Next Article in Journal
MR Neuroimaging in Pediatric Inborn Errors of Metabolism
Previous Article in Journal
De-Speckling Breast Cancer Ultrasound Images Using a Rotationally Invariant Block Matching Based Non-Local Means (RIBM-NLM) Method
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Diagnostics
Volume 12
Issue 4
10.3390/diagnostics12040864
diagnostics-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Patients with Different Stages of Chronic Kidney Disease Undergoing Intravenous Contrast-Enhanced Computed Tomography—The Incidence of Contrast-Associated Acute Kidney Injury

by
Ming-Ju Wu
1,2,3,4,5 and
Shang-Feng Tsai
1,5,6,7,*
1
Division of Nephrology, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung 407, Taiwan
2
School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
3
Rong Hsing Research Center for Translational Medicine, Institute of Biomedical Science, College of Life Science, National Chung Hsing University, Taichung 402, Taiwan
4
Graduate Institute of Clinical Medical Science, School of Medicine, China Medical University, Taichung 404, Taiwan
5
Department of Post-Baccalaureate Medicine, College of Medicine, National Chung Hsing University, Taichung 402, Taiwan
6
Department of Life Science, Tunghai University, Taichung 407, Taiwan
7
School of Medicine, National Yang-Ming University, Taipei 112, Taiwan
*
Author to whom correspondence should be addressed.
Diagnostics 2022, 12(4), 864; https://doi.org/10.3390/diagnostics12040864
Submission received: 9 March 2022 / Revised: 23 March 2022 / Accepted: 29 March 2022 / Published: 30 March 2022
(This article belongs to the Section Pathology and Molecular Diagnostics)
Browse Figures
Versions Notes

Abstract

:
Introduction: Iodinated contrast medium (CM) is the third most common cause of acute kidney injury (AKI). However, the association is poorly known between the definitions of AKI between different stages of chronic kidney disease after intravenous CM administration. Methods: The dataset, covering a period of ~15 years (1 June 2008 to 31 March 2015), consisted of 20,018 non-dialytic adult patients who had received intravenous injections of non-ionic iso-osmolar CM, iodixanol, for enhanced computed tomography imaging. Contrast-associated AKI (CA-AKI), dialysis-required AKI, and mortality were analyzed. Results: A total of 12,271 participants were enrolled. CA-AKI increased significantly starting from stage 3A onward (p < 0.001). In summary, incidences of CA-AKI against different levels of chronic kidney disease were as follows: stage 1 (8.3%) = stage 2 (6.7%) < stage 3A (9.9%) < stage 3B (14.3%) < stage 4 (20.5%) = stage 5 (20.4%). The incidences of dialysis within 30 days were as follows: stage 1 (1%) = stage 2 (1.4%) = stage 3A (2.7%) < stage 3B (5.7%) < stage 4 (18%) < stage 5 (54.1%). The prediction of dialysis was good based on the baseline serum creatinine > 1.5 mg/dL (72.78% of sensitivity, 86.07% of specificity, 0.851 of area under curve) or baseline estimated glomerular filtration rate ≤ 38.49 mL/min/1.732 m2 (70.19% of sensitivity, 89.08% of specificity, 0.853 of area under curve). In multivariate Cox regression analysis model for CA-AKI, independent risk factors were stage 4 chronic kidney disease (p = 0.001) and shock (p = 0.001). Conclusion: Baseline serum creatinine and estimated glomerular filtration rate were good predictors for dialysis-required AKI. CA-AKI increased significantly since stage 3A chronic kidney disease. Stage 4 and 5 chronic kidney disease have the same risk for CA-AKI, but stage 5 chronic kidney disease has markedly higher risk for dialysis.

1. Background

Iodinated contrast medium (CM) is the third most common cause of acute kidney injury (AKI) [1], which increases the risks of dialysis and mortality. The most common cause of contrast-induced nephropathy (CIN) is pre-existing chronic kidney disease (CKD). Since 2008, a number of studies have indicated that the severity of CKD is a risk factor for the development of AKI [2,3]. Specifically, CIN occurs following CM exposure in 8% of patients with estimated glomerular filtration rate (eGFR) lying between 45 to 60 mL/min/1.73 m2, 13% with eGFR between 30 to 45 mL/min/1.73 m2, or 27% with eGFR < 30 mL/min/1.73 m2 [4,5,6]. Only post-contrast renal outcome has been reported when eGFR falls below 30 mL/min/1.73 m2. Little is known about the AKI, dialysis and mortality after CM administration in patients with further severe CKD (i.e., stages 4 and 5) [7,8,9]. Such studies on CKD and CIN when also reported is based on a small number of patients [10].
CIN, classically defined by an increase in serum creatinine (SCr) levels by 25% or >44 μmol/L that occurs within 48–72 h after intravenous (IV) CM administration [11], was replaced recently by contrast-associated AKI (CA-AKI) based on the definition of AKI (Kidney Disease Improving Global Outcomes (KDIGO) practice guideline [12]), which broadened the period of renal dysfunction from 48–72 h to 7 days. Most earlier studies on post-contrast renal impairment were based on the classical definition of CIN [11] rather than the newer CA-AKI. Therefore, the study between CA-AKI (occurs within 7 days) after CM administration is largely limited.
The risk of CIN due to IV CM maybe overstated [13,14]. Clinicians used high-osmolality CM in early studies, but low-osmolality CM agents with much less CIN [15] were used instead in the current era. The Contrast Media Safety Committee (CMSC) of the European Society of Urogenital Radiology (ESUR) recommended an eGFR < 45 mL/min/1.73 m2 before an IV CM application and an eGFR < 60 mL/min/1.73 m2 before an intra-arterial (IA) CM administration is considered a risk factor for CIN [13,16,17]. More chances of CIN can likely occur with IA CM than with IV CM. The literature regards incidences of CIN that occur typically following cardiac angiography, with lower risks of CIN after IV injection. Most previous studies are on IA CM-related CIN for patients with either cardiac catheterization or percutaneous coronary intervention. IV CM administration is not associated with higher risks of CIN, emergent dialysis, and short-term mortality in another study [18]. Similarly, a retrospective cohort study in 2017 showed that IV CM from contrast-enhanced CT (CCT) (with iso- or low- osmolar agents) does not associate with more incidences of CIN [10]. On the contrary, IV CM was found to be associated with CIN in two other studies [19,20]. The association remains controversial between IV CM administration from CCT and CIN. We here aimed to study the association between IV CM from CCT and renal dysfunction in patients with different baseline renal functions, using a large database to determine the association between different stages of CKD and renal impairment (defined by CA-AKI instead of CIN) in patients undergoing IV CM (iso-osmolar CM, 100 mL) from CCT.

2. Materials and methods

2.1. Study Design and Patient Population

We conducted this retrospective historical cohort study on a database at our hospital (Taichung Veterans General Hospital) as recorded from 20,018 adult patients without dialysis receiving IV non-ionic and iso-osmolar CM (iodixanol (Visipaque, Chicago, IL, USA)) for enhanced CT during a period of ~15 years (1 June 2008 to 31 March 2015). All data were from electronic medical record system in our institute. The data for each patient included baseline SCr within two days before CCT. Data were employed to determine the post-CCT association between baseline stages of CKD and renal outcome (CA-AKI [12], dialysis within 30 days, and mortality). Excluded participants were patients with pre-existing AKI (defined according to KDIGO practice guideline [12]), with recent exposures to CM over the preceding 30 days, volume of CM not equal to 100 mL (usual volume of CM for CCT), not available baseline SCr within the two days before CCT, and not available post-contrast SCr within one week after CCT.
The institute review board of Taichung Veterans General Hospital approved this study (IRB TCVGH No: F15059). The entire procedures were performed in accordance with the relevant guidelines and regulations. Informed consent was waived due to the data evaluation nature of the study. We had no official protocol for the prevention of CIN in our institute, such as IV normal saline hydration, sodium bicarbonate infusion, and N-acetylcysteine during the period of this study.

2.2. Baseline Information Retrieval and Definition

Baseline stages of CKD was determined by the calculation from the modification of diet in renal disease (MDRD) [21]: eGFR (mL/min per 1.73 m2) = 186 × SCr−1.154 × Age−0.203 × 0.742 (0.742 instead of 1.0, in the case of female). All comorbid conditions were screened as possible, including cardiovascular and cerebrovascular disease (cerebrovascular attack, coronary artery disease, peripheral arterial disease, and acute myocardial infarction), metabolic disease (hypertension and diabetes mellitus), liver disease (cirrhosis, peritonitis, ascites, and hepatoma), gastrointestinal bleeding, malignancy (lung and colon cancer), and shock. Prescriptions were all screened for angiotensin II receptor blockers or angiotensin-converting enzyme inhibitors, non-steroidal anti-inflammatory drugs, aspirin, aminoglycoside, statins, loop diuretics, steroids, and H2-blockers (famotidine and ranitidine).

2.3. Outcome Retrieval and Definitions

We set primary outcome as CA-AKI, which was defined according to the KDIGO practice guideline [12]: after CCT, an increase in SCr ≥ 0.3 mg/dL above baseline levels within 48 h or ≥ 50% within 7 days. To broaden the period of renal dysfunction to 7 days from 48–72 h, we chose not to follow the classical definition of CIN (i.e., an increase of SCr > 44 μmol/L or 25%, within 48–72 h following IV CM [11]). Because urine volumes were not collected periodically, we thus cannot include urine volume as a criterion for CI-AKI, as that was in the guideline of KDIGO.
The secondary endpoint was the necessity of evolving hemodialysis (i.e., dialysis-required AKI) within 30 days after CCT (the first documented hemodialysis within 30 days later than CCT). All indications and timing for urgent hemodialysis included refractory fluid excess even with diuretic drugs, severe hyperkalemia (>6.5 meq/L) even following potassium-lowering agents, >100 mg/dL of blood urea nitrogen, >6 mg/dL of SCr, metabolic acidosis (pH < 7.2), uremic encephalopathy, uremic bleeding, and uremic pericarditis. Mortality was also recorded for post-contrast complication.
We divided all patients to five groups according to stages of CKD [21]. In addition, the Youden index was used to establish the cutoff value of baseline SCr and eGFR to predict CA-AKI and dialysis within 30 days after the administration of CM.
This study was approved by Ethics Committee of Taichung Veterans General Hospital, IRB number: F15059. All patients’ data were retrospectively analyzed. According to the regulation, no patient’s informed consents were needed.

2.4. Statistical Analyses

Quantitative data are presented as mean ± standard deviation. Nominal and categorical variables were compared pairwise using the chi-square likelihood ratio or Fisher exact test with Bonferroni post hoc analyses. Continuous variables were evaluated by applying the nonparametric Wilcoxon test. We used univariate and multivariate logistic regression analyses to determine the associations between patient-related characteristics or comorbidities with CA-AKI and dialysis within 30 days and mortality. We used odds ratio (OR) and 95% confidence interval (CI) to determine the associations with the risks of CA-AKI and dialysis within 30 days after CCT. Two-sided p-values < 0.05 were considered statistically significant differences. We used the SPSS software (Statistical Package for the Social Science, version 20.0, Armonk, NY, USA) for all our statistical analyses.

3. Results

The initial population undergoing CCT was 58,106 patients. After exclusion (no SCr data, repeated patients, and pre-existing AKI), 12,271 were finally included in this study (Figure 1). Their baseline data are shown in Table 1 (listed separately according to the five stages of CKD). Patients of later stages of CKD had more of the following: DM (p < 0.001), CAD (p < 0.001), AMI (p < 0.001), and gastrointestinal hemorrhage (p < 0.001). They also had higher serum levels of potassium (p < 0.001), fewer medications with NSAIDs (p < 0.001), more medications with aspirin (p < 0.001), and fewer using aminoglycosides (p < 0.001).
The associations between outcome after CM exposure and different stages of CKD are plotted in Figure 2A (for CA-AKI), Figure 2B (for dialysis-required AKI, within 30 days), and Figure 2C (for mortality within 30 days). CA-AKI incidence increased significantly starting from CKD stage 3A onward (p < 0.001) (Figure 2A). Incidences of CA-AKI were similar between stage 1 and stage 2 and also similar between stage 4 and stage 5 of CKD. In summary, the incidences of CA-AKI across CKD stages were as follows: stage 1 (8.3%) = stage 2 (6.7%) < stage 3A (9.9%) < stage 3B (14.3%) < stage 4 (20.5%) = stage 5 (20.4%). As for dialysis within 30 days (Figure 2B), such incidences increased significantly from CKD stage 3B onward. Incidences of dialysis within 30 days were as follows: stage 1 (1%) = stage 2 (1.4%) = stage 3A (2.7%) < stage 3B (5.7%) < stage 4 (18%) < stage 5 CKD (54.1%). Death within 30 days after CM increased significantly from CKD stage 3A onward (Figure 2C). Incidences of mortality were as follow: stage 1 (8.3%) = stage 2 (8.2%) < stage 3A (12.2%) = stage 3B (14.9%) < stage 4 (20.5%) = stage 5 (18.3%). Once with the occurrence of CA-AKI (7.9% vs. 33.3%, p < 0.001) or dialysis within 30 days (9.3% vs. 32.7%, p < 0.001), mortality rates increased significantly (Figure 3).
The predictive power of baseline SCr > 1.3 mg/dL on CA-AKI was not good (36.73% of sensitivity, 78.92% of specificity, 0.555 of AUC) (Figure 4A). Similarly, predictive power of baseline eGFR ≤ 57.18 mL/min/1.732 m2 on CA-AKI was not good (43.17% of sensitivity, 73.69% of specificity, and 0.563 of AUC) (Figure 4B). On the other hand, the predictive powers were good on dialysis for baseline SCr > 1.5 mg/dL (72.78% sensitivity, 86.07% specificity, 0.851 of AUC) (Figure 4C) on dialysis and for baseline eGFR ≤ 38.49 mL/min/1.732 m2 (70.19% sensitivity, 89.08% specificity, and 0.853 of AUC) (Figure 4D).
In the multivariate Cox regression model, two independent risk factors were found for CA-AKI: stage 4 CKD (p = 0.001) and shock (p = 0.001) (Table 2). Similarly for dialysis, six independent risk factors were found: stage 3A (p = 0.010), stage 3B (p < 0.001), stage 4 (p < 0.001), and stage 5 CKD (p < 0.001), DM (p = 0.039), shock (p < 0.001), and longer prothrombin time (p = 0.019) (Table 3). As for mortality, nine independent risk factors were found: stage 3A (p = 0.01), stage 3B (p = 0.021), stage 4 (p < 0.001), and stage 5 (p = 0.004) CKD, hepatoma (p = 0.042), lung cancer (p < 0.001), shock (p < 0.001), and peritonitis (p = 0.026) (p < 0.001) (Table 4).

4. Discussion

Our present study is the biggest one of its kind in elucidating, after IV CM from CCT, the association between CA-AKI (rather than CIN) and different stages of CKD (with some difference between stage 4 and 5 CKD). Little previous study has provided clinicians the information regarding different incidences if any of CA-AKI in stage 4 and 5 CKD. Only one study mentioned the association of CA-AKI, dialysis, and mortality after CM administration between stage 4 and stage 5 CKD but with small numbers of patients (only 78 patients with stage 4–5 CKD) [10]. Two previous studies [4,5,6] showed that in CKD patients, the occurrence of CIN is 8% in stage 3A, 13% in stage 3B, and 27% in stages 4 and 5. The other three studies on CKD did not differentiate risks of CIN between stage 4 and 5 patients [18,22,23]. In CMSC of the ESUR, CIN is discussed on CKD but without differentiating stage 4 and 5 patients [13,17]. The major finding of our present study is that information is now available to medical professionals regarding incidence of CA-AKI in both stage 4 and stage 5 CKD patients. Compared to previous studies (on CIN rather than CA-AKI), the incidence of CA-AKI is 9.9% in stage 3A, 14.3% in stage 3B, 20.5% in stage 4, and 20.4% in stage 5 CKD (similar to stage 4 CKD). Comparing between CIN [4,5,6] and CA-AKI in CKD patients, their incidences are similar in stage 3A (8% vs. 9.9%) and stage 3B (13% vs. 14.3%). The incidence of CIN in stage 4–5 is 27%, and the incidence of CA-AKI is 20.4% in stage 4 and 20.5% in stage 5 CKD patients. In summary, the incidence of CA-AKI was similar to the incidence of CIN. CIN is defined as renal dysfunction within 48–72 h after CM exposure, but the AKI definition broadens the timeline up to 7 days after CM administration. However, with contrast-related renal dysfunctions, SCr levels almost all increased within 24 to 48 h after the CM exposure [24,25]. In our opinion, extending observation period to 7 days therefore offered little advantage for the evaluation of renal dysfunction.
Incidences of CA-AKI in stage 4 and 5 were nearly identical (20.4 vs. 20.5%), which did not indicate the same risk of renal function deterioration between stage 4 and 5 CKD after CM administration. First, increased SCr is not linearly related to the renal injury. The diagnosis of AKI based on KDIGO definition [12] likely underestimates the importance of real renal function injury in the severe stages of CKD. Similarly, in another study (based on new AKI definition), the incidence of CA-AKI was 10.3% in stage 4 CKD and 25% in stage 5 CKD [10]. The incidence did not increase significant from stage 4 to 5 CKD. Those will underestimate the importance of renal dysfunction between stage 4 and 5 CKD. In that study [10], they also excluded patients with SCr > 4 mg/dL, which is very severe selection bias. They excluded the highest risk for the requirement of dialysis. Only 78 patients of CKD stage 4–5 received contrast, but up to 576 patients of CKD stage 1–3 did. Therefore, the risk of renal dysfunction is not as low as that study in CKD stage 5 [10].
CA-AKI is a SCr-based analysis, but the dialysis-required AKI is a multiple clinical-variables-based outcome, which is a better marker for renal injury in the advanced stages of CKD. In clinical practice, the necessity for dialysis (clinical outcome) is more important than CA-AKI (laboratory outcome) to both patients and clinicians. The incidence of urgent hemodialysis markedly higher in stage 5 CKD compared to stage 4 CKD (51.4% vs. 18.0%, p < 0.001) even at similar incidences of CA-AKI. For dialysis-requiring AKI, a patient started at a lower GFR prior to AKI (more severe stage of CKD) would be more likely to begin dialysis than a patient started at a higher GFR (less severe stage of CKD). In this cohort, the predictive value of baseline SCr and eGFR were both better for urgent dialysis (sensitivity = 72.78%, specificity = 86.07%, AUC= 0.851, by SCr; sensitivity = 70.19%, specificity = 89.08%, AUC= 0.853, by eGFR) than for CA-AKI. As a result, we suggest here that not only the incidence of CA-AKI (laboratory outcome) but also dialysis-requiring AKI (clinical outcome) should be included in the outcome analysis of renal dysfunction after CM administration.
In 2010, the exposure to iodinated CM was implicated as the third most common cause of AKI with concomitant increased risks of dialysis and death [19]. The most common cause of CIN is pre-existing CKD because of the less-preserved renal function. Moreover, it is known that CIN in CKD patients have higher mortality rates compared to those without CKD [26]. However, the risk of CIN caused by CM administration may be overestimated [13,14]. There are hosts of confounding factors when addressing this issue: baseline condition, IA or IV CM, contrast volume, baseline conditions for IA (unstable hemodynamics, easier thromboli or emboli), types of CM (hyper-osmolality, hypo-osmolality, and isotonic CM), and first- or second-pass renal exposure. The type and volume of CM do matter. In the current era, low-osmolality CM agents cause fewer cases of CIN [15]. In this study, we only focused on the pure non-ionic iso-osmolar CM, iodixanol (Visipaque, Chicago, IL, USA), at a fixed volume (100 mL) to avoid bias. Second, CIN is more likely to occur in IA CM following cardiac angiography. The increased SCr may be due to background fluctuations of GFR that are common in sick, hospitalized patients. Patients receiving IA cardiac angiography may need volumes > 100 mL CM because of intervention and their less-stable hemodynamics. Reports on CIN are typically those cases following cardiac angiography. According to the recommendations of CMSC of the ESUR, eGFR levels < 45 mL/min/1.73 m2 before IV CM and eGFR levels < 60 mL/min/1.73 m2 before IA CM administrations represent a risk factor for CIN [16]. This same guideline in 2018 [13,17] suggested that if eGFR levels are < 45 mL/min/1.73 m2 and IA CM with first-pass renal exposure in the intensive care unit, prevention was suggested (evidence C). The prevention of CIN is therefore more likely after IA CM than IV CM [27,28]. Lower volumes and greater dilution before reaching the kidneys more likely happen in the case of IV CM. For IA CM, a score system has been established for CIN based on IA CM [28]. Renal injury after IV CM administration remains without consensus. Two meta-analyses in 2018 [10,29] reported no association between IV CM administration and CIN. Other studies also suggested that CIN after CCT may have been overlooked [18,23,30,31,32]. A retrospective study over a period of 7 years on 11,588 patients who underwent CT (5790 with CM, 7484 without) also supported similar results [33]. They considered CIN cannot be reflexively attributed to CM. However, in a propensity-matched analysis in 2019 [34], the administration of both IV and IA CM were found to associate with a risk of CIN. In our study, we did not have IA CM group for comparison, so we were uncertain the difference of risk of CA-AKI between IA and IV CM administration. However, in this cohort, the incidence of CA-AKI and dialysis-required AKI both increased at the worse baseline renal function.
A study by Bruce [30] suggested that the incidence of SCr elevation in patients receiving non-CM CCT was statistically similar to that in the iso-osmolar CM regardless of their baseline SCr levels and stages of CKD. However, in his study, only 62 (7.6%) patients with stage 4 and 5 CKD received IV CM CCT, and up to 1131 (15.1%) patients with stage 4 and 5 CKD received non-CM CT. Another 2015 study on CKD patients [18] reported that IV CM administration is not associated with an increased risk of CIN, emergent dialysis, and short-term mortality. However, their study had only a small number of patients with severe CKD (6% of stage 3 CKD and 17% of stage 4 and 5 CKD). Selection bias likely took place due to the fact that the sample size with severe CKD was small. Furthermore, those studies did not have same type or fixed volume of CM. However, in our study, we had more (1046) patients with stage 4 and 5 CKD receiving CCT with fixed contrast volume and had different baseline comorbidities. In other better-designed studies on IV CM after CCT, lower baseline eGFR was found to associate with more CIN [19,20,22,23]. Davenport et al. [22] reported that IV CM is a nephrotoxic risk factor for patients with eGFR levels consistently < 30 mL/min/1.73 m2, with a trend toward significance at 30–44 mL/min/1.73 m2. That is consistent with our finding that stage 4 CKD is associated with CA-AKI (OR = 1.90, 95%CI = 1.29–2.79, p < 0.001). Further, the baseline renal function (SCr and eGFR) can predict the dialysis-required CA-AKI with sufficient accuracy. Higher mortality likely occurs once with CA-AKI or dialysis after IV CM administration.
There are limitations of this study. First, we had no control group in this study. Second, this is a retrospective and single-center study. Third, we did not record the underlying condition of sepsis [35] in this study. However, we already included many comorbidities in this study, including DM, hypertension, CVA, PAOD, cirrhosis, hepatoma, colon cancer, lung cancer, AF, CAD, AMI, shock, peritonitis, ascites, and GI hemorrhage. Fourth, not every possible medication [36,37] and Chinese herbal medicine [38] affecting renal function was recorded in this study. However, we already included as many medications as possible, such as NSAID, aspirin, COX2i, aminoglycoside, loop diuretics, ACEi, ARB, steroid, statin, ranitidine, and famotidine. Fifth, we did not collect other biomarkers to correlate the association of CI-AKI [39], such as KIM-1, NGAL, IL-18, MCP-1, UMOD, and YKL-40. We also did not correlate new technology for the CI-AKI in this study, such as nanomedicine [40]. Finally, the recruitment period was long with the possibility of practices change over time.

5. Conclusions

Even without consensus on the renal toxicity of IV CM, we would like to suggest that the procedure of IV CM administration should be avoided for patients with severe stages of CKD to minimize outcomes of CA-AKI (another definition rather than CIN), dialysis, and mortality. Baseline SCr and eGFR both had good predictive power for dialysis-required AKI. Stage 4 and 5 CKD have the same risk for CA-AKI, but stage 5 CKD has markedly higher risk for dialysis.

Author Contributions

M.-J.W. and S.-F.T. conceived of the presented idea. M.-J.W. analyzed data, and S.-F.T. supervised the findings of this work. All authors discussed the results and contributed to the final manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This study was supported by Grants TCVGH-1093605D and TCVGH-1093602B from Taichung Veterans General Hospital.

Institutional Review Board Statement

This study was approved by Ethics Committee of Taichung Veterans General Hospital, IRB number: F15059. All data were approved by Institutional Review Board of Taichung Veterans General Hospital to be published.

Informed Consent Statement

Patient consent was waived due to restrospective study without any interventions.

Data Availability Statement

Data cannot be shared due to the regulation of local institute.

Acknowledgments

This work was funded in part by Taichung County Kidney Association. We thank the Clinical Informatics Research and Development Center of Taichung Veterans General Hospital for assistance in data collection, Lin, Fen-Yi for assistance in data preparation. The authors thank the Biostatistics Task Force of Taichung Veterans General Hospital and Chen, Jun-Peng for help in statistics.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Mohammed, N.M.; Mahfouz, A.; Achkar, K.; Rafie, I.M.; Hajar, R. Contrast-induced Nephropathy. Heart Views 2013, 14, 106–116. [Google Scholar] [CrossRef] [PubMed]
  2. Hsu, C.Y.; Ordonez, J.D.; Chertow, G.M.; Fan, D.; McCulloch, C.E.; Go, A.S. The risk of acute renal failure in patients with chronic kidney disease. Kidney Int. 2008, 74, 101–107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Gansevoort, R.T.; Matsushita, K.; van der Velde, M.; Astor, B.C.; Woodward, M.; Levey, A.S.; de Jong, P.E.; Coresh, J. Lower estimated GFR and higher albuminuria are associated with adverse kidney outcomes. A collaborative meta-analysis of general and high-risk population cohorts. Kidney Int. 2011, 80, 93–104. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. Patschan, D.; Muller, G.A. Acute Kidney Injury, AKI-Update 2018. Dtsch. Med. Wochenschr. 2018, 143, 1094–1096. [Google Scholar] [CrossRef] [PubMed]
  5. McDonald, J.S.; McDonald, R.J.; Tran, C.L.; Kolbe, A.B.; Williamson, E.E.; Kallmes, D.F. Postcontrast Acute Kidney Injury in Pediatric Patients: A Cohort Study. Am. J. Kidney Dis. Off. J. Natl. Kidney Found. 2018, 72, 811–818. [Google Scholar] [CrossRef]
  6. Hossain, M.A.; Costanzo, E.; Cosentino, J.; Patel, C.; Qaisar, H.; Singh, V.; Khan, T.; Cheng, J.S.; Asif, A.; Vachharajani, T.J. Contrast-induced nephropathy: Pathophysiology, risk factors, and prevention. Saudi J. Kidney Dis. Transplant. Off. Publ. Saudi Cent. Organ Transplant. Saudi Arab. 2018, 29, 1–9. [Google Scholar] [CrossRef]
  7. Pistolesi, V.; Regolisti, G.; Morabito, S.; Gandolfini, I.; Corrado, S.; Piotti, G.; Fiaccadori, E. Contrast medium induced acute kidney injury: A narrative review. J. Nephrol. 2018, 31, 797–812. [Google Scholar] [CrossRef]
  8. Pannu, N. In patients with CKD having CT with contrast media, no prehydration and prehydration did not differ for AKI. Ann. Intern. Med. 2020, 173, Jc8. [Google Scholar] [CrossRef]
  9. Rudnick, M.R.; Wahba, I.M.; Leonberg-Yoo, A.K.; Miskulin, D.; Litt, H.I. Risks and Options with Gadolinium-Based Contrast Agents in Patients with CKD: A Review. Am. J. Kidney Dis. 2021, 77, 517–528. [Google Scholar] [CrossRef]
  10. Hinson, J.S.; Ehmann, M.R.; Fine, D.M.; Fishman, E.K.; Toerper, M.F.; Rothman, R.E.; Klein, E.Y. Risk of Acute Kidney Injury After Intravenous Contrast Media Administration. Ann. Emerg. Med. 2017, 69, 577–586.e574. [Google Scholar] [CrossRef]
  11. Stacul, F.; van der Molen, A.J.; Reimer, P.; Webb, J.A.; Thomsen, H.S.; Morcos, S.K.; Almen, T.; Aspelin, P.; Bellin, M.F.; Clement, O.; et al. Contrast induced nephropathy: Updated ESUR Contrast Media Safety Committee guidelines. Eur. Radiol. 2011, 21, 2527–2541. [Google Scholar] [CrossRef] [PubMed]
  12. Okusa, M.D.; Davenport, A. Reading between the (guide)lines–the KDIGO practice guideline on acute kidney injury in the individual patient. Kidney Int. 2014, 85, 39–48. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. van der Molen, A.J.; Reimer, P.; Dekkers, I.A.; Bongartz, G.; Bellin, M.F.; Bertolotto, M.; Clement, O.; Heinz-Peer, G.; Stacul, F.; Webb, J.A.W.; et al. Post-contrast acute kidney injury-Part 1: Definition, clinical features, incidence, role of contrast medium and risk factors: Recommendations for updated ESUR Contrast Medium Safety Committee guidelines. Eur. Radiol. 2018, 28, 2845–2855. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  14. Luk, L.; Steinman, J.; Newhouse, J.H. Intravenous Contrast-Induced Nephropathy-The Rise and Fall of a Threatening Idea. Adv. Chronic Kidney Dis. 2017, 24, 169–175. [Google Scholar] [CrossRef] [PubMed]
  15. Goldfarb, S.; Spinler, S.; Berns, J.S.; Rudnick, M.R. Low-osmolality contrast media and the risk of contrast-associated nephrotoxicity. Investig. Radiol. 1993, 28 (Suppl. S5), S7–S10; discussion S11–S12. [Google Scholar] [CrossRef]
  16. Thomsen, H.S.; Morcos, S.K. Contrast media and the kidney: European Society of Urogenital Radiology (ESUR) guidelines. Br. J. Radiol. 2003, 76, 513–518. [Google Scholar] [CrossRef]
  17. van der Molen, A.J.; Reimer, P.; Dekkers, I.A.; Bongartz, G.; Bellin, M.F.; Bertolotto, M.; Clement, O.; Heinz-Peer, G.; Stacul, F.; Webb, J.A.W.; et al. Post-contrast acute kidney injury. Part 2: Risk stratification, role of hydration and other prophylactic measures, patients taking metformin and chronic dialysis patients: Recommendations for updated ESUR Contrast Medium Safety Committee guidelines. Eur. Radiol. 2018, 28, 2856–2869. [Google Scholar] [CrossRef] [Green Version]
  18. McDonald, J.S.; McDonald, R.J.; Lieske, J.C.; Carter, R.E.; Katzberg, R.W.; Williamson, E.E.; Kallmes, D.F. Risk of Acute Kidney Injury, Dialysis, and Mortality in Patients with Chronic Kidney Disease After Intravenous Contrast Material Exposure. Mayo Clin. Proc. 2015, 90, 1046–1053. [Google Scholar] [CrossRef] [Green Version]
  19. Mitchell, A.M.; Jones, A.E.; Tumlin, J.A.; Kline, J.A. Incidence of contrast-induced nephropathy after contrast-enhanced computed tomography in the outpatient setting. Clin. J. Am. Soc. Nephrol. CJASN 2010, 5, 4–9. [Google Scholar] [CrossRef]
  20. Nyman, U.; Aspelin, P.; Jakobsen, J.; Bjork, J. Controversies in Contrast Material-induced Acute Kidney Injury: Propensity Score Matching of Patients with Different Dose/Absolute Glomerular Filtration Rate Ratios. Radiology 2015, 277, 633–637. [Google Scholar] [CrossRef] [Green Version]
  21. Levey, A.S.; Coresh, J.; Greene, T.; Stevens, L.A.; Zhang, Y.L.; Hendriksen, S.; Kusek, J.W.; Van Lente, F.; Chronic Kidney Disease Epidemiology, C. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann. Intern. Med. 2006, 145, 247–254. [Google Scholar] [CrossRef] [PubMed]
  22. Davenport, M.S.; Khalatbari, S.; Cohan, R.H.; Dillman, J.R.; Myles, J.D.; Ellis, J.H. Contrast material-induced nephrotoxicity and intravenous low-osmolality iodinated contrast material: Risk stratification by using estimated glomerular filtration rate. Radiology 2013, 268, 719–728. [Google Scholar] [CrossRef] [PubMed]
  23. McDonald, J.S.; McDonald, R.J.; Carter, R.E.; Katzberg, R.W.; Kallmes, D.F.; Williamson, E.E. Risk of intravenous contrast material-mediated acute kidney injury: A propensity score-matched study stratified by baseline-estimated glomerular filtration rate. Radiology 2014, 271, 65–73. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Rich, M.W.; Crecelius, C.A. Incidence, risk factors, and clinical course of acute renal insufficiency after cardiac catheterization in patients 70 years of age or older. A prospective study. Arch. Intern. Med. 1990, 150, 1237–1242. [Google Scholar] [CrossRef] [PubMed]
  25. Rudnick, M.R.; Berns, J.S.; Cohen, R.M.; Goldfarb, S. Nephrotoxic risks of renal angiography: Contrast media-associated nephrotoxicity and atheroembolism--a critical review. Am. J. Kidney Dis. 1994, 24, 713–727. [Google Scholar] [CrossRef]
  26. Abe, M.; Morimoto, T.; Akao, M.; Furukawa, Y.; Nakagawa, Y.; Shizuta, S.; Ehara, N.; Taniguchi, R.; Doi, T.; Nishiyama, K.; et al. Relation of contrast-induced nephropathy to long-term mortality after percutaneous coronary intervention. Am. J. Cardiol. 2014, 114, 362–368. [Google Scholar] [CrossRef] [PubMed]
  27. Kroneberger, C.; Enzweiler, C.N.; Schmidt-Lucke, A.; Ruckert, R.I.; Teichgraber, U.; Franiel, T. Contrast-induced nephropathy in patients with chronic kidney disease and peripheral arterial disease. Acta Radiol. Open 2015, 4, 815–821. [Google Scholar] [CrossRef]
  28. Modi, K.; Gupta, M. Contrast-Induced Nephropathy. In StatPearls; StatPearls Publishing LLC: Treasure Island, FL, USA, 2019. [Google Scholar]
  29. Aycock, R.D.; Westafer, L.M.; Boxen, J.L.; Majlesi, N.; Schoenfeld, E.M.; Bannuru, R.R. Acute Kidney Injury After Computed Tomography: A Meta-analysis. Ann. Emerg. Med. 2018, 71, 44–53.e44. [Google Scholar] [CrossRef]
  30. Bruce, R.J.; Djamali, A.; Shinki, K.; Michel, S.J.; Fine, J.P.; Pozniak, M.A. Background fluctuation of kidney function versus contrast-induced nephrotoxicity. AJR Am. J. Roentgenol. 2009, 192, 711–718. [Google Scholar] [CrossRef]
  31. Murakami, R.; Hayashi, H.; Sugizaki, K.; Yoshida, T.; Okazaki, E.; Kumita, S.; Owan, C. Contrast-induced nephropathy in patients with renal insufficiency undergoing contrast-enhanced MDCT. Eur. Radiol. 2012, 22, 2147–2152. [Google Scholar] [CrossRef]
  32. McDonald, R.J.; McDonald, J.S.; Carter, R.E.; Hartman, R.P.; Katzberg, R.W.; Kallmes, D.F.; Williamson, E.E. Intravenous contrast material exposure is not an independent risk factor for dialysis or mortality. Radiology 2014, 273, 714–725. [Google Scholar] [CrossRef] [PubMed]
  33. Tublin, M.E.; Murphy, M.E.; Tessler, F.N. Current concepts in contrast media-induced nephropathy. AJR Am. J. Roentgenol. 1998, 171, 933–939. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Chaudhury, P.; Armanyous, S.; Harb, S.C.; Ferreira Provenzano, L.; Ashour, T.; Jolly, S.E.; Arrigain, S.; Konig, V.; Schold, J.D.; Navaneethan, S.D.; et al. Intra-Arterial versus Intravenous Contrast and Renal Injury in Chronic Kidney Disease: A Propensity-Matched Analysis. Nephron 2019, 141, 31–40. [Google Scholar] [CrossRef] [PubMed]
  35. Poston, J.T.; Koyner, J.L. Sepsis associated acute kidney injury. Bmj 2019, 364, k4891. [Google Scholar] [CrossRef] [PubMed]
  36. Cook, A.M.; Hatton-Kolpek, J. Augmented Renal Clearance. Pharmacotherapy 2019, 39, 346–354. [Google Scholar] [CrossRef]
  37. Goldstein, S.L. Medication-induced acute kidney injury. Curr. Opin. Crit. Care 2016, 22, 542–545. [Google Scholar] [CrossRef]
  38. Yang, B.; Xie, Y.; Guo, M.; Rosner, M.H.; Yang, H.; Ronco, C. Nephrotoxicity and Chinese Herbal Medicine. Clin. J. Am. Soc. Nephrol. CJASN 2018, 13, 1605–1611. [Google Scholar] [CrossRef]
  39. Parikh, C.R.; Liu, C.; Mor, M.K.; Palevsky, P.M.; Kaufman, J.S.; Thiessen Philbrook, H.; Weisbord, S.D. Kidney Biomarkers of Injury and Repair as Predictors of Contrast-Associated AKI: A Substudy of the PRESERVE Trial. Am. J. Kidney Dis. 2020, 75, 187–194. [Google Scholar] [CrossRef]
  40. Eftekhari, A.; Maleki Dizaj, S.; Ahmadian, E.; Przekora, A.; Hosseiniyan Khatibi, S.M.; Ardalan, M.; Zununi Vahed, S.; Valiyeva, M.; Mehraliyeva, S.; Khalilov, R.; et al. Application of Advanced Nanomaterials for Kidney Failure Treatment and Regeneration. Materials 2021, 14, 2939. [Google Scholar] [CrossRef]
Diagnostics 12 00864 g001 550
Figure 1. Patients selection flow chart.
Figure 1. Patients selection flow chart.
Diagnostics 12 00864 g001
Diagnostics 12 00864 g002a 550Diagnostics 12 00864 g002b 550
Figure 2. Outcomes of renal function outcomes according to baseline stages of CKD. All the three renal outcomes are significantly worse beyond the baseline renal function of stage IIIA. (A) Incidences of acute kidney injury after CCT according to baseline stages of CKD. Incidences are significant (p < 0.001) between stages I and IIIB–V; between stages II and IIIA to V; between stages IIIA and IIIB to V; and between stages IIIB and V. The increases in incidence are statistically significant starting from stage IIIA onward. Acute kidney injury after contrast computed tomography shown according to baseline stages of CKD; post hoc analysis showed p < 0.001 in I vs. IIIB, I vs. IV, I vs. V, II vs. IIIA, II vs. IIIB, II vs. IV, II vs. V, IIIA vs. IIIB, IIIA vs. IV, IIIA vs. V, and IIIB vs. IV. (B) Incidences of dialysis within 30 days after CCT shown according to baseline stages of CKD. The incidence was significantly different (p < 0.001) between stages I and IIIA to V; between stages II and IIIB to V; between stages IIIA and IIIB to V; between stages IIIB and IV to V; between stages IV and V. The incidence significantly increased from stage IIIA onward. Dialysis within 30 days after contrast computed tomography shown according to baseline stages of CKD, Post hoc analysis showed p < 0.001 in I vs. IIIA, I vs. IIIB, I vs. IV, I vs. V, II vs. IIIB, II vs. IV, II vs. V, IIIA vs. IIIB, IIIA vs. IV, IIIA vs. V, IIIB vs. IV, IIIB vs. V, and IV vs. V. (C) Incidences of death within 30 days after CCT shown according to baseline stages of CKD. The incidence was significantly different (p < 0.001) between stages I and IIIA to V; between stages II and s IIIA to V; between stages IIIA and IV to V; and between stages IIIB and IV. The incidence significantly increased from stage IIIA onward. Deaths within 30 days after contrast computed tomography shown according to baseline stages of CKD. Post hoc analysis showed p < 0.001 in I vs. IIIA, I vs. IIIB, I vs. IV, I vs. V, II vs. IIIA, II vs. IIIB, II vs. IV, II vs. V, IIIA vs. IV, IIIA vs. V, and IIIB vs. IV; chi-square test, ** p < 0.01.
Figure 2. Outcomes of renal function outcomes according to baseline stages of CKD. All the three renal outcomes are significantly worse beyond the baseline renal function of stage IIIA. (A) Incidences of acute kidney injury after CCT according to baseline stages of CKD. Incidences are significant (p < 0.001) between stages I and IIIB–V; between stages II and IIIA to V; between stages IIIA and IIIB to V; and between stages IIIB and V. The increases in incidence are statistically significant starting from stage IIIA onward. Acute kidney injury after contrast computed tomography shown according to baseline stages of CKD; post hoc analysis showed p < 0.001 in I vs. IIIB, I vs. IV, I vs. V, II vs. IIIA, II vs. IIIB, II vs. IV, II vs. V, IIIA vs. IIIB, IIIA vs. IV, IIIA vs. V, and IIIB vs. IV. (B) Incidences of dialysis within 30 days after CCT shown according to baseline stages of CKD. The incidence was significantly different (p < 0.001) between stages I and IIIA to V; between stages II and IIIB to V; between stages IIIA and IIIB to V; between stages IIIB and IV to V; between stages IV and V. The incidence significantly increased from stage IIIA onward. Dialysis within 30 days after contrast computed tomography shown according to baseline stages of CKD, Post hoc analysis showed p < 0.001 in I vs. IIIA, I vs. IIIB, I vs. IV, I vs. V, II vs. IIIB, II vs. IV, II vs. V, IIIA vs. IIIB, IIIA vs. IV, IIIA vs. V, IIIB vs. IV, IIIB vs. V, and IV vs. V. (C) Incidences of death within 30 days after CCT shown according to baseline stages of CKD. The incidence was significantly different (p < 0.001) between stages I and IIIA to V; between stages II and s IIIA to V; between stages IIIA and IV to V; and between stages IIIB and IV. The incidence significantly increased from stage IIIA onward. Deaths within 30 days after contrast computed tomography shown according to baseline stages of CKD. Post hoc analysis showed p < 0.001 in I vs. IIIA, I vs. IIIB, I vs. IV, I vs. V, II vs. IIIA, II vs. IIIB, II vs. IV, II vs. V, IIIA vs. IV, IIIA vs. V, and IIIB vs. IV; chi-square test, ** p < 0.01.
Diagnostics 12 00864 g002aDiagnostics 12 00864 g002b
Diagnostics 12 00864 g003 550
Figure 3. Once patients had developed post-CCT AKI, they more likely died (33.3% vs. 7.9%, p < 0.001). Similarly, once patients started with dialysis after CCT, they more likely died (32.7% vs. 9.3%, p < 0.001). The association between mortality within 30 days and AKI or dialysis within 30 days. Chi-square test, ** p < 0.01.
Figure 3. Once patients had developed post-CCT AKI, they more likely died (33.3% vs. 7.9%, p < 0.001). Similarly, once patients started with dialysis after CCT, they more likely died (32.7% vs. 9.3%, p < 0.001). The association between mortality within 30 days and AKI or dialysis within 30 days. Chi-square test, ** p < 0.01.
Diagnostics 12 00864 g003
Diagnostics 12 00864 g004a 550Diagnostics 12 00864 g004b 550Diagnostics 12 00864 g004c 550Diagnostics 12 00864 g004d 550
Figure 4. The predictive value of baseline serum creatinine (SCr) and eGFR to acute kidney injury and dialysis within 30 days after CCT. (A) The baseline serum creatinine (SCr) (>1.3 mg/dL) to predicting post-CCT AKI showed rather low sensitivity (36.73%) and high specificity (78.92%). The AUC was only 0.555. (B) The baseline eGFR (≤57.18 mL/min/1.732 m2) in predicting post-CCT AKI showed rather low sensitivity (43.17%) and high specificity (73.69%). The AUC was only 0.563. The baseline eGFR in predicting post-CCT AKI. (C) The baseline serum creatinine (SCr) (>1.5 mg/dL) in predicting dialysis within 30 days after CCT showed high sensitivity (72.78%) and high specificity (86.07%). The AUC was up to 0.851. The baseline serum creatinine (Scr) in predicting dialysis within 30 days after CCT. (D) The baseline eGFR (≤38.49 mL/min/1.732 m2) in predicting dialysis within 30 days after CCT showed high sensitivity (70.19%) and high specificity (89.08%). The AUC was up to 0.853. The baseline eGFR in predicting dialysis within 30 days after CCT.
Figure 4. The predictive value of baseline serum creatinine (SCr) and eGFR to acute kidney injury and dialysis within 30 days after CCT. (A) The baseline serum creatinine (SCr) (>1.3 mg/dL) to predicting post-CCT AKI showed rather low sensitivity (36.73%) and high specificity (78.92%). The AUC was only 0.555. (B) The baseline eGFR (≤57.18 mL/min/1.732 m2) in predicting post-CCT AKI showed rather low sensitivity (43.17%) and high specificity (73.69%). The AUC was only 0.563. The baseline eGFR in predicting post-CCT AKI. (C) The baseline serum creatinine (SCr) (>1.5 mg/dL) in predicting dialysis within 30 days after CCT showed high sensitivity (72.78%) and high specificity (86.07%). The AUC was up to 0.851. The baseline serum creatinine (Scr) in predicting dialysis within 30 days after CCT. (D) The baseline eGFR (≤38.49 mL/min/1.732 m2) in predicting dialysis within 30 days after CCT showed high sensitivity (70.19%) and high specificity (89.08%). The AUC was up to 0.853. The baseline eGFR in predicting dialysis within 30 days after CCT.
Diagnostics 12 00864 g004aDiagnostics 12 00864 g004bDiagnostics 12 00864 g004cDiagnostics 12 00864 g004d
Table
Table 1. Baseline characteristics of all participants divided according to their stages of CKD.
Table 1. Baseline characteristics of all participants divided according to their stages of CKD.
CKD StageTotal
(n = 12,271)		p-Value
IIIIIIAIIIBIVV
Gender (Female)2870(59.0%)2476(66.4%)971(64.9%)704(62.2%)367(56.9%)209(52.1%)7597(61.9%)<0.001
Age, years57.13±16.3866.80±15.1472.02±13.0173.90±13.4173.65±13.0769.43±13.8964.70±16.49<0.001
Types of patients <0.001
Outpatients114(2.3%)89(2.4%)31(2.1%)21(1.9%)6(0.9%)7(1.7%)268(2.2%)
Inpatients1971(40.5%)1388(37.2%)455(30.4%)311(27.5%)154(23.9%)111(27.7%)4390(35.8%)
Emergent room2783(57.2%)2254(60.4%)1009(67.5%)799(70.6%)485(75.2%)283(70.6%)7613(62.0%)
Comorbidity
DM966(19.8%)1021(27.4%)566(37.9%)507(44.8%)311(48.2%)206(51.4%)3577(29.2%)<0.001
Hypertension1641(33.7%)1928(51.7%)953(63.7%)776(68.6%)419(65.0%)268(66.8%)5985(48.8%)<0.001
CVA522(10.7%)621(16.6%)291(19.5%)252(22.3%)146(22.6%)84(20.9%)1916(15.6%)<0.001
PAOD65(1.3%)104(2.8%)49(3.3%)70(6.2%)33(5.1%)31(7.7%)352(2.9%)<0.001
Cirrhosis514(10.6%)383(10.3%)187(12.5%)156(13.8%)87(13.5%)41(10.2%)1368(11.1%)0.002
Hepatoma435(8.9%)315(8.4%)149(10.0%)114(10.1%)65(10.1%)27(6.7%)1105(9.0%)0.147
Colon cancer477(9.8%)367(9.8%)127(8.5%)111(9.8%)50(7.8%)28(7.0%)1160(9.5%)0.149
Lung cancer882(18.1%)725(19.4%)278(18.6%)146(12.9%)74(11.5%)32(8.0%)2137(17.4%)<0.001
AF229(4.7%)341(9.1%)204(13.6%)175(15.5%)128(19.8%)65(16.2%)1142(9.3%)<0.001
CAD404(8.3%)635(17.0%)364(24.3%)331(29.3%)204(31.6%)130(32.4%)2068(16.9%)<0.001
AMI82(1.7%)144(3.9%)95(6.4%)94(8.3%)85(13.2%)59(14.7%)559(4.6%)<0.001
Shock89(1.8%)78(2.1%)29(1.9%)51(4.5%)44(6.8%)12(3.0%)303(2.5%)<0.001
Peritonitis101(2.1%)78(2.1%)32(2.1%)34(3.0%)25(3.9%)19(4.7%)289(2.4%)<0.001
Ascites75(1.5%)40(1.1%)24(1.6%)15(1.3%)7(1.1%)9(2.2%)170(1.4%)0.245
GI hemorrhage229(4.7%)197(5.3%)101(6.8%)103(9.1%)74(11.5%)51(12.7%)755(6.2%)<0.001
Laboratory data of blood
Hb (n = 12,242)12.30±2.4512.36±2.4911.98±2.5811.56±2.6711.05±2.7510.13±2.7212.08±2.57<0.001
Albumin (n = 6940)3.42±0.743.44±0.733.31±0.723.18±0.723.00±0.733.07±0.673.35±0.74<0.001
Calcium (n = 9455)7.81±1.718.00±1.708.06±1.627.93±1.787.92±1.677.80±1.867.91±1.71<0.001
Uric acid (n = 730)4.98±2.096.42±2.607.26±2.118.34±2.948.73±3.078.38±2.616.67±2.81<0.001
Sodium (n = 12,153)137.36±5.37137.91±5.37137.42±6.19137.56±6.79138.07±7.56137.20±6.72137.59±5.80<0.001
Potassium (n = 12,146)3.98±0.644.03±0.654.10±0.754.23±0.874.34±0.904.46±1.024.07±0.72<0.001
pH (n = 9348)6.89±0.806.82±0.866.82±0.896.92±0.857.01±0.817.27±0.566.89±0.83<0.001
HCO3− (n = 5768)25.14±4.4424.55±4.8223.68±5.1322.55±5.5420.31±5.7720.51±5.8923.84±5.22<0.001
PT (n = 9863)11.49±3.2111.79±5.4112.00±4.7012.91±7.2613.58±7.5012.80±6.7711.93±5.04<0.001
INR (n = 9857)1.09±0.241.12±0.491.15±0.461.23±0.671.30±0.741.20±0.491.14±0.45<0.001
Medications
NSAID2788(57.3%)1858(49.8%)608(40.7%)427(37.8%)204(31.6%)91(22.7%)5976(48.7%)<0.001
ASPIRIN561(11.5%)749(20.1%)391(26.2%)337(29.8%)201(31.2%)130(32.4%)2369(19.3%)<0.001
COX2i541(11.1%)460(12.3%)231(15.5%)154(13.6%)74(11.5%)38(9.5%)1498(12.2%)<0.001
Aminoglycoside2285(46.9%)1651(44.3%)590(39.5%)407(36.0%)218(33.8%)114(28.4%)5265(42.9%)<0.001
Loop diuretics2230(45.8%)1921(51.5%)946(63.3%)816(72.1%)497(77.1%)251(62.6%)6661(54.3%)<0.001
ACEI258(5.3%)347(9.3%)199(13.3%)175(15.5%)96(14.9%)56(14.0%)1131(9.2%)<0.001
ARB679(13.9%)726(19.5%)378(25.3%)371(32.8%)208(32.2%)134(33.4%)2496(20.3%)<0.001
Steroid1022(21.0%)724(19.4%)314(21.0%)223(19.7%)129(20.0%)64(16.0%)2476(20.2%)0.125
Statin264(5.4%)349(9.4%)196(13.1%)167(14.8%)103(16.0%)61(15.2%)1140(9.3%)<0.001
Ranitidine439(9.0%)305(8.2%)113(7.6%)95(8.4%)55(8.5%)22(5.5%)1029(8.4%)0.131
Famotidine869(17.9%)563(15.1%)211(14.1%)200(17.7%)109(16.9%)59(14.7%)2011(16.4%)0.001
BiPAP202(4.1%)129(3.5%)56(3.7%)56(5.0%)53(8.2%)40(10.0%)536(4.4%)<0.001
ICU466(9.6%)345(9.2%)164(11.0%)151(13.4%)135(20.9%)88(21.9%)1349(11.0%)<0.001
Sodium bicarbonate (n = 759)145.58±123.47186.94±221.86156.15±232.77169.35±188.41200.99±232.59173.58±151.50175.69±202.120.308
IV fluid > 1000.c.802(16.5%)669(17.9%)265(17.7%)267(23.6%)212(32.9%)103(25.7%)2318(18.9%)<0.001
With Acetylcyestine220(4.5%)194(5.2%)88(5.9%)78(6.9%)50(7.8%)17(4.2%)647(5.3%)<0.001
Table
Table 2. Univariate and multivariate Cox regression analyses for the risk of acute kidney injury.
Table 2. Univariate and multivariate Cox regression analyses for the risk of acute kidney injury.
UnivariateMultivariable
Odds Ratio95%CIp-ValueOdds Ratio95%CIp-Value
Age1.01 (1.01–1.02)<0.0011.00 (0.99–1.01)0.960
Gender
 FReference
 M1.00 (0.88–1.13)0.954
CKD Stage
IReference Reference
II0.79 (0.67–0.93)0.0040.91 (0.67–1.22)0.528
IIIA1.21 (0.99–1.47)0.0621.19 (0.83–1.69)0.346
IIIB1.84 (1.51–2.23)<0.001 1.42 (1.00–2.02)0.053
IV2.83 (2.28–3.51)<0.001 1.90 (1.29–2.79)0.001
V2.83 (2.17–3.68)<0.001 1.45 (0.95–2.22)0.086
Comorbidity
DM1.60 (1.41–1.81)<0.001 1.05 (0.84–1.32)0.650
HT1.35 (1.19–1.52)<0.001 1.15 (0.91–1.46)0.238
CVA1.26 (1.07–1.47)0.004 0.98 (0.75–1.29)0.901
PAOD1.32 (0.95–1.83)0.093
LC1.33 (1.11–1.58)0.002 0.79 (0.58–1.08)0.141
Liver ca1.30 (1.07–1.58)0.008 1.02 (0.72–1.45)0.899
Colon ca0.90 (0.73–1.11)0.323
Lung ca0.85 (0.72–1.01)0.060
AF1.55 (1.29–1.86)<0.001 1.11 (0.81–1.51)0.514
CAD1.48 (1.28–1.71)<0.001 0.96 (0.72–1.29)0.792
AMI2.09 (1.67–2.62)<0.001 1.18 (0.79–1.77)0.426
Shock3.81 (2.94–4.94)<0.001 2.15 (1.53–3.02)<0.001
Peritonitis1.39 (0.98–1.98)0.063
Ascites1.88 (1.25–2.83)0.0031.55 (0.82–2.91)0.175
GI hemorrhage1.53 (1.23–1.90)<0.001 1.07 (0.78–1.48)0.671
Laboratory data
Hb0.91 (0.89–0.93)<0.001 0.98 (0.95–1.02)0.390
Alb0.52 (0.47–0.57)<0.001 0.88 (0.75–1.04)0.145
Ca0.93 (0.90–0.97)<0.001 0.92 (0.86–0.99)0.025
UA1.10 (1.02–1.19)0.010
NA0.99 (0.98–1.00)0.0451.00 (0.99–1.01)0.969
K1.16 (1.07–1.26)<0.001 1.12 (0.99–1.27)0.071
pH1.32 (1.21–1.44)<0.001 1.18 (0.98–1.42)0.073
HCO3−0.97 (0.95–0.98)<0.001 0.99 (0.98–1.01)0.567
PT1.03 (1.02–1.04)<0.001 1.02 (0.87–1.20)0.821
INR1.43 (1.29–1.59)<0.001 0.87 (0.16–4.59)0.866
Logistic regression. * p < 0.05, ** p < 0.01.
Table
Table 3. Univariate and multivariate Cox regression analyses for the risk of dialysis within 30 days after CCT.
Table 3. Univariate and multivariate Cox regression analyses for the risk of dialysis within 30 days after CCT.
UnivariateMultivariable
Odds Ratio95%CIp-ValueOdds Ratio95%CIp-Value
Age1.02 (1.01–1.02)<0.001 0.99 (0.98–1.00)0.102
Gender
 FReference
 M0.90 (0.75–1.07)0.228
CKD Stage
IReference Reference
II1.47 (1.00–2.18)0.0521.69 (1.00–2.86)0.052
IIIA2.76 (1.81–4.22)<0.001 2.19 (1.20–4.00)0.010
IIIB6.12 (4.19–8.94)<0.001 3.98 (2.32–6.81)<0.001
IV22.02 (15.55–31.19)<0.001 11.06 (6.58–18.58)<0.001
V118.43 (83.83–167.31)<0.001 36.38 (21.58–61.34)<0.001
Comorbidity
DM2.41 (2.03–2.87)<0.001 1.36 (1.02–1.81)0.039
HT1.60 (1.34–1.90)<0.001 0.90 (0.66–1.22)0.488
CVA1.39 (1.12–1.72)0.003 1.08 (0.75–1.53)0.688
PAOD2.67 (1.87–3.79)<0.001 0.79 (0.38–1.64)0.534
LC1.52 (1.20–1.93)0.001 0.99 (0.67–1.44)0.941
Liver ca1.06 (0.79–1.42)0.715
Colon ca0.72 (0.51–1.00)0.051
Lung ca0.41 (0.30–0.56)<0.001 0.60 (0.36–1.00)0.050
AF2.03 (1.61–2.57)<0.001 1.12 (0.75–1.65)0.584
CAD2.09 (1.72–2.53)<0.001 1.05 (0.73–1.51)0.809
AMI2.99 (2.27–3.95)<0.0011.05 (0.64–1.71)0.856
Shock5.00 (3.67–6.81)<0.001 2.16 (1.42–3.29)<0.001
Peritonitis3.13 (2.18–4.51)<0.001 1.35 (0.79–2.31)0.276
Ascites1.97 (1.14–3.44)0.0161.68 (0.76–3.73)0.200
GI hemorrhage1.94 (1.47–2.58)<0.001 0.82 (0.53–1.26)0.359
Laboratory data
Hb0.79 (0.77–0.82)<0.001 0.95 (0.90–1.00)0.038
Alb0.44 (0.38–0.50)<0.0010.66 (0.53–0.83)<0.001
Ca0.95 (0.91–1.00)0.068
UA1.21 (1.11–1.33)<0.001
NA0.99 (0.98–1.01)0.332
K1.48 (1.34–1.64)<0.001 1.12 (0.96–1.31)0.140
PH1.70 (1.48–1.96)<0.001 0.99 (0.79–1.24)0.918
HCO3−0.90 (0.89–0.92)<0.001 1.00 (0.98–1.03)0.940
PT1.03 (1.02–1.04)<0.001 1.30 (1.04–1.61)0.019
INR1.38 (1.23–1.54)<0.001 0.07 (0.01–0.69)0.023
Logistic regression. * p < 0.05, ** p < 0.01.
Table
Table 4. Univariate and multivariate Cox regression analyses for the risk of mortality within 30 days after CCT.
Table 4. Univariate and multivariate Cox regression analyses for the risk of mortality within 30 days after CCT.
UnivariateMultivariable
Odds Ratio95%CIp-ValueOdds Ratio95%CIp-Value
Age1.02 (1.01–1.02)<0.0011.00 (1.00–1.01)0.164
Gender
 FReference Reference
 M1.19 (1.05–1.34)0.006 0.94 (0.77–1.15)0.553
CKD Stage
IReference Reference
II0.98 (0.84–1.15)0.8351.28 (0.98–1.66)0.067
IIIA1.54 (1.28–1.85)<0.001 1.50 (1.09–2.07)0.013
IIIB1.93 (1.59–2.34)<0.001 1.47 (1.06–2.04)0.021
IV2.84 (2.29–3.53)<0.001 2.00 (1.40–2.87)<0.001
V2.47 (1.88–3.24)<0.001 1.79 (1.20–2.68)0.004
Comorbidity
DM1.08 (0.96–1.23)0.209
HT0.91 (0.81–1.03)0.124
CVA0.84 (0.71–1.00)0.045 0.77 (0.60–1.00)0.054
PAOD0.75 (0.50–1.10)0.142
LC1.80 (1.53–2.10)<0.0010.90 (0.69–1.19)0.471
Liver ca2.07 (1.75–2.44)<0.001 1.36 (1.01–1.83)0.042
Colon ca0.81 (0.66–1.01)0.060
Lung ca2.02 (1.77–2.31)<0.001 2.68 (2.10–3.42)<0.001
AF1.29 (1.07–1.55)0.007 0.84 (0.62–1.14)0.260
CAD1.04 (0.89–1.21)0.646
AMI1.48 (1.16–1.89)0.002 1.22 (0.85–1.74)0.288
Shock6.77 (5.34–8.57)<0.001 3.11 (2.28–4.23)<0.001
Peritonitis1.82 (1.33–2.48)<0.001 0.61 (0.39–0.94)0.026
Ascites2.92 (2.05–4.16)<0.0011.47 (0.85–2.55)0.172
GI hemorrhage1.71 (1.40–2.10)<0.001 0.94 (0.70–1.26)0.685
Laboratory data
Hb0.83 (0.82–0.85)<0.001 0.96 (0.93–1.00)0.027
Alb0.34 (0.30–0.37)<0.001 0.54 (0.47–0.63)<0.001
Ca1.00 (0.97–1.04)0.940
UA1.12 (1.04–1.20)0.001
NA0.96 (0.95–0.97)<0.001 0.99 (0.98–1.01)0.367
K1.14 (1.06–1.23)0.001 1.08 (0.96–1.21)0.193
PH1.35 (1.24–1.47)<0.001 1.01 (0.86–1.18)0.932
HCO30.96 (0.95–0.97)<0.001 0.99 (0.98–1.01)0.416
PT1.06 (1.05–1.07)<0.001 1.00 (0.86–1.17)0.965
INR2.00 (1.76–2.27)<0.0011.26 (0.25–6.37)0.782
BilT1.12 (1.10–1.14)<0.001 1.08 (1.05–1.10)<0.001
Logistic regression. * p < 0.05, ** p < 0.01.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Wu, M.-J.; Tsai, S.-F. Patients with Different Stages of Chronic Kidney Disease Undergoing Intravenous Contrast-Enhanced Computed Tomography—The Incidence of Contrast-Associated Acute Kidney Injury. Diagnostics 2022, 12, 864. https://doi.org/10.3390/diagnostics12040864

AMA Style

Wu M-J, Tsai S-F. Patients with Different Stages of Chronic Kidney Disease Undergoing Intravenous Contrast-Enhanced Computed Tomography—The Incidence of Contrast-Associated Acute Kidney Injury. Diagnostics. 2022; 12(4):864. https://doi.org/10.3390/diagnostics12040864

Chicago/Turabian Style

Wu, Ming-Ju, and Shang-Feng Tsai. 2022. "Patients with Different Stages of Chronic Kidney Disease Undergoing Intravenous Contrast-Enhanced Computed Tomography—The Incidence of Contrast-Associated Acute Kidney Injury" Diagnostics 12, no. 4: 864. https://doi.org/10.3390/diagnostics12040864

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop