group vs noncontrast group.

d AKIN criteria defined as ≥0.3 mg/dL or 50% or more over baseline SCr; standard criteria defined as ≥0.5 mg/dL over baseline SCr. To convert mg/dL to mmol/L, multiply by 0.0259.

Table 3CKD Stage III Cohort Outcomes After Propensity Score Analysis a , b

Variable Contrast group Noncontrast group Odds ratio (95% CI) c P
Stratified analysis: no. of patients 474 1612    
AKI d        
AKIN criteria 94 (20) 458 (28) 1.01 (0.77-1.33) .99
Standard criteria 65 (14) 361 (22) 0.90 (0.66-1.24) .90
Dialysis within 30 d of the scan 7 (1.5) 28 (1.7) 1.83 (0.73-4.55) .31
Death within 30 d of the scan 84 (18) 266 (17) 1.03 (0.77-1.38) .89
1:1 matched analysis: no. of patients 419 419    
AKI d        
AKIN criteria 89 (21) 81 (20) 1.14 (0.78-1.50) .47
Standard criteria 62 (15) 61 (15) 1.02 (0.63-1.41) .92
Dialysis within 30 d of the scan 7 (1.7) 3 (0.7) 2.33 (0.98-3.68) .22
Death within 30 d of the scan 77 (18) 81 (19) 0.93 (0.57-1.29) .71

a AKI = acute kidney injury; AKIN = Acute Kidney Injury Network; CKD = chronic kidney disease; SCr = serum creatinine.

b Data are presented as No. (percentage) of patients unless otherwise indicated.

c Odds of contrast group vs noncontrast group.

d AKIN criteria defined as ≥0.3 mg/dL or 50% or more over baseline SCr, standard criteria defined as ≥0.5 mg/dL over baseline SCr. To convert mg/dL to mmol/L, multiply by 0.0259.

Table 4CKD Stage IV-V Cohort Outcomes After Propensity Score Analysis a , b

 

Sensitivity Analysis: Adjusted Outcome Rates in Patients With Stable Prescan SCr

Propensity score matching after excluding any patients who had widely fluctuating SCr results (ΔSCr ≥0.5 mg/dL) before their CT scan yielded a cohort of 2146 matched CT scan recipients for the CKD stage III subgroup (1073 contrast and 1073 noncontrast) and a cohort of 496 matched CT scan recipients for the CKD stage IV-V subgroup (248 contrast and 248 noncontrast) ( Supplemental Tables 5 and 6 , available online at http://www.mayoclinicproceedings.org ). After matching, there were no significant differences in any covariates between the contrast and noncontrast groups in both CKD subgroups. Rates of AKI, emergent dialysis, and mortality were again not significantly higher in the contrast group than in the noncontrast group in either CKD subgroup, regardless of AKI criteria or whether patients were stratified or matched by propensity score ( Supplemental Tables 7 and 8 , available online at http://www.mayoclinicproceedings.org ).

Sensitivity Analysis: Adjusted Outcome Rates Including Intravenous Fluid Administration in the Propensity Score Model

Incorporation of intravenous fluids administered in the 24 hours before the CT scan in the propensity score model yielded a cohort of 1734 matched CT scan recipients for the CKD stage III subgroup (867 contrast recipients and 867 noncontrast recipients) and a cohort of 572 matched CT scan recipients for the CKD stage IV-V subgroup (286 contrast recipients and 286 noncontrast recipients) ( Supplemental Tables 9 and 10 , available online at http://www.mayoclinicproceedings.org ). After matching, there were no significant differences in clinical covariates between the contrast and noncontrast groups in either CKD subgroup. Rates of AKI, emergent dialysis, and mortality were again not significantly higher in the contrast group than in the noncontrast group in either CKD subgroup, after incorporating prescan intravenous fluid administration, regardless of AKI criteria or whether patients were stratified or matched by propensity score ( Supplemental Tables 11 and 12 , available online at http://www.mayoclinicproceedings.org ).

The administration of intravenous fluids on the day of the CT scan or the day after the scan was not included in the propensity score model, because only covariates that are present at the time of treatment can be included. In the matched CKD stage III subgroup, contrast recipients received significantly more fluids on the day of the scan than did patients in the noncontrast group ( P =.04) ( Supplemental Table 9 ). In the matched CKD stage IV-V subgroup, contrast recipients and patients in the noncontrast group had similar likelihoods of receiving fluids on the day of the CT scan and the day after the scan and received similar amount of fluids ( Supplemental Table 10 ). In patients with similar intravenous fluid administration, AKI, dialysis, and mortality rates were again not significantly higher in the contrast group than in the noncontrast group ( Supplemental Tables 13 and 14 , available online at http://www.mayoclinicproceedings.org ).

Discussion

This large, propensity score–adjusted, retrospective study suggests that intravenous contrast material administration for CT scanning is not associated with an increased risk of AKI in a cohort of patients with renal insufficiency. These results were observed regardless of propensity score adjustment method, AKI cutoff, or subgroup analysis. These findings provide more robust further evidence that the risk of CIN is extremely low in most patients undergoing CT scanning.

Our findings corroborate previous propensity score studies that also found similar rates of AKI, emergent dialysis, and short-term mortality between contrast-enhanced and unenhanced CT scan recipients, even in patients with renal insufficiency. 7 10 11 19 Our present study builds on these findings in multiple ways. First, our study included almost all the reported risk factors for AKI into the propensity score model, including use of potentially nephrotoxic medications, the presence of associated chronic or acute conditions, and the presence of stable or unstable renal function at the time of the CT scan. Second, we performed manual chart review to validate model covariates instead of relying on automated retrievals of ICD-9 diagnostic codes, which are known to be less accurate. 12 13 14 Third, we accounted for intravenous fluid administration data in our analysis to better characterize patients in terms of hydration status. Other AKI prophylactic measures, including N -acetylcysteine and sodium bicarbonate, were not included in the model because there is insufficient evidence of their efficacy. 1 20 21 22

We found a significantly lower risk of AKI in stage III contrast recipients than in propensity score–stratified or –matched control patients if a cutoff of 0.3 mg/dL or more or 50% or more over baseline SCr was used to define AKI. There are several potential reasons for this observation. One possibility is that the control patients in this cohort more frequently had minor variability in SCr after the CT scan as compared with contrast recipients, and this variability could have been interpreted as AKI. Another possibility is that an unmeasured confounder remains in this cohort after propensity score adjustment that results in a higher rate of AKI in the control group. Slightly lower risks of AKI when defined by a cutoff of 0.5 mg/dL or more over baseline SCr, emergent dialysis, and mortality were also observed in stage III contrast recipients than in control patients, supporting this hypothesis.

A previous study by Davenport et al 6 reported a significantly higher rate of AKI in patients with eGFR less than 30 mL/min per 1.73 m 2 who received intravenous contrast material than in a propensity score–matched control group. Our findings suggest that patients with eGFR less than 30 mL/min per 1.73 m 2 were not at increased risk of CIN. There are several possible reasons for this discrepancy. First, a more comprehensive list of clinical covariates was used in our propensity score models and different methods were used to retrieve covariates from the medical record (ie, automated ICD-9 diagnostic code retrieval vs manual chart review). Second, Davenport et al created 1 propensity score model for all patients, whereas our study created separate models for the CKD stage III and IV-V subgroups. We believe that these 2 groups represent different patient populations that require separate propensity score models, a hypothesis strengthened by our finding that different clinical covariates have different relative influences on the propensity scores of the 2 subgroups. Finally, the discrepancy between study findings may reflect differences in patient populations or clinical practices. Additional prospective and large sample size retrospective studies are needed, particularly those that examine AKI sequelae including dialysis and death, to determine the safety of intravenous contrast material in patients with severe renal insufficiency.

Our study has several limitations. First, retrospective statistical methods including propensity score adjustment can only account for measured confounders. To our knowledge, our propensity score model with 32 clinical covariates is the most robust model to date. This expanded model had results similar to the results of our previous propensity score study with fewer covariates. However, unmeasured confounders may still remain in our present study that could affect patient outcomes. Second, because we could only examine patients with sufficient pre- and postscan SCr results, we were limited to a predominantly inpatient cohort. However, this bias favorably enriches the number of inpatients in our study population, increasing the probability of observing AKI in a more acutely ill population as compared with outpatients. Third, we were unable to determine whether contrast osmolality affected differences in outcomes because only a small percentage of patients in our cohort (6% of patients with stage III CKD and 17% of patients with stage IV-V CKD) received iso-osmolar contrast material. Fourth, although we used KDOQI CKD stage cutoffs to stratify patients by eGFR, a percentage of patients were likely assigned to these subgroups because of acute or subacute changes in renal function instead of the presence of true CKD. Finally, although prospective randomized controlled trials of CIN are the best way to determine causality, such trials are ethically challenging and require large sample sizes to be sufficiently powered to examine rare outcomes such as emergent dialysis. Additional observational studies incorporating different clinical covariates, patient populations, and clinical practices are needed to confirm the true risk of CIN.

Conclusion

Our findings provide additional evidence that the administration of intravenous contrast material does not increase the risk of AKI, emergent dialysis, and mortality, even in patients with substantially compromised renal function.

Supplemental Online Material

Supplemental Material Video 1

Supplemental Online Material

Supplemental material can be found online at http://www.mayoclinicproceedings.org . Supplemental material attached to journal articles has not been edited, and the authors take responsibility for the accuracy of all data.

Grant Support: The work was supported by the National Institute of Diabetes and Digestive and Kidney Diseases of the National Institutes of Health under award number K01DK097054. The content is solely the responsibility of the authors and does not necessarily reflect the official views of the National Institutes of Health.

Potential Competing Interests: Drs Williamson and McDonald have received a research grant for Mayo Clinic from GE Healthcare, a manufacturer of the contrast agents studied in this article. The grant did not cover any part of the present study and is not currently active. Dr Kalmes participates on the Cost Effectiveness Board at GE Healthcare, unrelated to contrast nephropathy.

References

  • 1 ACR manual on contrast media. Version 9. American College of Radiology website. <http://www.acr.org/∼/media/ACR/Documents/PDF/QualitySafety/Resources/Contrast Manual/2013_Contrast_Media.pdf>. Accessed June 29, 2015.
  • 2 F. Stacul, A.J. van der Molen, P. Reimer, et al., Contrast Media Safety Committee of European Society of Urogenital Radiology (ESUR). Contrast induced nephropathy: updated ESUR Contrast Media Safety Committee guidelines. Eur Radiol. 2011;21(12):2527-2541
  • 3 R.W. Katzberg, R. Lamba. Contrast-induced nephropathy after intravenous administration: fact or fiction?. Radiol Clin North Am. 2009;47(5):789-800 v
  • 4 R.W. Katzberg, J.H. Newhouse. Intravenous contrast medium-induced nephrotoxicity: is the medical risk really as great as we have come to believe?. Radiology. 2010;256(1):21-28
  • 5 J.S. McDonald, R.J. McDonald, J. Comin, et al. Frequency of acute kidney injury following intravenous contrast medium administration: a systematic review and meta-analysis. Radiology. 2013;267(1):119-128
  • 6 M.S. Davenport, S. Khalatbari, R.H. Cohan, J.R. Dillman, J.D. Myles, J.H. Ellis. Contrast material-induced nephrotoxicity and intravenous low-osmolality iodinated contrast material: risk stratification by using estimated glomerular filtration rate. Radiology. 2013;268(3):719-728
  • 7 J.S. McDonald, R.J. McDonald, R.E. Carter, R.W. Katzberg, D.F. Kallmes, E.E. Williamson. Risk of intravenous contrast material-mediated acute kidney injury: a propensity score-matched study stratified by baseline-estimated glomerular filtration rate. Radiology. 2014;271(1):65-73
  • 8 M.S. Davenport, R.H. Cohan, S. Khalatbari, J.H. Ellis. The challenges in assessing contrast-induced nephropathy: where are we now?. AJR Am J Roentgenol. 2014;202(4):784-789
  • 9 J.H. Newhouse, A. RoyChoudhury. Quantitating contrast medium-induced nephropathy: controlling the controls. Radiology. 2013;267(1):4-8
  • 10 R.J. McDonald, J.S. McDonald, J.P. Bida, et al. Intravenous contrast material-induced nephropathy: causal or coincident phenomenon?. Radiology. 2013;267(1):106-118
  • 11 R.J. McDonald, J.S. McDonald, R.E. Carter, et al. Intravenous contrast material exposure is not an independent risk factor for dialysis or mortality. Radiology. 2014;273(3):714-725
  • 12 E.F. Kern, M. Maney, D.R. Miller, et al. Failure of ICD-9-CM codes to identify patients with comorbid chronic kidney disease in diabetes. Health Serv Res. 2006;41(2):564-580
  • 13 K.M. Newton, E.H. Wagner, S.D. Ramsey, et al. The use of automated data to identify complications and comorbidities of diabetes: a validation study. J Clin Epidemiol. 1999;52(3):199-207
  • 14 J.W. Peabody, J. Luck, S. Jain, D. Bertenthal, P. Glassman. Assessing the accuracy of administrative data in health information systems. Med Care. 2004;42(11):1066-1072
  • 15 National Kidney Foundation. K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis. 2002;39(2, suppl 1):S1-S266
  • 16 R.L. Mehta, J.A. Kellum, S.V. Shah, et al., Acute Kidney Injury Network. Acute Kidney Injury Network: report of an initiative to improve outcomes in acute kidney injury. Crit Care. 2007;11(2):R31
  • 17 Ridgeway G, McCaffrey DF, Morral AR, Burgette LF, Griffin BA. Toolkit for Weighting and Analysis of Nonequivalent Groups: a tutorial for the TWANG package. <http://cran.r-project.org/web/packages/twang/vignettes/twang.pdf>. Accessed June 29, 2015.
  • 18 R: A Language and Environment for Statistical Computing. (R Foundation for Statistical Computing, Vienna, Austria, 2012) [computer program]. Version 3.0.3
  • 19 S. Ehrmann, J. Badin, L. Savath, et al. Acute kidney injury in the critically ill: is iodinated contrast medium really harmful?. Crit Care Med. 2013;41(4):1017-1026
  • 20 ACT Investigators. Acetylcysteine for prevention of renal outcomes in patients undergoing coronary and peripheral vascular angiography: main results from the randomized Acetylcysteine for Contrast-induced nephropathy Trial (ACT). Circulation. 2011;124(11):1250-1259
  • 21 Z. Sun, Q. Fu, L. Cao, W. Jin, L. Cheng, Z. Li. Intravenous N-acetylcysteine for prevention of contrast-induced nephropathy: a meta-analysis of randomized, controlled trials. PloS One. 2013;8(1):e55124
  • 22 S. Zoungas, T. Ninomiya, R. Huxley, et al. Systematic review: sodium bicarbonate treatment regimens for the prevention of contrast-induced nephropathy. Ann Intern Med. 2009;151(9):631-638

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