Abstract
Intravascular administration of iodinated contrast media can cause contrast-induced acute kidney injury, especially in patients with an estimated glomerular filtration rate (eGFR) less than 30 mL/min/1.73 m2. The American College of Radiology (ACR) and the European Society of Urogenital Radiology (ESUR) guidelines recommend renal function screening based on medical history, but their effectiveness has been under-evaluated. This retrospective study included 2,560 consecutive adult outpatients without eGFR measurements within 180 days before contrast-enhanced computed tomography (CT) at a single tertiary hospital from July through September 2023. On the day of CT, they underwent eGFR tests and 1.1% had an eGFR < 30 mL/min/1.73 m2, preferentially with histories of gout and renal disease. According to the ACR and ESUR strategies, 16.9% and 38.8% of all study participants were positive, respectively, identifying 92.6% and 96.3% of patients with renal insufficiency. Both strategies demonstrated high negative predictive values. These results support selective renal function screening before contrast-enhanced examinations.
Keywords: Contrast-Induced Acute Kidney Injury, Estimated Glomerular Filtration Rate, Renal Insufficiency, Renal Function Screening, Outpatient
Graphical Abstract
Iodinated contrast media (ICM) is a critical pharmaceutical in modern radiology, with annual use expected to exceed 100 million patients worldwide.1 The intravascular administration of ICM is mostly safe, but can cause a sudden decline in renal function, referred to as contrast-induced acute kidney injury (CI-AKI). Given its potent impact on morbidity and mortality when occurred,2,3 it is crucial to prevent the development of CI-AKI.
Several risk factors are proposed for CI-AKI, and pre-existing renal insufficiency is known to be the most important.4,5,6,7,8 There has been no clear consensus on the degree of renal insufficiency at which ICM exposure becomes a significant nephrotoxic factor leading to CI-AKI. Recent studies, however, have identified an estimated glomerular filtration rate (eGFR) of 30 mL/min/1.73 m2 as the threshold of independent risk factor for CI-AKI.9,10
To effectively identify high-risk patients before intravascular ICM administration, the 2023 American College of Radiology (ACR) and the 2018 European Society of Urogenital Radiology (ESUR) guidelines recommend renal function screening based on the medical history of patients.8,11 However, these guidelines have rarely been validated,12,13 and despite having different screening indications, no comparison of their effectiveness has been conducted.
In this study, based on a single-center cohort of outpatients who underwent contrast-enhanced computed tomography (CT) examinations, our aims were to investigate the prevalence of renal insufficiency, identify associated risk factors, and validate the effectiveness of the ACR and ESUR screening strategies.
The cohort was generated during the 2023 imaging examination appropriateness assessment conducted by the Health Insurance Review and Assessment Service (HIRA). HIRA, an organization responsible for reviewing medical fees and evaluating the quality of healthcare in South Korea, investigated the renal function assessment rate within 180 days before contrast-enhanced CT examinations from July through September 2023. During this period, we identified all consecutive adult outpatients without renal function test results within 180 days before the CT examinations performed at a single tertiary hospital. These patients were required to undergo renal function tests 2 hours prior to CT given the HIRA’s investigation policy (Fig. 1). Patients with an eGFR < 30 mL/min/1.73 m2 were instructed to receive pre- and post-examination hydration in a day care center or outpatient infusion room, if alternative examination was not feasible. Renal function was reassessed 2–3 days later (Fig. 2).
Fig. 1. Timeline for eGFR testing prior to contrast-enhanced CT examinations.
eGFR = estimated glomerular filtration rate, CT = computed tomography.
Fig. 2. Flow diagram for outpatients with an eGFR less than 30 mL/min/1.73 m2 before contrast-enhanced CT examinations.
CT = computed tomography, eGFR = estimated glomerular filtration rate.
Baseline characteristics, including age, sex, patients’ medical conditions, and medication, were ascertained by reviewing consent forms obtained for contrast-enhanced CT examinations. Medical personnel collected histories of asthma, allergy, gout, hyperthyroidism, diabetes mellitus, hypertension, and heart and renal diseases during the informed consent process. Renal disease history includes known chronic kidney disease, a remote history of AKI, dialysis, kidney surgery, kidney ablation, or albuminuria according to the ACR and ESUR guidelines,8,11 however, it was not classified in detail within the consent form.
The study population was dichotomized into patients with an eGFR < 30 mL/min/1.73 m2 and others. The χ2 and Fisher exact tests were used for group comparisons. Univariate and multivariate logistic regression analyses were performed to identify potential risk factors for severe renal insufficiency. We checked whether the ACR and ESUR screening strategies identified patients with an eGFR < 30 mL/min/1.73 m2 and calculated test performance parameters including sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (LR+). and negative likelihood ratio (LR−). P values < 0.05 were considered statistically significant. All analyses were performed using SPSS v. 29.0 (IBM Corp., Armonk, NY, USA).
This retrospective cohort study included 2,560 outpatients (median age, 62 years; 1,058 men). Of these, 1.1% (95% confidence interval [CI], 0.7–1.5%; 27 patients) had an eGFR < 30 mL/min/1.73 m2 (Table 1). Many of the patients in this group had renal diseases (88.9%; 24/27), and this group exhibited a higher prevalence of gout, diabetes, hypertension, heart disease, and renal disease than their counterparts. A multivariate analysis (Table 2) showed significant associations between histories of gout and renal disease and eGFR < 30 mL/min/1.73 m2.
Table 1. Demographic and clinical characteristics of patients by eGFR value in renal function screening.
| Characteristics | eGFR < 30 mL/min/1.73 m2 (n = 27) | eGFR ≥ 30 mL/min/1.73 m2 (n = 2,533) | P value | |
|---|---|---|---|---|
| Age, median (range) | 63 (32–90) | 62 (19–92) | 0.528 | |
| Age, yr | ||||
| 19 | 0 (0) | 4 (0.2) | ||
| 20–29 | 0 (0) | 64 (2.5) | ||
| 30–39 | 1 (3.7) | 102 (4.0) | ||
| 40–49 | 4 (14.8) | 315 (12.4) | ||
| 50–59 | 6 (22.2) | 553 (21.8) | ||
| 60–69 | 7 (25.9) | 825 (32.6) | ||
| 70–79 | 7 (25.9) | 524 (20.7) | ||
| 80–89 | 1 (3.7) | 138 (5.4) | ||
| 90–99 | 1 (3.7) | 8 (0.3) | ||
| Sex | 0.469 | |||
| Male | 13 (48.1) | 1,045 (41.3) | ||
| Female | 14 (51.9) | 1,488 (58.7) | ||
| Underlying disease | ||||
| Asthma | 0 (0) | 26 (1.0) | 1.000 | |
| Allergic disease | 0 (0) | 109 (4.3) | 0.627 | |
| Gout | 2 (7.4) | 14 (0.6) | 0.012 | |
| Hyperthyroidism | 0 (0) | 9 (0.4) | 1.000 | |
| Diabetes mellitus | 8 (29.6) | 337 (13.3) | 0.022 | |
| Hypertension | 18 (66.7) | 767 (30.3) | < 0.001 | |
| Heart disease | 6 (22.2) | 195 (7.7) | 0.016 | |
| Renal disease | 24 (88.9) | 86 (3.4) | < 0.001 | |
| Medications | ||||
| Metformin | 0 (0) | 161 (6.4) | 0.411 | |
| Aminoglycoside | 0 (0) | 0 (0) | Not applicable | |
| NSAID | 0 (0) | 3 (0.1) | 1.000 | |
| Beta-blocker | 0 (0) | 31 (1.2) | 1.000 | |
| ACR positivea | 25 (92.6) | 408 (16.1) | ||
| ACR negativeb | 2 (7.4) | 2,125 (83.9) | ||
| ESUR positivea | 26 (96.3) | 968 (38.2) | ||
| ESUR negativeb | 1 (3.7) | 1,565 (61.8) | ||
Values are presented as number (%).
eGFR = estimated glomerular filtration rate, NSAID = nonsteroidal anti-inflammatory drug, ACR = American College of Radiology, ESUR = European Society of Urogenital Radiology.
aPatients meeting the ACR/ESUR renal screening criteria.
bPatients not meeting the ACR/ESUR renal screening criteria.
Table 2. Univariate and multivariate logistic regression analyses of risk factors for renal insufficiency.
| Characteristics | eGFR < 30 mL/min/1.73 m2 | |||
|---|---|---|---|---|
| Univariate analysis | Multivariate analysis | |||
| Exp(B) (95% CI) | P value | Exp(B) (95% CI) | P value | |
| Age | 1.0 (1.0–1.0) | 0.527 | ||
| Sex | 1.3 (0.6–2.8) | 0.471 | ||
| Gout | 14.4 (3.1–66.7) | < 0.001 | 20.7 (1.4–302.1) | 0.027 |
| Diabetes mellitus | 2.7 (1.2–6.3) | 0.018 | ||
| Hypertension | 4.6 (2.1–10.3) | < 0.001 | ||
| Heart disease | 3.4 (1.4–8.6) | 0.009 | ||
| Renal disease | 227.6 (67.2–770.5) | < 0.001 | 235.8 (67.8–820.2) | < 0.001 |
eGFR = estimated glomerular filtration rate, CI = confidence interval.
Among all study participants, 16.9% (433/2,560) and 38.8% (994/2,560) met the renal function screening criteria according to the ACR and ESUR strategies, respectively, leading to the identification of 92.6% (25/27) and 96.3% (26/27) of patients with eGFR < 30 mL/min/1.73 m2 (Table 1). The unidentified patients were a 40-year-old patient with hypertension (ACR) and a 60-year-old patient without a prior medical history (both ACR and ESUR). The sensitivity and specificity of the ACR strategy were 92.6% and 83.9%, respectively, while the ESUR strategy showed a slightly higher sensitivity of 96.3% but a lower specificity of 61.6% (Table 3). PPVs were low for both strategies (ACR, 5.8%; ESUR, 2.6%). NPVs were high, both exceeding 99.9%. The ACR strategy had a higher LR+ compared to ESUR (ACR, 5.75; ESUR, 2.52). Conversely, the ESUR strategy had a slightly lower LR− (ACR, 0.09; ESUR, 0.06).
Table 3. Performance parameters of the ACR and the ESUR guidelines.
| Parameters | ACR (95% CI) | ESUR (95% CI) |
|---|---|---|
| Sensitivity | 0.93 (0.77–0.98) | 0.96 (0.82–0.99) |
| Specificity | 0.84 (0.82–0.85) | 0.62 (0.60–0.64) |
| Positive predictive value | 0.06 (0.04–0.08) | 0.03 (0.02–0.04) |
| Negative predictive value | > 0.99 (0.99–1.00) | > 0.99 (0.99–1.00) |
| Positive likelihood ratio | 5.75 (3.93–8.41) | 2.52 (1.72–3.68) |
| Negative likelihood ratio | 0.09 (0.02–0.35) | 0.06 (0.01–0.43) |
ACR = American College of Radiology, ESUR = European Society of Urogenital Radiology, CI = confidence interval.
As in previous studies,14,15,16 our results support selective renal function screening before contrast-enhanced examinations, rather than universal screening. First, the prevalence of outpatients with eGFR < 30 mL/min/1.73 m2 was remarkably low at 1.1%. Second, the ACR and ESUR screening strategies effectively identified over 92.6% of patients with severe renal insufficiency, with a notable emphasis on the history of renal disease as a strong predictive factor. Lastly, both strategies significantly reduced the number of necessary tests to 16.9% (ACR) and 38.8% (ESUR), while demonstrating a high NPV of over 99.9%.
Despite these advantages, both screening strategies showed some drawbacks. First, both exhibited very low PPVs, meaning there were a considerable number of false positives. Additionally, neither strategy identified 100% of patients with eGFR < 30 mL/min/1.73 m2. The unidentified patients had advanced age or hypertension, factors that were deemed overly sensitive, and therefore were not included in the ACR strategy.8 Incorporating advanced age (60 years or older) and hypertension into the ACR screening criteria increases the screening population to 67.8% (1,735/2,560) and decreases the PPV to 0.02 (95% CI, 0.01–0.02). Nevertheless, in situations where minimizing the risk of missing examinees with renal insufficiency is paramount, such an increase might be acceptable even if it results a higher rate of false positives. Careful consideration is needed to determine the most appropriate screening strategy in individual situations to ensure comprehensive detection while maintaining efficiency.
The relationship between age and the renal function decline is complex. While older patients have a higher prevalence of chronic kidney disease, they exhibit lower rates of disease progression.17,18 In our study, no significant association was found between age and low eGFR (< 30 mL/min/1.73 m2), even when the age variable was dichotomized at 60 years. Nonetheless, advanced age can still be considered as a screening indication as it is not only related to disease but also influences factors such as a cognitive decline and patterns of healthcare utilization.
In our study, only gout and renal disease showed statistically significant associations with low eGFR in the multivariate analysis. Hyperuricemia, the cause of gout, has been consistently studied as an inducer of renal insufficiency.19,20,21,22 However, there is a lack of research on its role as an indication for renal function screening. Additionally, unlike the ACR guideline, the ESUR guideline suggests it as an indication (Table 4). Therefore, further studies are needed to explore the role of hyperuricemia in renal function screening.
Table 4. Comparison of outpatient renal function screening guidelines before intravascular administration of ICM.
| Items | Guidelines | |||||
|---|---|---|---|---|---|---|
| 2023 ACR | 2018 ESUR | 2022 Korean Clinical Practice Guideline | ||||
| Indication | • Personal history of renal disease, including: | • All patients | • Patients having an eGFR < 60 mL/min/1.73 m2 | |||
| Known chronic kidney disease | OR | AND | ||||
| Remote history of acute kidney injury | • Patients with a history of | • With a history of | ||||
| Dialysis | Renal disease (eGFR < 60 mL/min/1.73 m2) | Kidney surgery | ||||
| Kidney surgery | Kidney surgery | Albuminuria | ||||
| Kidney ablation | Proteinuria | Hypertension | ||||
| Albuminuria | Hypertension | Hyperuricemia | ||||
| • History of diabetes mellitus (optional) | Hyperuricemia | Metformin use | ||||
| • Metformin or metformin-containing drug combinations | Diabetes mellitus | Diabetes mellitus | ||||
| Timing of eGFR measurement prior to ICM exposure | • Within 30 days | • Within 3 months | • Within 3–6 months | |||
ACR = American College of Radiology, ESUR = European Society of Urogenital Radiology, eGFR = estimated glomerular filtration rate, ICM = iodinated contrast medium.
Including our research, studies on renal function screening before intravenous ICM injection in outpatients have shown high sensitivity, all above 92%.15,16 However, a study using the 2020 ACR/National Kidney Foundation (NKF) consensus criteria reported a relatively lower sensitivity of 66%.12 Several explanations can account for this difference. The first is the difference in the size of the study populations. The ACR/NKF criteria study had a population of over 10,000, while other studies had populations ranging from approximately 1,300 to 2,600. The second is the difference in the participating healthcare institutions. Unlike other studies conducted in a single tertiary center, the study on the ACR/NKF criteria was conducted at a large health system comprising 12 sites (two large academic institutions, nine community hospitals, and a large outpatient cancer center). This difference may be related to the differences in the characteristics of the population, including the degree of patients' self-awareness of their underlying conditions. Third, in the ACR/NKF criteria study, a high proportion of patients (27.5%) did not report risk factors present in the electronic health record, which appears to be one of the reasons for the low sensitivity. However, information about incorrect reports was not investigated, making direct comparisons difficult.
The 2022 Korean clinical practice guideline, published by the Korean Society of Radiology and the Medical Guidelines Committee, suggests renal function screening for patients having a baseline eGFR < 60 mL/min/1.73 m2 as well as a history of risk factors (Table 4).23 While the ACR and ESUR guidelines also propose chronic kidney disease as a screening indication, the Korean guideline relies on laboratory results rather than patients' reporting. This approach would reduce the influence of patients' self-awareness, thereby decreasing false negatives. Nevertheless, the application of baseline eGFR can be interpreted as presupposing the necessity of universal eGFR in all subjects undergoing contrast-enhanced examinations.
There are several limitations in our study. First, the number of patients with eGFR < 30 mL/min/1.73 m2 was relatively small. Second, since this study was conducted at a single tertiary center, it is difficult to validate the effectiveness of the screening strategies across various types of healthcare institutions. Third, the ACR and ESUR strategies suggest a shorter interval between CT examinations and renal function tests than 180 days (Table 4). The HIRA has not provided a clear rationale for the 180-day period, which might be too long to detect acute changes in renal function. Fourth, the definition of renal disease in the consent form was not specific. Fifth, we used patient-reported risk factors in our consent form, which may not be reliable, especially for patients with cognitive impairment or when the consent was provided by a proxy. However, this reflects real clinical situations.
In conclusion, when applying the ACR and ESUR screening strategies before contrast-enhanced CT examinations, unnecessary renal function tests were substantially excluded while satisfactorily identifying outpatients with severe renal insufficiency. Our findings suggest that applying appropriate strategies can conserve medical resources and reduce patient discomfort compared to universal tests. This efficient use of resources allows for better allocation of time and effort, ultimately enhancing the quality of healthcare services. However, missing patients with impaired renal function can cause serious consequences, emphasizing a need to review screening criteria and address the causes of false negatives. Accurate collection of patient medical history is particularly crucial, as risk factors are primarily assessed through patient self-reporting in clinical practice. Further research across different settings is necessary to optimize the use of these screening strategies.
Ethics statement
This study was approved by the Institutional Review Board of Seoul National University Hospital with a waiver of informed consent (approval No. 2311-152-1487).
Footnotes
Disclosure: Activities not related to the present article: Yoon SH holds stocks and stock options of Medical IP. Other authors have no potential conflicts of interest to disclose.
- Conceptualization: Hwang I, Cho YJ, Han SS, Yoon SH.
- Data curation: Lee Y, Hwang I, Cho YJ, Han SS, Yoon SH.
- Formal analysis: Lee Y, Yoon SH.
- Methodology: Lee Y, Hwang I, Cho YJ, Han SS, Yoon SH.
- Writing - original draft: Lee Y, Yoon SH.
- Writing - review & editing: Lee Y, Hwang I, Cho YJ, Han SS, Yoon SH.
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