Takura et al. BMC Nephrology(2023) 24:135
https://doi.org/10.1186/s12882-023-03194-2

BMC Nephrology

Open Access

RESEARCH

Long-term effects of contrast media exposure
on renal failure progression: a retrospective
cohort study
Tomoyuki Takura1* , Kosaku Nitta2, Ken Tsuchiya3 and Hideki Kawanishi4
Abstract
Background With the constant need for technique improvement for ensuring correct diagnoses and precise
treatment, imaging examinations that use contrast media have become unavoidable and indispensable. However, thelong-term effects of contrast media on renal function remain unclear in populations with advanced renal failure. This
study aimed to examine the relationship between contrast media exposure and long-term trends in renal function inpatients with renal failure.
Methods This retrospective cohort study included patients with a definitive diagnosis of chronic kidney disease
who visited medical institutions in Japan between April 2012 and December 2020. The cohort was divided into
contrast agent therapy and non-contrast agent therapy groups. The assessment indices were the number of contrast
exposures and renal function decline. Renal function decline was calculated based on observed chronic kidneydisease stage trends and glomerular filtration rate correspondence tables sourced from various guidelines. A stratified
analysis focusing on changes in renal function while accounting for the acceleration of chronic kidney diseaseprogression was also performed.
Results After adjusting for patient background with propensity score matching, 333 patients each were included inboth groups. The observation period was 5.3 ± 2.1 and 4.9 ± 2.2 years per case in the contrast-enhanced and noncontrast-enhanced groups, respectively. The baseline estimated glomerular filtration rate at the beginning of theobservation period was 55.2 ± 17.8 mL/min/1.73 m2 in the contrast-enhanced groups (P = 0.65). Although only slightly
different in both groups, the glomerular filtration rate change was 1.1 ± 3.3 mL/min/1.73 m2/year in the contrast agent
therapy group and tended to be higher with contrast media exposure. Stratified analysis showed that the annual
glomerular filtration rate changes in patients with more contrast media exposures and altered renal function were
7.9 ± 7.1 mL/min/1.73 m2/year and 4.7 ± 3.6 mL/min/1.73 m2/year in the contrast agent therapy and non-contrast
agent therapy groups, respectively (1.69 times, P < 0.05).
Conclusion We were able to identify a clinical trend of successful measures for preventing adverse renal outcomes
associated with contrast media exposure. However, increased frequency of contrast media exposure has a long-term
effect on renal function in patients with altered it. Appropriate treatment choices related to contrast media may
control chronic kidney disease.

*Correspondence:
Tomoyuki Takura
ttakura@m.u-tokyo.ac.jp
Full list of author information is available at the end of the article© The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use,sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) andthe source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in thisarticle are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not includedin the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you willneed to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The
Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available
in this article, unless otherwise stated in a credit line to the data.

Takura et al. BMC Nephrology(2023) 24:135

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Keywords Long-term effects, Contrast media, Glomerular filtration, Advanced renal failure, Appropriate use criteria,
Big data, Propensity score matching

Background
With the increasing importance of accurate diagnosis
and precise treatment, imaging examinations using contrast media have become unavoidable and indispensable in many disease areas. However, contrast media can
induce hypersensitivity symptoms such as erythema andurticaria immediately after injection, resulting in severe
shock. Despite years of research, the pathogenesis of contrast-induced nephropathy (CIN) remains poorly understood. The risk of CIN development includes chronic
kidney disease (CKD), which occurs in 4–11% of patientswith moderate renal impairment and 50% of patientswith severe renal impairment [1–4]. Management by
rehydration is the primary preventive measure for CIN.
The effects of CIN on renal function are often transient[1, 5]. For example, serum creatinine levels peak at 2–4
days after contrast administration and recover to preadministration values within 2 weeks. In a short-term
post-administration analysis of 90–180 days, contrast
media testing did not affect renal function decline in a
few studies [6–8]. CIN related to percutaneous coronary intervention does not affect the long-term prognosis (death or initiation of permanent dialysis) of Japanesepatients with advanced renal failure [9].
In contrast, renal function decline progresses to thepoint of requiring haemodialysis in some cases. There
are scattered reports that CIN affects renal function
decline in a long-term analysis over 2 years after administration [10–12]. With the increasing prevalence oflifestyle-related diseases, there is growing interest in theprevention of CKD progression and risk factors for CIN,
including diabetes [13]. Contrast agents, which are taxing on the kidneys, and other risk factors, such as diabetes and the use of non-steroidal anti-inflammatory drugs(NSAIDs), are a cause of concern for long-term CKD
progression, mainly because of frequent contrast studies
and imaging-based treatments for chronic diseases [10].
As described above, concerns have been raised regarding the long-term prognosis of the effect of contrast
media on renal function, but sufficient data have not been
accumulated. In particular, the effects of contrast media
on CIN development and the long-term prognosis (follow-up period of 5 years or more) of CKD have not been
fully investigated in populations with advanced renal failure. Therefore, we examined the relationship between
medical intervention with contrast media and long-term
trends in renal function in patients with renal failurefrom the perspective of preventing CKD progression.
The present study aimed to analyse the long-term
effects of contrast media exposure in the field of CKD,

which is of great social concern due to its high disease and economic burdens, and to compile basic datathat will contribute to the study of preventive measuresagainst its progression. The obtained results will indirectly contribute to the development of medical strategies for the application of contrast media testing andstudy of disease mechanisms, such as CIN.

Methods
Research design

This study was a retrospective cohort study (data science)that applied medical big data (TheBD: The Tokyo University Health Economy Big Data) for real-world evaluation.
The study data were collected from April 2012 to December 2020, and the target population included patientsdiagnosed with CKD (International Classification of
Diseases, 10th edition [ICD-10] code: N18) who visited
medical institutions (examination and treatment intervention) in Japan. CKD is defined as ‘renal impairment
evident by urinalysis, blood tests, or imaging’; ‘glomerular filtration rate (GFR) less than 60 ml/min/1.73 m2’, orboth of these findings for at least 3 months. The exclusion criteria were as follows: (1) individuals aged < 20years who had congenital renal disease; (2) individuals
receiving renal replacement therapy; and (3) individuals
with cancer (within 3 years prior to observation), except
for renal cancer, which was excluded from the sample ofpatients with cancer. Samples for which the use of iodine
contrast media could not be correctly determined werealso excluded. We adhered to the STROBE guidelines forthis cohort study.
The cohort was divided into contrast agent therapy(CAT, contrast-enhanced treatment) and non-contrast
agent therapy (non-CAT, non-contrast-enhanced treatment) groups for laboratory and therapeutic interventions while considering the risk factors for CKD, suchas hypertension, diabetes, medications (e.g., analgesics
and antihypertensive drugs), age, and sex. Renal function
decline was calculated from the correspondence tablebetween the CKD stage (KDIGO 2012: G1–G5) and GFRreference values (CKD Practice Guide 2012: mL/min/1.73m2) [14, 15]. The endpoints were the number of contrast
exposures, regardless of contrast route and dose, andrenal function derangement. They were analysed in unitsof annual averages divided by the observation period,
accounting for the timing of reciprocal occurrences. The
framework was a long-term longitudinal study based on
disease characteristics and study objectives. The average
analysis period was 5 years, with a minimum observation
period of 6 months or longer.

Takura et al. BMC Nephrology(2023) 24:135

Study data sourceThis study used a large database that includes medical
service data examined by a specialised public organisation (Social Insurance Medical Fee Payment Fund), in
accordance with the format stipulated by the Ministryof Health, Labor and Welfare (MHLW Notification: Vol.
0831 No. 1). We selected medical economic big data
(TheBD; S1 Table), [16, 17] which included medical service bills in Japan between April 2012 and March 2021,
representing the coverage for 7 million insured patients.
The present study was conducted in accordance withthe principles embodied in the Declaration of Helsinki.
This study received comprehensive approval in March
2019 from the Institutional Review Board of the University of Tokyo Hospital (screening no: 2018167NI,
approval date: March 26, 2019). Because we used database records (anonymized) for analysis, the requirement
for the acquisition of informed consent from patients waswaived at the above Institutional Review Board (opt-out
format).
The largest proportion of the sample was from theyear 2016 (22.1%). Medical information accounted
for 6.18 million results while dispensing informationaccounted for 6.20 million results (including duplications). The patient-based hospitalisation rate was 13.5%(including duplications), and the average percentage ofmale patients for all years was 46.8%. This database is
updated every 6 months. All data on disease name, testing, medication, surgery, and any other medical interventions with dates of initiation and related costs are linked
in chronological order using unique IDs for each patient.
During each biannual update, the transfer of data for
insured persons is managed, and adjustments are madeaccording to the allocation of medical facilities. TheBD
has been used in several studies evaluating the economic
aspects of medical interventions (S2 Table).
Selection conditions for research subjects

For cases that met the abovementioned selection criteria
but did not meet the exclusion criteria, we defined theobservation period to be at least 6 months from the dateof the first diagnosis of CKD stage. Injuries were identified by the ICD-10 code (N18) and CKD stage (injuryname).
The analysis period was from the date when the CKD
stage injury was first identified (index day) or the date ofdata generation, whichever was earlier, to the date whenrenal replacement therapy was initiated. We observed
hemodialysis, peritoneal dialysis, and renal transplantation interventions as renal replacement therapies. For
patients who did not receive renal replacement therapy,
the analysis period was up to the date of the last identifiable CKD stage injury (end date).

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Data extraction was performed on the six components(conditions) listed in the ‘Extraction conditions’ tableshown in Fig. 1. We first selected patients (15095 cases)
with renal failure that met the selection criteria fromthe medical big data (Fig. 1). We then excluded thosethat met the exclusion criteria, for a final sample of 1366
cases. We classified this population into CAT and nonCAT groups according to contrast exposure. The patient
background in both groups was adjusted for major risk
factors for renal function by applying the propensity
score matching (PSM) method.
Thus, this study included 333 patients in the CAT
and non-CAT groups, totalling to 666 patients. In thisstudy, most CATs were imaging tests. We also performed a stratified analysis focusing on the group withaltered renal function (260 patients; 39.0%), while taking the acceleration of CKD progression into account.
For the stratified analysis (260 patients), the decline inrenal function group was selected from the basic analysis
cohort (666 patients). After processing PSM, the analysis
included 63 patients in each group, totalling 126 patients.
We calculated the cut-off value of renal function
decline for CAT from the receiver operating characteristic (ROC) curve in the stratification analysis.
Evaluable interventions and precautionary conditions

The interventions evaluated in this study were practices
involving iodine contrast media. All iodine contrast
media approved in Japan were included in the evaluation.
Iodine contrast media are classified into two types:
water-soluble and oil-based. Water-soluble contrast
media are used in patients with normal renal function.
Approximately 90% is excreted as urine from the kidneys at approximately 6 h after injection. In contrast,
oil-based iodine contrast media can remain in the bodyfor a long period. These two types of contrast media areused separately according to the purpose of the examination. Water-soluble contrast media are selected in mostcases. Water-soluble contrast media can be further classified into ionic and non-ionic contrast media. Comparedwith ionic contrast media, non-ionic contrast media havelower osmotic pressure and are more similar to blood,
which alleviates the symptoms of adverse reactions, suchas the burning sensation experienced during injection.
In Japan, non-ionic contrast media are most commonlyused in angiography.
During the examination of contrast exposure and its
impact on renal function, the amount of contrast media
injected into the body is of importance. However, thedata source for this study is based on information frommedical claims, which provides information on product consumption but not on internal infusion volume.
In addition, information on weight and detailed imaging type of the subject cases is essential for determining

Takura et al. BMC Nephrology(2023) 24:135

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Fig. 1 Structure of this study: basic flow of data set and main analysis conditions
PSM, propensity score matching

the internal infusion volume. However, due to the large
uncertainty, there were limitations regarding the organisation of this information.
The rehydration (saline) volume was categorised bydrug category (code 331), and the cumulative volume(in mL/year) within the observation period was calculated. Consistency was also maintained for rehydration
on a yearly basis in relation to the analysis of time-serieschanges in renal function. This volume was calculated
from the volume set for each drug name, as there wasvariation in the volume or number of times that it wasused, depending on the case or prescription. Furthermore, if the frequency was two or more times, it was further corrected by considering the frequency in addition
to the calculated amount used. The figures for this calculation are the product consumption, not the injectable
volume.
Main analysis methods and assessment of renal function

The Mann–Whitney U test was used to evaluate theeffect of iodine contrast media use on renal function, andthe chi-square test was used along with the previouslyTakura et al. BMC Nephrology(2023) 24:135

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Table 1 CKD stage to GFR conversion
Item
CKD stage
GFR criteria (mL/min/1.73 m2)
Amount of decline in renal function associated with changes in CKD stage (ΔGFR)aConversion of GFR from CKD stage
G1
G2
G3a
G3b
100
89
59
44
11
30
15
15

G4
29
15

G5
14
9

G5Da
5
―

Renal replacement therapy, haemodialysis, peritoneal dialysis, renal transplantation

described test to compare patient background. The significance level was set at 5%. We calculated Pearson’s correlation coefficient to assess the correlation between thenumber of contrast media used and the decline in renal
function. Multivariate analysis of risk factors for renal
function was performed using logistic regression analysis. Statistical analysis was performed using SPSS version
26.0 (IBM Corp., Armonk, New York). The figures in thetables are presented as means and standard deviations,whereas the figures are presented as standard errors.
PSM was used to minimise bias related to patient background. Therefore, the forced entry method was chosen
for the multivariate logistic regression model. The independent variables (covariates) were age, sex, hypertension/diabetes, use of NSAIDs, antimicrobial agents,
antineoplastic agents, and others. Propensity scores foreach case were calculated, and a 1:1 matching method
was applied to align the sample numbers and confirm thedata distribution and balance in both groups. Among theindependent variables (covariates), age was defined as thedate of CKD stage; hypertension was diagnosed within
the observation period; and the use of NSAIDs, antimicrobial agents, and antineoplastics within the observation period was defined as the scope of analysis.
The GFR in each case was converted from the GFR category correspondence table of CKD severity classification based on the observed CKD stage in ICD-10 codesin this study. Furthermore, we estimated the decline inrenal function associated with changes in CKD stage
from the CKD stages and GFR levels in previous studies[18–21]. The underlying data used for the conversion are
shown in Table 1. The annual change in estimated GFR
was calculated as follows: [ΔGFR: estimated GFR (index
day) - estimated GFR (end date)] / [duration: observation period]. When some information regarding the CKD
stage was missing, estimates were made based on preand post-stage data.

Results
Basic analysis of the whole population

The analysis population comprised 1366 patients (CATgroup: n = 369, non-CAT group: n = 997). After adjusting for patient background with PSM, 333 patients (age:55.6 ± 9.0, male percentage: 70.5%) were included in the
CAT group, whereas 333 patients (age: 56.0 ± 8.6, malepercentage: 73.0%) were included in the non-CAT group(P = 0.48 and 0.55 for age and sex, respectively) (Table 2).

Figure 2 shows the covariates before and after matchingby PSM in both groups. The duration of observation was
5.3 ± 2.1 and 4.9 ± 2.2 years per case in the CAT and nonCAT groups, respectively (P < 0.05). The mean numberof contrast exposures was 2.4 ± 2.4 per case (mean per
year: 0.45 per case). The volume of contrast media was
46.2 ± 54.6 mL/procedure/year. The baseline estimated
GFR at the beginning of observation was 55.2 ± 17.8 mL/
min/1.73 m2 and 53.3 ± 15.2 mL/min/1.73 m2 in the CAT
and non-CAT groups, respectively (P = 0.65).
The underlying cause of renal failure was glomerulonephritis in 15.9% and 18.6% of the patients in the
CAT and non-CAT groups, respectively (P = 0.36). Diabetic nephropathy was observed in 8.4% and 6.3% of thepatients in the CAT and non-CAT groups, respectively(P = 0.30). Concomitant hypertension was observed in
84.1% and 86.8% of the patients in the CAT and nonCAT groups, respectively (P = 0.32). The main drugs were
NSAIDs in 62.8% and 60.4% of the patients in the CAT
and non-CAT groups, respectively (P = 0.52); antihypertensives in 75.7% and 76.9% of the patients in the CAT
and non-CAT groups, respectively (P = 0.72); and antidiabetic drugs in 31.2% and 29.1% of the patients in the CAT
and non-CAT groups, respectively (P = 0.56).
Disease prevention interventions were performed in
1.8% and 1.2% of the patients in the CAT and non-CAT
groups (P = 0.52), respectively, for lifestyle guidance (comprehensive management including education). The rehydration volume was 1689 ± 3399 mL/year and 289 ± 900mL/year in the CAT and non-CAT groups, respectively(P < 0.01).
The final CKD stage during the observation period was
12.9% and 14.1% (P = 0.65) in renal replacement therapy(G5D); 4.2% and 5.7% (P = 0.37) in G5; 10.2% and 11.4%(P = 0.62) in G4; 16.5% and 12.3% in G3b; and 40.8% and39.3% (P = 0.69) in G3a in the CAT and non-CAT groups,
respectively.
Logistic regression analysis of this population, withrenal function decline (presence or absence of declined
renal function during the observation period) as theobjective variable, resulted in an odds ratio of 1.01 (95%
confidence interval: 1.01–1.01, P < 0.05) for the cumulative contrast media usage in the observation period(Fig. 3). Thus, the annual GFR change was 1.1 ± 3.3 mL/
min/1.73 m2/year and 0.9 ± 2.5 mL/min/1.73 m2/year in
the CAT and non-CAT groups (P = 0.91), respectively(Fig. 4 ). It was implied that an increase in contrast media

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Table 2 Basic analysis of patient background and various interventions
Parameter

CAT group

Non-CAT groupP-value

Sample (n)Age (years)
Sex: male (%)
Observation period (years)
Baseline estimated GFR (mL/min/1.73 m2)

333
55.6
70.9
5.3
55.2

333
56.0
73.0
4.9
53.3

0.48
0.55
0.04
0.65

Diabetic nephropathy (%)
Glomerular nephritis (%)
Nephrosclerosis (%)
Hypertension (%)
Diabetes (%)

8.4
15.9
4.8
84.1
39.0

Number of contrast agent exposures (time/year)
Amount of contrast agent (mL/year)
Amount of rehydration (mL/year)

2.4
46.1
1689.5Hyperkalaemia drug (%)
Phosphate binder (%)
Erythropoiesis-stimulating agent (%)
Spherical carbon adsorbent (AST-120) (%)
Antihypertensive (%)
Diuretic (%)
Diabetes drug (%)
Non-steroidal anti-inflammatory drug (%)
Antibacterial drug (%): Aminoglycosides, Glycopeptides, Others

12.9
6.6
15.0
6.6
75.7
37.5
31.2
62.8
9.6

14.7
8.1
18.0
11.1
76.9
28.8
29.1
60.4
7.2

0.50
0.46
0.30
0.04
0.72
0.02
0.56
0.52
0.26

Revascularisation (%)
Cardiovascular implantable electronic device, others (%)
Heart valve replacement, valvuloplasty (%)

2.4
1.2
0.3

0.0
0.6
0.0

0.05
0.77
0.85

3.6

1.8

0.69

2.7
12.6
40.8
16.5
10.2
4.2
12.9

2.7
14.4
39.3
12.3
11.4
5.7
14.1

1.00
0.50
0.69
0.12
0.62
0.37
0.65

Case
±

8.6

±
±

2.1
17.8

±

8.6

±
±

2.2
15.2

Main disease
6.3
18.6
4.8
86.8
36.9

0.30
0.36
1.00
0.32
0.58

289.0

―
―
< 0.01

Contrast agent
±
±
±

2.4
54.6
3399.7±900.9

Main medicine

Main surgery

Main prevention
Lifestyle disease prevention (education, guidance) (%)
CKD stage (final in the observation period: end day)G1 (%)
G2 (%)
G3a (%)
G3b (%)
G4 (%)
G5 (%)
G5D (%)

exposure might have an increased effect on renal function decline. For example, the population with more than
0.3 contrast media exposures per year had a decline inrenal function to 1.3 ± 4.2 mL/min/1.73 m2/year in the
CAT group.
Stratified analysis of the group with altered renal function

In the renal function decline group, the target population
for stratified analysis, 63 patients (age: 54.4 ± 9.0, maleratio: 71.4%) were in the CAT group, and 63 patients (age:54.5 ± 7.9, male ratio: 77.8%) were in the non-CAT group(P = 0.93 and 0.41 for age and sex, respectively) after

adjusting for patient background with PSM (Table 3).
Figure 5 presents the pre- and post-matching covariates
for both groups by PSM. The observation period was
5.1 ± 2.0 years and 4.6 ± 1.8 years per case in the CAT and
non-CAT groups (P = 0.16), respectively. The mean number of contrast exposures was 1.9 ± 1.7 per case (mean per
year: 0.37 per case). The volume of contrast media was
40.1 ± 54.1 mL/procedure/year.
The baseline estimated GFR at the beginning of observation was 42.1 ± 46.6 mL/min/1.73 m2 and 31.5 ± 41.4
mL/min/1.73 m2 in the CAT and non-CAT groups

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Fig. 2 Pre- and post-matching covariates for both groups by PSM (in the basic analysis)(P = 0.22), respectively. The GFR level of the non-CAT
group was lower than that of the CAT group in baseline.
The underlying cause of renal failure was diabetic
nephropathy in 27.0% and 20.0% of the patients in the
CAT and non-CAT groups (P = 0.40), respectively, andglomerulonephritis in 22.2% and 12.7% of the patientsin the CAT and non-CAT groups (P = 0.16), respectively.
Concomitant hypertension was observed in 98.4% and100.0% of the patients in the CAT and non-CAT groups,
respectively (P = 1.00). The main drugs were NSAIDs in
57.1% and 58.7% (P = 0.86) and antihypertensive drugs in
88.9% and 95.2% (P = 0.19) of the patients in the CAT and
non-CAT groups, respectively. Other major therapeuticinterventions included revascularisation (e.g., percutaneous coronary intervention) (12.4%), cardiovascularTakura et al. BMC Nephrology(2023) 24:135

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Fig. 3 Odds ratios of each covariate for renal function decline (logistic regression, n = 666)
NSAID, non-steroidal anti-inflammatory drug. OR, odds ratio
Note: Age: year, Sex: binary (Male), Cumulative contrast agent usage: mL/year, Analgesics: binary, Antimicrobial agents: binary, Ischemic heart disease:binary, Type 2 diabetes: binary, Rehydration: mL/year

Fig. 4 Annual GFR decline by contrast exposure (basic analysis, after PSM,n = 666)
SE: standard error

implantable electronic device (6.9%), and valve replacement/valvuloplasty (2.2%).
Disease prevention interventions accounted for 6.3%
and 3.2% in the CAT and non-CAT groups (P = 0.68),
respectively, for lifestyle guidance (mostly diabetes dialysis prevention guidance and management). The rehydration volume was 3983 ± 5635 mL/year and 969 ± 1264
mL/year in the CAT and non-CAT groups, respectively(P < 0.01).
In the renal function decline group, the annual GFRchange was 5.8 ± 5.6 mL/min/1.73 m2/year and 4.7 ± 3.6

mL/min/1.73 m2/year in the CAT and non-CAT group,
respectively (P = 0.18) (Fig. 6). Building on the supporting
results of the basic analysis, we also attempted an analysis in a population with high exposure to contrast media.
The cut-off value for renal function decline for CAT
was in the 0.2 range (times/year, area under the curve:
0.74, 95% CI: 0.62–0.86, P < 0.01). We set a cut-off valueof 0.2 times/year as a conservative estimate. Although
limited by the small sample size (n = 32), in the population with more than 0.2 contrast exposures per year, theCAT group accounted for 7.9 ± 7.1 mL/min/1.73 m2/year(P < 0.05) (Fig. 7).
Correlation analysis showed that the number of contrast media exposures per year was statistically significantly positively correlated with the annual GFR change(r = 0.51, P < 0.01) (Fig. 8).

Discussion
Notwithstanding the limitations surrounding the collection of information on patient background, test results,
some aspects of the clinical picture, and statistics, thisstudy, oriented towards real-world considerations in theJapanese health care system, clarified the actual longterm effects of contrast media exposure on renal function. Thus, we were able to identify a clinical trend of
successful measures for preventing renal outcomes associated with contrast media exposure. We subsequently
found that contrast exposure under certain conditions
is a potential long-term influencing factor on renal
function.

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Table 3 Stratified analysis of patient background and various interventions (population with renal function displacement)
Parameter

CAT group

Non-CAT groupP-value

Case
Sample (n)Age (years)
Sex: male (%)
Observation period (years)
Baseline estimated GFR (mL/min/1.73 m2)
DiseaseDiabetic nephropathy (%)
Glomerular nephritis (%)
Nephrosclerosis (%)
Hypertension (%)
Diabetes (%)
Contrast agent
Number of contrast agent exposures (time/year)
Amount of contrast agent (mL/year)
Amount of rehydration (mL/year)
Main medicine
Hyperkalaemia drug (%)
Phosphate binder (%)
Erythropoiesis-stimulating agent (%)
Spherical carbon adsorbent (AST-120) (%)
Antihypertensive (%)
Diuretic (%)
Diabetes drug (%)
Non-steroidal anti-inflammatory drug (%)
Antibacterial drug (%): Aminoglycosides, Glycopeptides, Others
Anticancer drug (%)
Main surgery
Revascularisation (%)
Cardiovascular implantable electronic device, others (%)
Heart valve replacement, valvuloplasty (%)
Main prevention
Lifestyle disease prevention (education, guidance) (%)

63
54.4
71.4
5.1
42.1

±

9.0

±
±

2.0
46.6

27.0
22.2
1.6
98.4
60.3
1.9
40.1
3983.4

±
±
±

1.7
54.2
5635.8

63
54.5
77.8
4.6
31.5

±

7.9

±
±

1.8
41.4

0.93
0.41
0.16
0.22

20.6
12.7
6.3
100.0
61.9

0.40
0.16
0.37
1.00
0.86

969.1

―
―
< 0.01±1264.9

42.9
30.2
63.5
27.0
88.9
69.8
58.7
57.1
15.9
1.6

49.2
39.7
69.8
36.5
95.2
58.7
55.6
58.7
11.1
1.6

0.48
0.26
0.45
0.25
0.19
0.19
0.72
0.86
0.43
1.00

12.1
6.9
2.2

0.0
0.9
0.0

< 0.01< 0.01
0.06

6.3

3.2

0.68

Note: Most CATs in this study were imaging tests. Therefore, descriptions in this table focused on therapeutic interventions

Although study design limitations require careful interpretation, the results of longitudinal observations overapproximately 5 years have implied that, as with otherrisk factors, the number of contrast exposures has along-term effect on renal function. The results of PSMadjusted stratified analysis (G3b-centred group withaltered renal function) showed that the decrease in GFR
in the CAT group was 1.69-fold greater than that in the
non-CAT group in the population with high annual contrast exposure. Therefore, it was inferred that the strategy
of selecting appropriate contrast-enhanced medical treatment is important as a part of CKD measures in moderate CKD and beyond.
The population in this study consisted of CKD patients
at high risk of CIN, particularly those in CKD stage G3
and beyond. For urgent diagnosis and treatment in thispopulation, the choice is generally based on a balanceof clinical risks and benefits while protecting the renal

function [6]. In the present study, we could not examine the amount of contrast media injected into the bodyand the type of intervention and route of administration in detail. Consequently, we did not discuss in detailthe causal relationship between the amount of contrast
media exposure and the amount of decline in renal function. Therefore, the results of this study are consideredinsufficient to contribute to the discussion of clinicaldecisions as described above. In the future, long-termclinical studies with multivariate analysis of relevant factors (serum creatinine, serum albumin, body mass index,
saline, etc.) are desirable [9, 22].
CKD is a concept regardless of the underlying disease,and treatment principles, such as blood pressure, blood
glucose control, and salt reduction guidance, remaincommon [23]. In this study, while comparing the CAT
and non-CAT groups, the main risk factors for CKD were
adjusted for both groups using PSM. This adjustment

Takura et al. BMC Nephrology(2023) 24:135

Page 10 of 13

Fig. 5 Pre- and post-matching covariates for both groups by PSM (stratified analysis)

excluded lifestyle guidance (including nutritional management, exercise therapy, etc.), which is expected to prevent renal failure progression; however, as a result, there
was no significant difference between the two groups. In
contrast, factors related to daily life could not be considered due to a lack of data. Further, the proportion ofpatients in the non-CAT group was significantly higher
than that in the CAT group due to insufficient adjustment

for AST-120, which inhibits renal failure progression in
the two groups. These uncertainties must be consideredwhen interpreting the results of this study. In the future,
the new and old prophylactic effects on contrast media
exposure must be extensively examined, considering thetrend of N-acetylcysteine and others [24, 25].
Although limited by the small sample size, in the analysis of the present study, a more pronounced trend wasTakura et al. BMC Nephrology(2023) 24:135

Page 11 of 13

Fig. 8 Correlation analysis between the yearly number of contrast exposures and annual GFR change (stratified analysis)Fig. 6 Comparison of annual GFR change by contrast exposure (stratified
analysis, after PSM, n = 126)

Fig. 7 Comparison of annual GFR change (stratified analysis, population
with > 0.2 contrast exposures per year)

observed in the groups with greater renal failure progression or a higher number of exposures to contrast media.
This trend was also significant in the correlation analysis
between the frequency of exposure and renal function

decline. In contrast, the frequency of exposure in thegroup with greater renal function derangement was lower
than that in the population as a whole. Considering therelationship between the baseline renal function andrenal outcome of contrast exposure, as well as previous
reports referring to the relationship between CKD and
CIN, the aforementioned trends reiterate the importanceof patient background (severity and comorbidity) in theanalysis, as well as the clinical significance for the prevention of CKD progression and the use of contrast media [4,
26–28]. The results of this study were interpreted in thesame way as the results of the previous study. Therefore,
consideration should be given to the possibility that the
CAT group has an inherent bias in terms of the severityof renal failure and the need for therapeutic intervention,
and a multifaceted discussion of the level of accelerationof CKD progression is also desirable.
Although not many reports have focused on the acceleration of CKD progression, small doses of iodine contrast media (median: 12 mL/dose) for patients withadvanced renal failure after stage G4 did not affect therenal outcome; however, an average monthly reductionof 0.14 mL/min/1.73 m2 was observed in the eGFR [7].
In the present study, in the overall population, including
patients with low exposure, there was no significant difference between the two groups, with an average monthly
decrease in progression acceleration of 0.07 mL/min/1.73
m2 and 0.09 mL/min/1.73 m2 in the non-CAT and CAT
groups, respectively. In contrast, in the population withhigher exposure frequency, the progression accelerationin the CAT group increased to 0.11 mL/min/1.73 m2. A

Takura et al. BMC Nephrology(2023) 24:135

significant effect of contrast exposure (0.48 mL/min/1.73
m2/month) was observed in the advanced renal failuregroup (stage G3b or later) with a higher frequency ofcontrast exposure. Thus, the progression acceleration of
CKD is more pronounced in patients with higher contrast exposure [2–4].
For example, a common renal injury caused by NSAIDs
is ischemic nephropathy due to cyclooxygenase inhibition, presenting with acute renal injury. In addition
to ischemic nephropathy, acute interstitial nephritis,
nephrotic syndrome with interstitial nephritis, andacute tubular necrosis may develop. Previous studies
have shown conflicting results, but the overall long-term
administration has a significant effect on renal function[29–31]. As shown in the examples above, it is necessary
to clearly define factors such as long-term administrationand one-time administration; however, it is difficult tocomprehensively deal with the effects of administrationintervals and doses for each drug type. Our study did not
adjust for patient characteristics to account for the duration of other medications. This point represents one of
the limitations of this study.
Although this study examined iodine contrast media,
other interventions that may have long-term effects onrenal function warrant further investigation. For example, fluorescent angiography using sodium fluorescein
dye is generally considered safe for patients with renal
disease, although there have been scattered reports on
the risk of inducing CIN [32]. It is expected that some offindings of this study will be utilised in such exploratory
discussions in the CKD field. The data science researchthat can be developed relatively efficiently is highly significant in organising the basic data to contribute to theinitial hypothesis testing and study design. The resultsof this study will be useful for further discussion in the
future, as disease control measures are important fromclinical and economic perspectives.

Conclusion
The present study was a longitudinal observation of thefrequency of contrast media exposure and renal function
decline over 5 years. As a result of this study, it was clarified that preventive measures against the decline in renal
function associated with contrast media exposure areclinically successful over the long term. The results also
imply that the number of contrast administration interventions has a long-term effect on the renal function,
similar to other risk factors. However, careful interpretation is required due to analytical limitations. Nonetheless, it can be inferred that the promotion of appropriate
practice choices related to contrast media is even more
important as part of CKD control measures in moderate
CKD and beyond.

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Abbreviations
CIN	Contrast-induced nephropathy
CKD	Chronic kidney disease
NSAIDs	Non-steroidal anti-inflammatory drugs
ICD-10	International Classification of Diseases, 10th editionCAT	Contrast agent therapy
non-CAT	Non-contrast agent therapy
GFR	Glomerular filtration rate
MHLW	Ministry of Health, Labor and Welfare
TheBD	The Tokyo University Health Economy Big Data
PSM	Propensity score matching
ROC	Receiver operating characteristic

Supplementary Information

The online version contains supplementary material available at https://doi.
org/10.1186/s12882-023-03194-2.
Supplementary Material 1
Acknowledgements
This manuscript received great help from Dr. Tomoaki Kobayashi. Ms.
Eri Yoshida, who works with Nihon Medi-Physics Co., has made a great
contribution to this study, including her own training in data analysis andcharting. This manuscript was preliminarily presented in part at the poster
session of WCN’22.
Author Contribution
Study design: TT and KN. Data acquisition: TT. Data analysis and interpretation:
TT, KN, HK. Drafting of the manuscript: TT and KN. Critical revision of themanuscript for intellectual content: HK, KT. As the corresponding author, TT
has had full access to the data in the study and holds the final responsibility
for the decision to submit for publication. All authors have approved the final
version of the manuscript.
Funding
This research did not receive any specific grant from funding agencies in the
public, commercial, or not-for-profit sectors.
Data Availability
The datasets used and/or analysed during the current study are available fromthe corresponding author on reasonable request.

Declarations
Competing interests
T.T. received grants from Nihon Medi-Physics Co., Ltd. and Fujifilm Toyama
Chemical Co., Ltd. H.K. received speaking honorarium from Kyowa-Kirin, Co.
Ltd., Nipro Co. Ltd., and JMS Co. Ltd. The other authors declare that they haveno conflicts of interest to disclose.
Ethics approval and consent to participate
This study received comprehensive approval in March 2019 from theInstitutional Review Board of the University of Tokyo Hospital (screening no:2018167NI, approval date: March 26, 2019). Because we used database records(anonymized) for analysis, the requirement for the acquisition of informed
consent from patients was waived at the Institutional Review Board of the
University of Tokyo Hospital (opt-out format).
Consent for publication
Not applicable.
Author details
1
Department of Healthcare Economics and Health Policy, Graduate
School of Medicine, The University of Tokyo, 7-3-1, Hongo, Bunkyo,
Tokyo 1138655, Japan2
Department of Medicine, Kidney Centre, Tokyo Women’s Medical
University, 8-1, Kwadacho, Shinjuku, Tokyo 1628666, Japan3
Department Blood Purification, Kidney Centre, Tokyo Women’s Medical
University, 8-1, Kwadacho, Shinjuku, Tokyo 1628666, Japan

Takura et al. BMC Nephrology(2023) 24:135

Page 13 of 13

Tsuchiya General Hospital, 3-30, Nakajimacho, Naka-ku,
Hiroshima 7308655, Japan

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