Novel renal biomarker evaluation for early detection of acute kidney injury after transcatheter aortic valve implantation.
MATERIALS AND METHODS
This was a prospective pilot study of consecutive patients with severe symptomatic aortic stenosis who were referred for TAVI at a single institution from June 2012 through May 2013. The protocol and informed consent form were approved by the local institutional review board.
Severe symptomatic aortic stenosis was defined as having an aortic valve area <1.0 [cm.sup.2], aortic valve [V.sub.max] [greater than or equal to] 4 m/s, and mean gradient >40 mm Hg on transthoracic echocardiogram with symptoms of exertional dyspnea or decreased exercise tolerance, angina, or syncope. Eligibility for TAVI was determined by a multidisciplinary heart team taking into consideration patient demographics, comorbid conditions as defined by the Society of Thoracic Surgeons (STS), and the STS-predicted risk of mortality (PROM).
Urine levels of NGAL, KIM-1, and IL-18 were measured at baseline and at 2, 4, and 12 hours post-TAVI using the enzyme-linked immunosorbent assay method (Hycult Biotech Inc., Plymouth Meeting, PA). SCr was measured daily until hospital discharge. Patient demographics and in-hospital adverse events were collected using the STS definitions. AKI was defined by the VARC-2 definition (16): Stage 1 AKI, increase in SCr to 1.5 to 1.99x baseline or increase of >0.3 mg/dL (>26.4 mmol/L) or urine output <0.5 mL/kg/hfor >6 hours but <12 hours; stage 2 AKI, increase in SCr to 2.0 to 2.99x baseline or urine output <0.5 mL/kg/h for >12 hours but <24 hours; stage 3 AKI, increase in SCr to >3x baseline or SCr of >4.0 mg/dL (>354 mmol/L) with an acute increase of [greater than or equal to] 0.5 mg/dL (44 mmol/L) or urine output <0.3 mL/kg/h for > 24 hours or anuria for > 12 hours. Patients receiving renal replacement therapy are considered to meet stage 3 criteria irrespective of other criteria. The maximum relative change in SCr was calculated as the greatest SCr of these postoperative SCr measurements divided by the preoperative level.
Demographic characteristics and procedural outcomes were compared between patients who developed AKI postTAVI and those who did not. Group comparisons were performed using the Wilcoxon signed test for continuous variables and using chi-squared or Fisher's exact tests for categorical variables. Unadjusted differences for baseline, 2 hours post-TAVI, 4 hours post-TAVI, and 12 hours post-TAVI levels of NGAL, KIM-1, and IL-18 between groups were tested using univariate logistic regression models with AKI as the dependent variable and each marker (NGAL, KIM-1, or IL-18) as the only independent variable. A generalized estimating equations model accounting for repeated measures and adjusted for STS PROM, baseline NGAL, and baseline NGAL minus 2 hours post-TAVI NGAL, baseline NGAL minus 4 hours post-TAVI NGAL, and baseline NGAL minus 12 hours post-TAVI NGAL was developed to assess maximum relative changes in SCr. The same analysis was repeated for KIM-1 and IL-18. Restricted cubic splines were used to model baseline NGAL, KIM-1, and IL-18 levels. (17,18)
Of the 66 patients enrolled, 17 patients (25.8%) developed AKI postoperatively: Stage 1 occurred in 14 patients (82.4%), stage 2 in 1 patient (5.9%), and stage 3 in 2 patients (11.4%). Patients who developed AKI were more likely to be female and to have experienced a prior myocardial infarction (Table 1). There was no significant difference in baseline estimated glomerular filtration rate (eGFR) by AKI status. The maximum relative change in SCr ranged from 0.72 to 4.58 with a mean (SD) of 1.19 (0.55), corresponding to a 19% increase in maximum postoperative SCr compared to preoperative levels.
The trends in postoperative SCr indicated that 1 patient who developed AKI had a measured rise in creatinine within 24 hours, 8 patients with AKI had a measured rise in creatinine from 24 to 48 hours, 6 patients had a measured rise in creatinine from 48 to 72 hours, and 2 patients had a measured rise in creatinine >72 hours post-TAVI. There were no significant unadjusted differences in mean NGAL or IL-18 levels between patients with AKI and those without AKI seen at 2, 4, and 12 hours postprocedure (Figure 1). Patients with AKI had a marginally greater KIM-1 at 2 hours post-TAVI (P = 0.05).
The adjusted associations between baseline NGAL, KIM-1, and IL-18 and maximum relative change in creatinine were not significant (P = 0.71, P = 0.37, and P = 0.69, respectively; Figure 2). Likewise, the adjusted association between NGAL, KIM-1, and IL-18 differences at 2, 4, and 12 hours from baseline measurement and maximum change in SCr was not significant (Figure 3).
Given the well-described higher rate of mortality and morbidity in patients who develop AKI after TAVI, there is a clinical need for earlier detection of AKI as well as development of therapeutic options for prevention to improve patient outcomes. Even more important, an enhanced ability to predict AKI prior to TAVI would be optimal. Risk factors associated with the development of AKI after TAVI include baseline renal function, diabetes mellitus, blood transfusion, hypertension, and peripheral vascular disease. (5,9-12) This pilot study demonstrated the occurrence of AKI in approximately 25% of the patients in a high-risk aortic stenosis cohort. The vast majority of these were stage 1 AKI. Though baseline eGFR did not differ between the group that developed AKI and the group that did not, there was a numerically lower eGFR in the AKI group, perhaps reflecting the possibility that the small numbers of patients limited our ability to detect differences.
NGAL is involved in the innate immune system and has been reported to predict AKI after cardiopulmonary bypass (CPB) in a pediatric population (19,20) as well as in adults (21-26) and after coronary angiography and percutaneous coronary intervention. (27,28) Similarly, KIM-1, a type-1 transmembrane protein, has been shown to be predictive of AKI following CPB, (29,30) coronary artery bypass grafting, (31) and valve surgery. (31) IL-18 is a pro-inflammatory cytokine that plays a role in both the innate and acquired immune response (32) and has also been shown to be predictive of AKI following CPB, (29,33) coronary artery bypass grafting, (33) and valve surgery, (33,34) as well as following thoracic aortic aneurysm repair. (34) These data lead to the choice of these biomarkers for evaluation. However, in our study, there were
no significant differences in the trend of urinary NGAL, KIM-1, or IL-18 in patients who developed AKI post-TAVI versus those who did not, in both unadjusted and adjusted analyses. Baseline levels of the biomarkers also did not differ based on whether AKI developed or not. Additionally, there was no association between the urinary biomarker levels and maximal change in SCr post-TAVI.
Only one other study has evaluated urinary NGAL levels after TAVI. (35) That study evaluated levels of NGAL 4 hours after TAVI in 34 patients, 6 (17.7%) of whom developed AKI (all of them stage 1), but demonstrated no significant difference in the single NGAL measurement between patients who developed AKI and those who did not. Our results are very similar to their results even with approximately twice the number of patients evaluated and with biomarker evaluation at multiple time points instead of just 4 hours postprocedure.
Therefore, the question becomes, why can we not demonstrate a difference in renal biomarkers after TAVI, though this has been demonstrated after cardiac surgery and in a few studies after percutaneous coronary intervention? First, perhaps there is something unique about the population with aortic stenosis that makes detection of differences in renal biomarkers more challenging. Elevated NGAL levels have been described in coronary artery disease, heart failure, and stroke, with evidence of up-regulation in the setting of failing myocardium and in atherosclerotic plaque. (36-38) Perhaps the magnitude of elevated baseline NGAL levels in patients with aortic stenosis makes it challenging to detect an additional increase in value after TAVI, with a physiologic mechanism that differs from that after coronary intervention. Finally, as a recent metaanalysis showed, (39) there is variability across published studies in the performance of biomarkers of AKI; several studies have reported nonsignificant associations of biomarker levels, including postoperative urinary NGAL, (30,34,40) KIM-1, (40) and IL-18, (30,41) with the development of AKI, despite having larger sample sizes than in the study presented here.
Renal biomarkers other than the ones studied here may also be considered for predicting AKI after TAVI. (39) One study has evaluated cystatin C in the prediction of AKI post-TAVI. (42) Additionally, combinations of renal biomarkers may be considered. Urinary liver-type fatty acid-binding protein has been evaluated as a predictor of AKI after cardiac surgery, with increased performance in detecting AKI (as measured by receiver operator characteristic analysis) when combined with urinary NGAL. (43) Thus, perhaps the most accurate prediction of AKI in the TAVI population will come from a combination of multiple biomarkers.
The limitations of this study are that it is a small study with significant selection bias related to the screening criteria of the population undergoing TAVI. TAVI was used as an alternative to surgical aortic valve replacement in patients who were classified by the multidisciplinary heart team to be high risk or inoperable for surgical aortic valve replacement. As a result, the selected TAVI population might have an unequal distribution of comorbidities. This was evident in the STS PROM in the 8.0% to 9.0% range in the study patients.
In conclusion, urinary levels of the renal biomarkers NGAL, KIM-1, and IL-18 were not found to be significantly different in patients who developed AKI post-TAVI compared to those who did not. Additionally, these biomarkers were not associated with maximum changes in SCr levels postoperatively. The lack of significant association may be due to the small study size versus no real differences in the TAVI population. Further research on renal biomarkers in TAVI is required to optimize outcomes in this high-risk population.
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Mani Arsalan, MD (a), Ethan Ungchusri, BSb, Robert Farkas, MDc, Melissa Johnson, BAb, Rebeca J. Kim, BAb, Giovanni Filardo, PhD, MPH (c,d), Benjamin D. Pollock, MSPHd, Molly Szerlip, MDc, Michael J. Mack, MDc, and Elizabeth M. Holper, MD, MPHb, (c)
(a) Cardiac Surgery, Kerckhoff Klinik, Bad Neuheim, Germany; bBaylor Scott & White Research Institute, Plano, Texas; cThe Heart Hospital Baylor Plano, Plano, Texas; dOffice of the Chief Quality Officer, Baylor Scott & White Health, Dallas, Texas
Corresponding author: Elizabeth M. Holper, MD, MPH, The Heart Hospital Baylor Plano, 1100 Allied Drive, Plano, TX 75093 (e-mail: Elizabeth.Holper@BSWHealth.org)
Received November 6, 2017; Accepted November 18, 2017.
Caption: Figure 2. Adjusted association (P = 0.714) between baseline neutrophil gelatinase-associated lipocalin (NGAL) and maximum change in creatinine. A generalized estimating equations model accounting for patients, repeated measures and adjusted for Society of Thoracic Surgeons predicted risk of mortality, baseline, 0 hour - 2 hour, 0 hour - 4 hour, and 0 hour - 12 hour post-transcatheter aortic valve implantation (TAVI) NGAL was developed to assess maximum changes in creatinine. Restricted cubic splines were used to model baseline NGAL.
Caption: Figure 3. Adjusted associations between neutrophil gelatinase-associated lipocalin (NGAL) differences at (a) 2 hours (P = 0.844), (b) 4 hours (P = 0.845), and (c) 12 hours (P = 0.440) from baseline measurement and maximum change in creatinine.
Table 1. Demographic and clinical characteristics Acute kidney injury Characteristic Yes(n = 17, 26%) Men 7(41%) Age (years) 82.9 [+ or -] 6.5 Height (cm) 165.4 [+ or -] 11.4 Weight (kg) 70.3 [+ or -] 16.8 Body mass index (kg/[m.sup.2]) 26.0 [+ or -] 6.5 Race White 15(88%) Black 1 (6%) Asian 1 (6%) Prior myocardial infarction 5 (29%) Prior stroke 0 (0%) Hypertension 17(100%) Diabetes 4 (24%) Chronic lung disease 5 (29%) Dyslipidemia 1 (6%) Peripheral artery disease 4 (24%) Previous PCI 6 (35%) Prior coronary bypass 5 (29%) Smoking 1 (6%) STS-predicted mortality (%) 9.6 [+ or -] 4.9 Aortic valve mean gradient 39.6 [+ or -] 10.9 (mm Hg) Aortic valve area ((cm.sup.2)) 0.66 [+ or -] 0.11 Preoperative eGFR (mL/min/ 54.8 [+ or -] 29.2 1.73 (m.sup.2)) AKI stage Stage 1 14 (82%) Stage 2 1 (6%) Stage 3 2(12%) Procedural outcomes Number of rapid pace runs 2.9 [+ or -] 1.0 Amount of contrast used 131 [+ or -] 53 (mL) Severe hypotension 1 (6%) Intraoperative arrhythmia 0 (0%) Operative mortality 2(12%) Acute kidney injury Characteristic No (n = 49, 74%) P value Men 34 (69%) 0.04 Age (years) 82.7 [+ or -] 8.9 0.76 Height (cm) 170.7 [+ or -] 9.0 0.15 Weight (kg) 78.7 [+ or -] 21.9 0.26 Body mass index (kg/[m.sup.2]) 27.1 [+ or -] 8.5 0.74 Race 0.22 White 47 (96%) Black 0 (0%) Asian 2 (4%) Prior myocardial infarction 4 (8%) 0.03 Prior stroke 4 (8%) 0.22 Hypertension 48 (98%) 0.55 Diabetes 11 (23%) 0.93 Chronic lung disease 15(31%) 0.93 Dyslipidemia 5(10%) 0.59 Peripheral artery disease 10(20.4%) 0.79 Previous PCI 16(33%) 0.84 Prior coronary bypass 18(37%) 0.59 Smoking 7(14%) 0.36 STS-predicted mortality (%) 8.0 [+ or -] 4.1 0.29 Aortic valve mean gradient 43.0 [+ or -] 12.4 0.53 (mm Hg) Aortic valve area ((cm.sup.2)) 0.69 [+ or -] 0.23 0.96 Preoperative eGFR (mL/min/ 70.7 [+ or -] 33.8 0.09 1.73 (m.sup.2)) AKI stage Stage 1 N/A Stage 2 N/A Stage 3 N/A Procedural outcomes Number of rapid pace runs 2.5 [+ or -] 1.0 0.11 Amount of contrast used 145 [+ or -] 61 0.37 (mL) Severe hypotension 2 (4%) 0.99 (a) Intraoperative arrhythmia 2 (4%) 0.99 (a) Operative mortality 1 (2%) 0.16 (a) AKI indicates acute kidney injury; eGFR, estimated glomerular filtration rate; PCI, percuta-neous coronary intervention; STS, Society of Thoracic Surgeons. (a) Fisher's exact test. Figure 1. Box plots of (a) urinary neutrophil gelatinase-associated lipocalin (NGAL), (b) interleukin-18 (IL-18), and (c) kidney injury molecule-1 (KIM-1) by acute kidney injury (AKI) status. Shown are unadjusted boxplots of 0-, 2-, 4-, and 12-hour biomarker measurements comparing patients who did not develop AKI to those who did develop AKI. The adjusted P values were obtained from a linear generalized estimating equations model with maximum relative change in serum creatinine as the dependent variable and the following dependent variables: baseline, 0 hour--2 hour, 0 hour--4 hour, and 0 hour--12 hour biomarker measurements and Society of Thoracic Surgeons predicted risk of mortality. Baseline 2 hours n=49 n=17 n=43 n-13 No AKI AKI No AKI AKI Jnadjusted p-value 0.95 0.08 Adjusted * p-value: 0.55 0.68 Baseline 2 hours n=46 n=16 n=43 n=14 No AKI AKI No AKI AKI Unadjusted p-value 0.64 0.05 Adjusted * p-value: 0.05 0.14 Baseline 2 hours n=36 n=14 n=32 n=10 No AKI AKI No AKI AKI Unadjusted p-value 0.55 0.10 Adjusted * p-value: 0.44 0.15 4 hours 12 hours n=49 n=15 n=46 n=17 No AKI AKI No AKI AKI Jnadjusted p-value 0.36 0.24 Adjusted * p-value: 0.71 0.44 4 hours 12 hours n=43 n=16 n=46 n=15 No AKI AKI No AKI AKI Unadjusted p-value 0 74 0.42 Adjusted * p-value: 0 80 0.42 4 hours 12 hours n=35 n-14 n=32 n=9 No AKI AKI No AKI AKI Unadjusted p-value 0.78 0.22 Adjusted * p-value: 0.38 0.92
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|Author:||Arsalan, Mani; Ungchusri, Ethan; Farkas, Robert; Johnson, Melissa; Kim, Rebeca J.; Filardo, Giovanni|
|Publication:||Baylor University Medical Center Proceedings|
|Date:||Apr 1, 2018|
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