Endothelial activation and stress index (EASIX) as a predictor of acute kidney injury in patients undergoing transcatheter aortic valve replacement: A retrospective cohort study

Abstract

Transcatheter aortic valve replacement (TAVR) is being performed in increasingly complex, high-risk cohorts, and contrast-induced nephropathy (CIN) remains a major determinant of morbidity and mortality. The endothelial-damage score EASIX (lactate dehydrogenase × creatinine/platelet count) is a validated prognostic index in hematology and critical care but has never been explored after TAVR. We retrospectively analyzed 161 consecutive severe AS patients (mean age 76.8 ± 8.4 years; 47.8% male) who underwent transfemoral TAVR (February 2019–March 2021). CIN was defined as a ≥25% mg/dL creatinine rise within 72 hours. The predictive value of EASIX was assessed with receiver operating characteristic analysis and multivariable logistic regression. CIN occurred in 19.3% (n = 31). Baseline EASIX was higher in CIN+ vs CIN− (2.92 ± 1.28 vs 1.33 ± 1.30; P < .001). An EASIX threshold ≥ 1.904 predicted CIN with 90.3% sensitivity and 86.2% specificity (area under the curve 0.908; P < .001). In multivariable analysis, EASIX (OR: 2.490; 95% CI: 1.498 -4.138; P < .001) and contrast volume (OR: 1.148; 95% CI: 1.086 -1.213; P < .001) were independently associated with CIN. EASIX, obtainable from routine laboratories, is an independent, high-performance predictor of CIN after TAVR and may facilitate pre-procedural risk stratification.

1. Introduction

Transcatheter aortic valve replacement (TAVR) has emerged as the preferred therapeutic option for patients with symptomatic severe aortic stenosis (AS) who are not candidates for surgical intervention.^[1] Recent trials have further established TAVR as a viable and often superior alternative for patients at intermediate or even low surgical risk.^[2] Landmark studies, including the PARTNER trial (Transcatheter Aortic Valve Implantation for Aortic Stenosis in Patients Who Cannot Undergo Surgery), SURTAVI (Surgical or Transcatheter Aortic Valve Replacement in Intermediate-Risk Patients), and PARTNER 2A, have demonstrated the superiority or non-inferiority of TAVR compared to surgical aortic valve replacement.^[2,3] Moreover, the PARTNER 3 trial and its 5-year follow-up data confirmed that TAVR maintains comparable efficacy and safety to surgical aortic valve replacement in low-risk patients.^[3,4]

With the increasing adoption of TAVR, several postprocedural complications have garnered attention, among which contrast-induced nephropathy (CIN) is particularly concerning. CIN, a form of acute kidney injury, is associated with both short- and long-term adverse cardiovascular outcomes, a fourfold increase in mortality risk, and prolonged hospitalization.^[5,6] The pathophysiology of CIN is multifactorial, involving oxidative stress, a prothrombotic state, inflammation, and endothelial dysfunction. Accordingly, inflammatory and thrombotic biomarkers – such as the neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, and systemic immune-inflammation index (SII) – have been investigated as potential predictors of CIN.^[5-7]

Given the strong association between CIN and postoperative mortality, the early identification of at-risk patients using novel biomarkers is essential for timely intervention. Moreover, the incidence of CIN has risen due to the increasing use of TAVR. Endothelial dysfunction plays a central role not only in cardiovascular diseases but also in a range of hematologic and renal complications. For instance, in hematology, endothelial injury is linked to poor outcomes following allogeneic stem cell transplantation (aSCT), contributing to complications such as refractory graft-versus-host disease (GVHD), transplant-associated thrombotic microangiopathy, sinusoidal obstruction syndrome/veno-occlusive disease, sepsis-induced cardiovascular failure, acute and chronic kidney disease, and late-onset macrovascular disease.^[8-10] Endothelial biomarkers have also shown prognostic relevance in various malignancies, including myelodysplastic syndromes,^[11] small cell lung cancer,^[12] urothelial cell carcinoma,^[13] and multiple myeloma.^[14]

To assess endothelial dysfunction and predict mortality in aSCT recipients with GVHD, the Endothelial Activation and Stress Index (EASIX) was developed. EASIX was found to be significantly associated with high mortality.^[14,15] EASIX has since been validated as a robust prognostic marker in a range of conditions, including severe liver disease,^[16] intensive care unit sepsis,^[17] and severe coronavirus disease 2019 (COVID-19),^[18] reflecting its potential as a global indicator of endothelial injury and systemic stress. Given its strong association with adverse outcomes across various disease states, we hypothesized that EASIX could also serve as a predictive marker for CIN following TAVR. This study, therefore, aimed to evaluate the relationship between EASIX and the development of CIN in patients undergoing TAVR.

2. Material and methods

2.1. Study population

Medical records of individuals undergoing TAVR between February 2019 and March 2021 – regardless of the type of valve (balloon-expandable or self-expandable) – were retrospectively reviewed. The study included 175 patients in total. Nine patients were excluded because they had different infections. Two patients were excluded due to periprocedural mortality, and 3 patients were excluded because they had chronic kidney disease or were on hemodialysis. The remaining 161 patientswere included in the analysis. Among these 161 patients, 31developed CIN.

Patients were categorized based on whether they developed CIN in order to create comparative tables. The study protocol was approved by the Local Ethics Committee of Selcuk University Faculty of Medicine (approval number: 2025/256) and conducted in accordance with the principles outlined in the Declaration of Helsinki. Informed consent was waived due to the retrospective nature of the study.

2.2. Contrast-induced nephropathy

The baseline value was defined as the serum creatinine level at hospital admission. Creatinine levels were also evaluated during the first 48 hours following the procedure. CIN was defined as an increase in creatinine of ≥25% from baseline within 72 hours after contrast medium exposure.^[19] Patients were categorized into those who developed CIN (CIN+) and those who did not (CIN−). Metformin and renin–angiotensin–aldosterone system blockers were discontinued at least 48 hours before the TAVR procedure. Pre-procedural computed tomography with contrast was performed at least 1 week prior to TAVR.

2.3. Endothelial activation and stress index

EASIX was calculated using the equation proposed by Luft et al^[20]:

$${\displaystyle \begin{array}{l}{\displaystyle \mathrm{E}\mathrm{A}\mathrm{S}\mathrm{I}\mathrm{X}=\frac{\mathrm{L}\mathrm{D}\mathrm{H}\left(\mathrm{U}/\mathrm{L}\right)\times \mathrm{c}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{n}\mathrm{e}\left(\mathrm{m}\mathrm{g}/\mathrm{d}\mathrm{L}\right)}{\mathrm{p}\mathrm{l}\mathrm{a}\mathrm{t}\mathrm{e}\mathrm{l}\mathrm{e}\mathrm{t}\mathrm{c}\mathrm{o}\mathrm{u}\mathrm{n}\mathrm{t}\left({10}^9/\mathrm{L}\right)}}\end{array}}$$

2.4. Statistical analysis

The statistical analysis of the study was performed by SPSS 27.0 (IBM Inc, Armonk, NY, USA) software. The descriptive statistics were presented as frequency (percentage) for categorical variables, and mean ± SD or median; Q1-Q3 for numerical variables. The normality of the continuous variables was checked by Kolmogorov-Smirnov test. The comparison between CIN+ and CIN- groups was performed by Student t-test or Mann-Whitney U test where necessary. The chi-squared test with Fisher’s exact test was used to determine the relations between the categorical variables and study groups. ROC analysis was performed to determine the diagnostic value of EASIX to predict CIN+. The cut-off value and the diagnostic rates (with 95% CI) were calculated. The univariate and multivariate logistic regression models were established to determine the diagnostic factors affecting the CIN level. In all analyses, p&lt;0.05 value was considered as statistically significant result for 5% type-I error.

3. Results

A total of 161 patients with severe AS who underwent TAVR were included. Patients were classified into 2 groups according to whether their serum creatinine increased by ≥25% from baseline within 72 hours. Accordingly, 19.3% (n = 31) of the patients were assigned to the CIN(+) group, while the remaining patients were categorized as CIN(−). The overall study cohort comprised 47.8% men, and the mean age was 76.75 ± 8.36 years (range 72–83).

No significant differences were observed between groups in terms of sex (P = .639) or mean age (P = .206). Among comorbidities, the prevalence of diabetes mellitus was significantly higher in the CIN(+) group (67.7%) compared with the CIN(−) group (53.8%; P = .031), whereas atherosclerotic kidney disease occurred at a significantly lower rate in CIN(+) patients (9.7%; P = .030). Usage rates of ACE inhibitors/angiotensin receptor blockers, thiazide diuretics, or mineralocorticoid receptor antagonists did not differ between the 2 groups.

Echocardiographic parameters (left ventricular ejection fraction, aortic valve area, maximum and mean gradients) were comparable between the groups (Table 1). Among hematologic parameters, the neutrophil-to-lymphocyte (Neu/Lym) ratio was significantly higher in the CIN(+) group (P = .035). Although serum glucose levels were similar, hemoglobin A1c was significantly elevated in CIN(+) patients (P = .041). While baseline glomerular filtration rate (GFR) values were similar between the groups, the 48-hour GFR was significantly lower in CIN(+) patients (P = .001), leading to a significant difference in the baseline-to-48-hour GFR ratio (P < .001). Platelet counts were significantly lower (P < .001) and lactate dehydrogenase (LDH) levels significantly higher in CIN(+) patients. Potassium, lipid profile, B-type natriuretic peptide (BNP), C-reactive protein (CRP), and albumin levels were not significantly different across groups (Table 1).

Table 1.

Demographic and clinical features of patients according to CIN status.

Parameter	CIN(−; n = 130)	CIN(+; n = 31)	P
Age (yr)	77.15 ± 8.17 (78.50; 72.75–83)	75.03 ± 9.07 (73; 70–81)	.206
Sex, male, n (%)	61 (46.9)	16 (51.6)	.640
Heart failure (HF), n (%)	30 (23.1)	10 (32.3)	.289
Hypertension (HT), n (%)	88 (67.7)	20 (64.5)	.832
Diabetes mellitus (DM), n (%)	60 (46.2)	21 (67.7)	.031*
Stroke, n (%)	4 (3.1)	3 (9.7)	.106
Atherosclerotic kidney disease (ASKVH), n (%)	37 (28.5)	3 (9.7)	.036*
ACEI/ARB usage, n (%)	90 (69.2)	16 (51.6)	.091
Thiazide diuretic usage, n (%)	26 (20.0)	7 (22.6)	.750
MRA usage, n (%)	15 (11.5)	5 (16.1)	.488
Left ventricular ejection fraction (LVEF, %)	49.11 ± 14.28 (55; 43.50–60)	47.94 ± 15.89 (55; 32–60)	.688
Aortic valve area (AVA, cm2)	0.70 + /-0.16 (0.70; 0.60-0.80)	0.71 + /-0.18 (0.70; 0.60-0.80)	.893
Maximum gradient (mm Hg)	75.40 ± 19.88 (72; 60–87.25)	79.35 ± 23.98 (77; 60–95)	.342
Mean gradient (mm Hg)	48.39 ± 13.55 (46; 40–56)	51.32 ± 16.51 (46; 40–66)	.365
WBC (103/µL)	7.12 ± 2.03 (6.87; 5.85–8.29)	7.86 ± 2.67 (7.32; 5.53–9.30)	.092
Hemoglobin (Hb, g/dL)	11.89 ± 1.84 (12.05; 10.57–13.02)	11.98 ± 1.27 (11.80; 11.20–12.60)	.738
Hematocrit (Hct, %)	36.59 ± 5.34 (36.35; 32.87–39.92)	36.88 ± 3.68 (36.90; 34.80–38.20)	.722
Neutrophils (neu, 103/µL)	4.76 ± 1.75 (4.30; 3.54–5.71)	5.60 ± 2.59 (4.69; 3.62–6.99)	.096
Lymphocytes (lymph, 103/µL)	1.61 ± 0.63 (1.65; 1.09–2.04)	1.43 ± 0.70 (1.32; 0.89–1.73)	.151
Neutrophil-to-lymphocyte (N/L) ratio	3.47 ± 2.25 (2.75; 2.09–3.82)	5.00 ± 3.71 (4.03; 2.19–5.32)	.035**
Glucose (mg/dL)	121.91 ± 49.95 (108; 89.75–134)	150.71 ± 85.83 (121; 94–178)	.081
HbA1c (%)	6.42 ± 1.13 (6.20; 5.70–6.90)	6.93 ± 1.21 (6.50; 5.90–7.80)	.041**
Baseline GFR (mL/min/1.73 m2)	61.51 ± 19.02 (60; 50–78)	68.06 ± 25.95 (68; 48–91)	.194
48-h GFR (mL/min/1.73 m2)	66.86 ± 20.01 (68.50; 53–83)	48.43 ± 24.14 (45; 29–69)	<.001***
Baseline/48-h GFR ratio	1.10 ± 0.23 (1.05; 0.92–1.21)	0.69 ± 0.15 (0.68; 0.59–0.77)	<.001**
Baseline creatinine (mg/dL)	1.20 ± 0.72 (1.08; 0.87–1.26)	1.58 ± 0.70 (1.56; 1.14–1.76)	.010**
Platelets (PLT, 103/µL)	235.95 ± 83.51 (219; 174–276.25)	185.39 ± 33.33 (183; 160–202)	<.001**
LDH (U/L)	229.01 ± 61.55 (217.50; 183–262.25)	345.00 ± 87.05 (362; 285–426)	<.001**
48-h creatinine (mg/dL)	1.06 ± 0.73 (0.93; 0.76–1.15)	4.22 ± 13.33 (1.32; 1.04–2.11)	.222
Baseline/48-h creatinine ratio	0.93 ± 0.16 (0.92; 0.80–1.07)	4.86 ± 17.62 (1.50; 1.35–1.65)	.249
Potassium (mEq/L)	4.42 ± 0.45 (4.50; 4.13–4.70)	4.48 ± 0.43 (4.40; 4.20–4.80)	.514
Triglycerides (mg/dL)	116.90 ± 48.06 (98.50; 81.75–151.25)	142.87 ± 89.65 (111; 82–180)	.128
HDL (mg/dL)	43.37 ± 13.43 (41; 33–52.22)	41.16 ± 11.95 (38; 32–51)	.402
LDL (mg/dL)	95.28 ± 37.28 (90.50; 66–115.50)	98.52 ± 30.94 (98; 74–116)	.656
BNP (pg/mL)	3366.53 ± 6838.51 (687; 196.75–2826)	3231.84 ± 4578.59 (1122; 641–3554)	.917
CRP (mg/L)	17.01 ± 28.45 (5; 3–20.25)	15.70 ± 22.35 (4; 3–14.70)	.812
Albumin (g/dL)	38.96 ± 4.15 (39.90; 36–42)	38.52 ± 5.00 (39; 34–43)	.647
CRP/albumin ratio	0.46 ± 0.77 (0.12; 0.07–0.54)	0.41 ± 0.61 (0.12; 0.06–0.35)	.747
CHADS-VASc score	3.81 ± 1.33 (4; 3–5)	3.58 ± 1.06 (4; 3–4)	.649
Contrast volume (mL)	135.62 ± 8.42 (135; 130–140)	150.97 ± 13.00 (150; 140–160)	<.001**
EASIX	1.33 ± 1.30 (1.07; 0.72–1.47)	2.92 ± 1.29 (2.60; 2.20–3.33)	<.001***

ACEI = angiotensin-converting enzyme inhibitor, ARB = angiotensin receptor blocker, ASKVH = atherosclerotic kidney disease, AVA = aortic valve area, BNP = B-type natriuretic peptide, CHADS-VASc = congestive heart failure, hypertension, age ≥75, diabetes mellitus, stroke, vascular disease, age 65–74, sex category, CIN = contrast-induced nephropathy, CRP = C-reactive protein, DM = diabetes mellitus, EASIX = Endothelial Activation and Stress Index, GFR = glomerular filtration rate, Hb = hemoglobin, Hct = hematocrit, HDL = high-density lipoprotein, HF = heart failure, HT = hypertension, LDH = lactate dehydrogenase, LDL = low-density lipoprotein, LVEF = left ventricular ejection fraction, Lymph = lymphocytes; N/L, neutrophil-to-lymphocyte, MRA = mineralocorticoid receptor antagonist, Neu = neutrophils, PLT = platelets, WBC = white blood cells.

^*Significant at the .05 level according to chi-square test.

^**Significant at the .05 level according to Student’s t-test.

^***Significant at the .05 level according to Mann–Whitney U test.

Contrast volume was significantly higher among CIN(+) patients, calculated as 135.62 ± 8.42 mL in the CIN(−) group versus 150.97 ± 13.01 mL in the CIN(+) group (P < .001). EASIX scores were also elevated in the CIN(+) group (2.92 ± 1.28) compared with the CIN(−) group (1.33 ± 1.30; P < .001). These findings are summarized in Table 1 and illustrated in Figures 1 and 2.

Figure 1.

EASIX scores according to CIN groups. EASIX scores were compared between patients with <25% increase in serum creatinine (CIN negative) and those with ≥25% increase (CIN positive). The box plots illustrate the median (line within the box), interquartile range (box), and range (whiskers). Circles and asterisks denote outliers. CIN = contrast-induced nephropathy, EASIX = Endothelial Activation and Stress Index.

Figure 2.

Standardized baseline creatinine, platelet count, and LDH values according to CIN groups. Box plots represent z-scores for baseline creatinine (blue), platelet count (green), and lactate dehydrogenase (purple) among patients with <25% increase in serum creatinine (CIN negative) versus ≥25% increase (CIN positive). Each box denotes the interquartile range, horizontal lines within boxes indicate the median, and whiskers depict the range. Circles indicate outliers. CIN = contrast-induced nephropathy, LDH = lactate dehydrogenase, PLT = platelets.

A ROC analysis was performed to determine the diagnostic accuracy of contrast volume and EASIX score in predicting CIN. The area under the curve (AUC) for contrast volume was 0.833 (95% CI, 0.738–0.927; P < .001), with a cutoff value of 147.50 mL. The AUC for EASIX was 0.908 (95% CI, 0.853–0.963; P < .001), and the optimal cutoff was 1.904 (Fig. 3). At this threshold, the sensitivity of EASIX was 90.3% and the specificity was 86.2%, representing excellent diagnostic performance (Table 2).

Figure 3.

ROC curve of the EASIX score for predicting CIN. The receiver operating characteristic (ROC) analysis demonstrates the ability of the EASIX score to discriminate between patients who develop contrast-induced nephropathy (CIN+) and those who do not. The area under the curve (AUC) is 0.908, with P < .001, indicating excellent diagnostic performance. AUC = area under the curve, CIN = contrast-induced nephropathy, EASIX = Endothelial Activation and Stress Index, ROC = receiver operating characteristic.

Table 2.

ROC analysis of EASIX and contrast volume for predicting CIN.

Parameter	AUC	P	Cutoff	Sensitivity	Specificity
EASIX	0.908	<.001*	1.904	90.3%	86.2%
Contrast volume	0.833	<.001*	147.50 mL	74.2%	87.7%

AUC = area under the ROC curve, CIN = contrast-induced nephropathy, EASIX = Endothelial Activation and Stress Index, ROC = receiver operating characteristic.

^*Significant at the .05 level according to ROC analysis.

Univariate and multivariate logistic regression models were constructed to identify factors influencing CIN development. The univariate model was significant, with a good model fit (Omnibus χ² = 118.59, P < .001; Nagelkerke R² = 0.870; Hosmer & Lemeshow χ² = 9.28, P = .134). The multivariate model was also significant with no multicollinearity and autocorrelation problems (Omnibus χ² = 66.813, P < .001; Nagelkerke R² = 0.544; Hosmer & Lemeshow χ² = 1.696, P = 0.989, VIF=1.038, Condition Index < 29.06, D-W=0.739). In both models, the constant values were significant. The univariate model revealed that the contrast volume (OR = 1.146) and EASIX (OR = 1.846) each had a significant effect. In the multivariate model, the contrast volume (OR = 1.148) and EASIX (OR = 2.490) all remained significant risk factors for CIN (Table 3).

Table 3.

Factors affecting the development of contrast-induced nephropathy (CIN) by binary logistic regression.

Univariate model				Multivariate model
Variable	β	P	OR	95% CI	β	P	OR	95% CI
Age	2.050	.191	7.774	0.359–168.467
DM	0.376	.825	1.457	0.051–41.546
Glucose	−0.001	.867	0.998	0.978–1.019
HbA1c	0.576	.535	1.779	0.288–10.997
Contrast volume	0.136	.038*	1.146	1.007–1.304	0.138	<.001*	1.148	1.086–1.213
EASIX	0.613	.047*	1.846	1.737–1.955	0.912	<.001*	2.490	1.498–4.138
Constant	−13.327	.356	1.63E−06		−22.748	<.001*

ASKVH = atherosclerotic kidney disease; CI = confidence interval; CIN = contrast-induced nephropathy; DM = diabetes mellitus; EASIX = Endothelial Activation and Stress Index; OR = odds ratio.

^*Significant at the .05 level according to binary logistic regression.

4. Discussion

To our knowledge, this is the first study in the literature to examine the association between the EASIX and CIN in patients undergoing TAVR for severe AS. The primary finding of our study is that EASIX, a simple index derived from routinely available laboratory parameters, can independently predict the development of CIN in this patient population. CIN is currently recognized as the third most common cause of hospital-acquired acute kidney injury, following ischemic and drug-induced etiologies.^[21] Advances in technology, the emergence of dedicated devices, and the increasing number of operators, together with the growing number of cardiovascular interventional procedures, will increase the number of patients with CIN. Despite ongoing innovations that may eventually mitigate this complication, CIN remains a significant and prevalent challenge in interventional cardiology.^[22]

Multiple pathophysiological mechanisms have been proposed to explain CIN development. A growing body of research has focused on oxidative stress, systemic inflammation, and the role of inflammatory markers such as neutrophils, lymphocytes, platelets, and high-sensitivity C-reactive protein.^[23,24] Importantly, Goldenberg et al underscored the central role of endothelial dysfunction in CIN pathogenesis.^[21] Changes in renal hemodynamics influenced by contrast media – such as increased activity of renal vasoconstrictors (vasopressin, angiotensin II, dopamine-1, endothelin, and adenosine) and decreased activity of renal vasodilators (nitric oxide and prostaglandins) – can heighten vulnerability in patients with endothelial dysfunction, increasing the risk of postprocedural complications.^[25,26] This reinforces the rationale for using biomarkers of endothelial injury, such as EASIX, in risk stratification.

EASIX, first introduced by Luft et al,^[20] is calculated using platelet count, creatinine, and LDH levels to assess endothelial dysfunction in patients with acute GVHD following aSCT, and has been strongly linked to high mortality. Although many markers have been associated with various clinical outcomes, EASIX has become routine for hematologists due to its high predictive value for thrombotic microangiopathy after aSCT.^[6,14,27] Recently, EASIX has also been used to predict mortality in various clinical settings beyond transplantation. For instance, it has shown utility in predicting sepsis, assessing prognosis in different hematological diseases, and evaluating outcomes after aSCT.^[14,28] During the COVID-19 pandemic, the importance of endothelial dysfunction was highlighted, prompting investigations into EASIX. Kalicińska et al^[29] conducted a retrospective study of 523 hospitalized COVID-19 patients and showed that EASIX independently predicted in-hospital mortality and the development of acute renal failure, especially in patients admitted to intensive care. Zińczuk et al^[30] corroborated these findings in a similar cohort, further supporting EASIX as a robust marker of endothelial dysfunction and poor outcomes. Despite its growing application, the use of EASIX in cardiology remains limited. A recent study by Finke et al^[31] demonstrated that EASIX independently predicted mortality in a large cohort of patients with coronary artery disease, signaling its potential broader utility in cardiovascular medicine. However, further studies are needed to establish its role in interventional settings such as TAVR.

In Turkey, approximately 2000 TAVR procedures are performed annually, a number that continues to rise with the increasing number of trained operators. Notably, many of these patients have high surgical risk profiles, as assessed by the STS or European System for Cardiac Operative Risk Evaluation systems, making them particularly vulnerable to postprocedural complications like CIN. In our study, we also identified an EASIX cutoff value of 1.904 to differentiate low from high EASIX levels, supporting its potential utility for clinical risk stratification.

5. Study Limitations

Several limitations of this study should be acknowledged. First, the study was retrospective and conducted at a single center, which may introduce selection bias and limits the generalizability of the findings. Second, although multivariable analyses were performed, the relatively small sample size and limited number of CIN events may have reduced the precision of the estimates and increased the possibility of residual confounding. The relatively limited number of CIN events may have reduced the stability of multivariable estimates. Third, several clinically relevant variables, including detailed hydration protocols, nephrotoxic medication exposure, and intraprocedural hemodynamic parameters, were not available in a standardized manner because of the retrospective study design and therefore could not be incorporated into the analyses. Fourth, the incremental prognostic value of EASIX beyond established risk stratification tools such as the STS score, EuroSCORE II, and Mehran risk score was not formally evaluated. Finally, we agree that the proposed EASIX cutoff value of 1.904 should be interpreted with caution. This threshold was derived from a single-center retrospective cohort and was not externally validated. The cutoff should therefore be regarded as exploratory. Independent prospective validation in larger multicenter cohorts will be necessary before any specific threshold can be recommended for clinical decision-making. Accordingly, the present findings should be considered hypothesis-generating and warrant confirmation in future prospective studies. The findings should be considered exploratory and hypothesis-generating until validated in independent prospective cohorts.

6. Conclusion

Our findings suggest that the EASIX could serve as a useful independent predictor of CIN in patients undergoing TAVR for severe AS. Incorporating EASIX into clinical assessment protocols may enable more timely implementation of preventive measures, potentially leading to improved patient outcomes. Further prospective and larger-scale studies are warranted to validate these preliminary findings.

Author contributions

Conceptualization: Yasin Özen, Hüseyin Tezcan, Kadri Murat Gürses, Mustafa Bilal Özbay, Muhammed Ulvi Yalçin.

Data curation: Yasin Özen, Hüseyin Tezcan, Kadri Murat Gürses, Mustafa Bilal Özbay, Muhammed Ulvi Yalçin.

Formal analysis: Yasin Özen, Hüseyin Tezcan, Kadri Murat Gürses, Mustafa Bilal Özbay, Muhammed Ulvi Yalçin.

Funding acquisition: Yasin Özen, Hüseyin Tezcan, Kadri Murat Gürses, Mustafa Bilal Özbay, Muhammed Ulvi Yalçin.

Investigation: Yasin Özen, Hüseyin Tezcan, Kadri Murat Gürses, Mustafa Bilal Özbay, Ahmet Göktuğ Ertem, Muhammed Ulvi Yalçin.

Methodology: Hüseyin Tezcan, Halil Özalp, Kaan Burak Yildiz, Mevlüt Serdar Kuyumcu, Ahmet Göktuğ Ertem.

Project administration: Halil Özalp, Kaan Burak Yildiz, Mevlüt Serdar Kuyumcu, Ahmet Göktuğ Ertem.

Resources: Halil Özalp, Adnan Karaibrahimoglu, Kaan Burak Yildiz, Mevlüt Serdar Kuyumcu, Ahmet Göktuğ Ertem.

Software: Halil Özalp, Adnan Karaibrahimoglu, Kaan Burak Yildiz, Mevlüt Serdar Kuyumcu, Abdullah Tunçez, Ahmet Göktuğ Ertem.

Supervision: Halil Özalp, Adnan Karaibrahimoglu, Kaan Burak Yildiz, Mevlüt Serdar Kuyumcu, Abdullah Tunçez, Ahmet Göktuğ Ertem, Nazif Aygul.

Validation: Adnan Karaibrahimoglu, Abdullah Tunçez, Nazif Aygul.

Visualization: Adnan Karaibrahimoglu, Abdullah Tunçez, Nazif Aygul.

Writing – original draft: Adnan Karaibrahimoglu, Abdullah Tunçez, Nazif Aygul.

Writing – review & editing: Adnan Karaibrahimoglu, Abdullah Tunçez, Nazif Aygul.