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Original Investigation | Caring for the Critically Ill Patient

Effect of Remote Ischemic Preconditioning on Kidney Injury Among High-Risk Patients Undergoing Cardiac Surgery A Randomized Clinical Trial FREE

Alexander Zarbock, MD1; Christoph Schmidt, MD1; Hugo Van Aken, MD1; Carola Wempe, PhD1; Sven Martens, MD2; Peter K. Zahn, MD3; Britta Wolf, MD3; Ulrich Goebel, MD4; Christian I. Schwer, MD4; Peter Rosenberger, MD5; Helene Haeberle, MD5; Dennis Görlich, PhD6; John A. Kellum, MD7; Melanie Meersch, MD1 ; for the RenalRIPC Investigators
[+] Author Affiliations
1Department of Anaesthesiology, Intensive Care Medicine and Pain Medicine, University Hospital Münster, Münster, Germany
2Department of Cardiac Surgery, University of Münster, Münster, Germany
3Department of Anaesthesiology, Intensive Care Medicine, Palliative and Pain Medicine, University Hospital Bochum, Bochum, Germany
4Department of Anaesthesiology and Intensive Care Medicine, University Hospital Freiburg, Freiburg, Germany
5Department of Anaesthesiology and Intensive Care Medicine, University Hospital Tübingen, Tübingen, Germany
6Institute of Biostatistics and Clinical Research, University of Münster, Münster, Germany
7Center for Critical Care Nephrology, Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania
JAMA. 2015;313(21):2133-2141. doi:10.1001/jama.2015.4189.
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Published online

Importance  No interventions have yet been identified to reduce the risk of acute kidney injury in the setting of cardiac surgery.

Objective  To determine whether remote ischemic preconditioning reduces the rate and severity of acute kidney injury in patients undergoing cardiac surgery.

Design, Setting, and Participants  In this multicenter trial, we enrolled 240 patients at high risk for acute kidney injury, as identified by a Cleveland Clinic Foundation score of 6 or higher, between August 2013 and June 2014 at 4 hospitals in Germany. We randomized them to receive remote ischemic preconditioning or sham remote ischemic preconditioning (control). All patients completed follow-up 30 days after surgery and were analyzed according to the intention-to-treat principle.

Interventions  Patients received either remote ischemic preconditioning (3 cycles of 5-minute ischemia and 5-minute reperfusion in one upper arm after induction of anesthesia) or sham remote ischemic preconditioning (control), both via blood pressure cuff inflation.

Main Outcomes and Measures  The primary end point was the rate of acute kidney injury defined by Kidney Disease: Improving Global Outcomes criteria within the first 72 hours after cardiac surgery. Secondary end points included use of renal replacement therapy, duration of intensive care unit stay, occurrence of myocardial infarction and stroke, in-hospital and 30-day mortality, and change in acute kidney injury biomarkers.

Results  Acute kidney injury was significantly reduced with remote ischemic preconditioning (45 of 120 patients [37.5%]) compared with control (63 of 120 patients [52.5%]; absolute risk reduction, 15%; 95% CI, 2.56%-27.44%; P = .02). Fewer patients receiving remote ischemic preconditioning received renal replacement therapy (7 [5.8%] vs 19 [15.8%]; absolute risk reduction, 10%; 95% CI, 2.25%-17.75%; P = .01), and remote ischemic preconditioning reduced intensive care unit stay (3 days [interquartile range, 2-5]) vs 4 days (interquartile range, 2-7) (P = .04). There was no significant effect of remote ischemic preconditioning on myocardial infarction, stroke, or mortality. Remote ischemic preconditioning significantly attenuated the release of urinary insulinlike growth factor–binding protein 7 and tissue inhibitor of metalloproteinases 2 after surgery (remote ischemic preconditioning, 0.36 vs control, 0.97 ng/mL2/1000; difference, 0.61; 95% CI, 0.27-0.86; P < .001). No adverse events were reported with remote ischemic preconditioning.

Conclusions and Relevance  Among high-risk patients undergoing cardiac surgery, remote ischemic preconditioning compared with no ischemic preconditioning significantly reduced the rate of acute kidney injury and use of renal replacement therapy. The observed reduction in the rate of acute kidney injury and the need for renal replacement warrants further investigation.

Trial Registration  German Clinical Trials Register Identifier: DRKS00005333

Figures in this Article

Acute kidney injury is a well-recognized complication after cardiac surgery and significantly affects morbidity and mortality.1,2 Up to 30% of patients develop acute kidney injury after cardiac surgery, whereas severe acute kidney injury requiring dialysis is relatively rare.3 Approximately 1% of all patients undergoing cardiac surgery develop a severe dialysis-dependent acute kidney injury, and this severity of injury is associated with especially poor outcomes.1 Although the mechanisms of acute kidney injury are not fully understood, injury to renal tubular epithelial cells is a universal aspect of the disease. Despite numerous clinical trials using several interventions,4 a reliable means to prevent acute kidney injury remains elusive.

Remote ischemic preconditioning elicited by brief episodes of ischemia and reperfusion in distant tissue may provide protection from subsequent injury.5 In cardiac surgery, adverse outcomes are mainly linked to perioperative myocardial injury.6

Remote ischemic preconditioning may attenuate renal injury by releasing various molecules such as damage-associated molecular patterns that are then filtered by the kidney and signal through Toll-like receptors in the proximal tubule epithelia.5,7 This signaling may then induce natural defenses such as bioenergetic down-regulation and temporary cell-cycle arrest.8 These defenses, once engaged, can then protect the kidney during subsequent inflammatory or ischemic stress.

However, despite this rationale, 3 small single-center randomized trials investigating the effect of remote ischemic preconditioning on acute kidney injury after cardiac surgery have shown conflicting results.911 Thus, a large randomized study with a robust and relevant clinical end point has been called for.12 As an initial step to achieving this goal, we performed a multicenter, randomized, controlled, clinical trial to investigate whether remote ischemic preconditioning could reduce the occurrence and severity of acute kidney injury as defined by Kidney Disease: Improving Global Outcomes criteria13 and to analyze other relevant clinical outcomes of remote ischemic preconditioning in cardiac surgery patients at high risk for acute kidney injury after on-pump cardiac surgery. Our goal was to acquire phase 2 equivalent data to support a larger multicenter trial.

Study Design and Participants

After obtaining approval from the institutional review boards at each site, we performed a multicenter, double-blind, randomized clinical trial (study protocol appears in Supplement 1). Consecutive patients were approached for enrollment during preadmission consultations and provided written informed consent. The study was conducted according to the principles of the Declaration of Helsinki. Eligible patients were adults at high risk for acute kidney injury who underwent cardiac surgery with the use of cardiopulmonary bypass at the universities of Münster, Tübingen, Freiburg, or Bochum (all in Germany) between August 2013 and June 2014. A Cleveland Clinic Foundation score (eTable 1 in Supplement 2) of 6 or higher was used to define patients at high risk for acute kidney injury.14 The score is composed of different risk factors, including patient characteristics, comorbidities, and type of surgery.14 Exclusion criteria were acute myocardial infarction up to 7 days before surgery, age younger than 18 years, off-pump heart surgery, preexisting acute kidney injury, kidney transplantation, chronic kidney disease with a glomerular filtration rate less than 30 mL/min, pregnancy, peripheral vascular disease affecting the upper limbs, hepatorenal syndrome, and drug therapy with sulfonamide or nicorandil (preconditioning-blocking and preconditioning-mimetic medication, respectively).

Randomization and Blinding

Patients were randomized on a 1:1 basis, stratified by center. Randomization codes were computer generated and concealed from investigators. On the day of surgery, patients were assigned to undergo either remote ischemic preconditioning or sham remote ischemic preconditioning (control) (Figure 1), and the intervention was provided by an investigator not involved in the care of the patient. Patients, anesthesiologists, staff providing care of the patient, cardiac surgeons, and intensive care physicians were unaware of treatment assignment.

Place holder to copy figure label and caption
Figure 1.
Participant Flow of Remote Ischemic Preconditioning in Patients Undergoing Cardiac Surgery
Graphic Jump Location
Procedures

Anesthesia was induced according to the standard of care at each center and maintained with volatile anesthetics because propofol may interfere with remote ischemic preconditioning.15 According to a recently published review,16 we standardized the management of cardiopulmonary bypass as follows: mean arterial blood pressure of 60 to 70 mm Hg, the use of nonpulsatile cardiopulmonary bypass, α-stat acid-base management to regulate carbon dioxide tension, hematocrit values of 25% to 30%, blood glucose levels less than 200 mg/dL, and the use of arterial line filters.

After induction of anesthesia and before skin incision, we performed remote ischemic preconditioning consisting of 3 cycles of 5-minute inflation of a blood pressure cuff to 200 mm Hg (or at least to a pressure 50 mm Hg higher than the systolic arterial pressure) to one upper arm, followed by 5-minute reperfusion with the cuff deflated. In patients assigned to the control group, sham remote ischemic preconditioning intervention was induced by 3 cycles of upper limb pseudo ischemia (low pressure, 5-minute blood pressure cuff inflation to a pressure of 20 mm Hg and 5-minute cuff deflation). The surgical procedure and perioperative care were performed according to the standard at each center.

Outcomes

Our primary end point was the occurrence of acute kidney injury within the first 72 hours after surgery. We defined acute kidney injury according to the Kidney Disease: Improving Global Outcomes criteria (eTable 2 in Supplement 2).13 Secondary end points were severe acute kidney injury (stage 2-3) within 72 hours, 30-day all-cause mortality, need for renal replacement therapy during index hospitalization, duration of ventilator support, length of stay in the intensive care unit, length of hospital stay, in-hospital death, concentrations of various urinary biomarkers in the first 24 hours after surgery, and perioperative myocardial infarction and stroke during the index hospital stay.

We abstracted clinical variables from the medical record. Initiation of renal replacement therapy was at the discretion of the intensive care unit clinicians blinded to treatment assignment. Criteria for renal replacement therapy were not included in the protocol. Perioperative myocardial infarction and stroke were defined as described previously.17 Perioperative myocardial infarction was defined as cardiac troponin I concentration in serum more than 5 times the 99th percentile of the reference range when associated with new left bundle-branch block pathologic Q waves, or angiography-confirmed new or native coronary occlusion. Postoperative myocardial infarction was defined as an increase in troponin complex I concentration from baseline to at least twice the upper limit of normal, together with evidence of myocardial ischemia, such as electrocardiographic changes or angina symptoms. Cerebrovascular accidents or stroke during or after hospital admission was assessed if at least 1 of the following criteria was fulfilled: a neurologic event resulting in new, temporary, or permanent focal or global neurologic deficit, any embolic event after the immediate perioperative period (when anesthesia-induced unconsciousness was completely reversed), or a stroke or permanent neurologic event lasting longer than 24 hours or less than 24 hours if a cerebral lesion was observed on imaging. Repeated revascularization was defined as any percutaneous coronary intervention or repeated coronary artery bypass graft surgery after the primary coronary artery bypass graft surgery.

Blood and Urine Sampling and Analysis

Blood samples were drawn before surgery and at prespecified points after surgery for measurement of serum creatinine concentrations (4 hours after cardiac surgery and on every morning for at least 3 days after cardiac surgery). We estimated glomerular filtration rate with the Modification of Diet in Renal Disease formula. Urine samples for biomarkers were collected before remote ischemic preconditioning or sham remote ischemic preconditioning, after inducing each one and at 4, 12, and 24 hours after surgery. Insulinlike growth factor–binding protein 7 (IGFBP7) and tissue inhibitor of metalloproteinases 2 (TIMP-2), both inducers of G1 cell cycle arrest, are implicated in acute kidney injury and serve as biomarkers to predict it. The product of urine TIMP-2 and IGFBP7 concentrations, (TIMP-2) × (IGFBP7), was measured with the NephroCheck Test (Astute Medical). Urine neutrophil gelatinase–associated lipocalin (NGAL), was measured with a commercially available assay (Dianova) according to the manufacturer's protocol. Urine high-mobility group box (HMGB) 1 was measured with a commercially available assay (http://antibodies-online.com) according to the manufacturer's protocol.

Statistical Analysis

We calculated a necessary sample size based on the primary end point, using nQuery Advisor version 7. The primary efficacy analysis was intended to show superiority of remote ischemic preconditioning in high-risk cardiac surgery patients, applying a 2-sided χ2 test on significance level α=.05. According to an observational study we performed in a similar patient population,18 the expected acute kidney injury rate in the control group treated with sham remote ischemic preconditioning was 50%. The expected absolute risk reduction for acute kidney injury was 18% according to a published single-center study investigating the effect of remote ischemic preconditioning on acute kidney injury after cardiac surgery.10 As a result of these considerations and a power of 80%, the required sample size was calculated to be 117 evaluable patients per treatment group, ie, 234 in total. An additional 6 patients were recruited to account for loss to follow-up or nonevaluable data.

The primary efficacy analysis included all randomized patients (full analysis set) and was performed according to the intent-to-treat principle, ie, all patients were analyzed according to their randomization (see statistical analysis plan in Supplement 1). For the primary outcome and the secondary end points acute kidney injury severity, need for renal replacement therapy, and mortality, all patients had complete data. For the analysis of biomarkers over time, information of all patients who had evaluable data for the respective time was included. For the logistic regression analyses, only patients with complete data regarding the included covariates were included. No imputation of the data was performed. Descriptive statistics are summarized for categorical variables as frequency (%) and were compared between groups with χ2 test (or Fisher exact test if the produced matrixes contained cells with expected counts <5). Continuous variables, expressed as mean (standard deviation), were compared between groups with an unpaired t test. Continuous variables, which were not distributed normally, were analyzed with nonparametric tests (Mann-Whitney U and Wilcoxon for unpaired and paired observations, respectively). We estimated the relative risk (RR) reduction and the absolute risk reduction, including 95% CIs, for the occurrence of acute kidney injury, comparing the 2 study cohorts. The 95% CIs for median differences were calculated by bootstrapping (10 000 random samples taken equally distributed from both randomization groups).

To identify the association between various risk factors and acute kidney injury, we used multivariable logistic regression with acute kidney injury within 72 hours of surgery (yes or no) as the dependent variable. We included variables from the Cleveland Clinic Foundation score14 (age, sex, diabetes, chronic obstructive pulmonary disease, previous heart surgery, and preoperative creatinine level), along with HMGB-1 (TIMP-2) × (IGFBP7) (difference between pre- and post–remote ischemic preconditioning) and remote ischemic preconditioning as dependent variables, using backward likelihood ratios for variable retention in the model. We used the Wald test and reported P value odds ratios with 95% CIs. To identify factors associated with (TIMP-2) × (IGFBP7) immediately after remote ischemic preconditioning, we used a predefined cutoff of 0.5 ng/mL2/100018 and used multivariable logistic regression with the same variables as described above (except [TIMP-2] × [IGFBP7]) as independent variables. Model performance was assessed by the analysis of the area under the receiver operating characteristic curve. P value is given for the hypothesis test area under the curve = 0.5. IBM SPSS version 21.0 software was used. Two-sided P values ≤.05 were considered indicative of statistical significance.

Patients

Of 790 patients screened for the trial, 240 were enrolled and randomized to receive either remote ischemic preconditioning (n = 120) or sham remote ischemic preconditioning (control) (n = 120) and included in the primary analysis (Figure 1). The baseline and intraoperative characteristics were similar between the groups (Table 1). The number of patients with a low ejection fraction was similar between the groups.

Table Graphic Jump LocationTable 1.  Baseline and Operative Characteristics
Primary Outcome

Significantly fewer patients in the remote ischemic preconditioning arm developed acute kidney injury within 72 hours after surgery compared with the control group (37.5% vs 52.5%; P = .02; RR, 71%; 95% CI, 54%-95%; absolute risk reduction, 15.0%; 95% CI, 2.56%-27.44%; RR reduction, 28.6%; 95% CI, 5%-47%) (Table 2). Correction of serum creatinine level for fluid balance slightly changed the occurrence of acute kidney injury but did not change the difference in acute kidney injury rate between the remote ischemic preconditioning group and control group (42.5% vs 53.3%; P = .03). We performed a stratified analysis of the primary end point to check for site effects, using the Cochran and Mantel-Haenszel t test. The 2-sided P value of the test was .02 (OR, 0.56; 95% CI, 0.33-0.93).

Table Graphic Jump LocationTable 2.  Primary and Secondary Study Outcomes, by Group
Secondary Outcomes

Remote ischemic preconditioning significantly reduced the number of moderate and severe acute kidney injury cases compared with that of the control group (12.5% vs 25.8%; P = .02; RR, 85%; 95% CI, 75%-97%) but did not reduce the rate of mild acute kidney injury (25% vs 26.7%; P = .77; RR, 98%; 95% CI, 84%-114%). Use of renal replacement therapy (5.8% vs 15.8%; P = .01; absolute risk reduction, 10%; 95% CI, 2.25%-17.75%) and length of intensive care unit stay (3 days [interquartile range, 2-5] vs 4 days [interquartile range, 2-7]; 95% CI, 0-2 days, median difference; P = .04) were significantly reduced with remote ischemic preconditioning (Table 2). However, we found no significant differences between groups in time receiving mechanical ventilation, myocardial infarction, and perioperative stroke (Table 2). Length of hospital stay after surgery was comparable. All-cause in-hospital mortality and 30-day mortality were not different between groups (Table 2).

Biomarkers

Although baseline urinary (TIMP-2) × (IGFBP7) and NGAL, tested immediately before the intervention, did not differ between groups, the control group had significantly higher urinary (TIMP-2) × (IGFBP7) at 4 hours after (remote ischemic preconditioning, 0.36 vs control, 0.97 ng/mL2/1000; difference, 0.61 [95% CI, 0.27-0.86]; P <.001) and 12 hours after cardiopulmonary bypass (P < .001) and higher NGAL at 4 hours after cardiopulmonary bypass (P = .04) compared with the remote ischemic preconditioning group (Figure 2A and B).

Place holder to copy figure label and caption
Figure 2.
Analysis of Acute Kidney Injury Biomarkers

A, Analysis of urine (TIMP-2) × (IGFBP7) before and after remote ischemic preconditioning (RIPC) and cardiopulmonary bypass (CPB) (pre-RIPC, P = .33; post-RIPC, P = <.01; 4 h after CPB, P = .01; 12 h after CPB, P = .01; 24 h after CPB, P = .35) (lower and upper limit of the reference range, 0.03 [2.5 percentile] and 1.93 [97.5 percentile], respectively). B, Analysis of urine neutrophil gelatinase-associated lipocalin (NGAL) concentrations before and after RIPC and CPB (pre-RIPC, P = .79; post-RIPC, P = .72; 4 h after CPB, P = .04; 12 h after CPB, P = .74; 24 h after CPB, P = .28) (reference range, 153 ng/mL; 90% CI, 142 to 182 ng/mL). C, Analysis of HMGB-1 concentrations before and after RIPC (pre-RIPC, P = .23; post-RIPC, P = <.01) (reference range: mean, 0.39 ng/mL; upper limit of the reference range, 1.4 ng/mL [97.5 percentile]). Error bars indicate 95% CI. All P values are for comparison of RIPC vs control. HMGB-1 indicates high-mobility group box 1; (TIMP-2) × (IGFBP7) indicates the product of urine IGFBP7 (insulinlike growth factor–binding protein 7) and TIMP-2 (tissue inhibitor of metalloproteinases 2).

Graphic Jump Location

By contrast, remote ischemic preconditioning increased urinary (TIMP-2) × (IGFBP7) immediately after remote ischemic preconditioning before cardiopulmonary bypass compared with that of the control group (Figure 2A), whereas urinary NGAL was unchanged (Figure 2B). Patients with urinary (TIMP-2) × (IGFBP7) level greater than or equal to 0.5 ng/mL2/1000 before the initiation of the cardiopulmonary bypass had a significantly reduced rate of acute kidney injury compared with patients with lower urinary (TIMP-2) × (IGFBP7) concentration (RR, 67%; 95% CI, 53%-83%; P < .001) (eFigure 1A in Supplement 2). However, patients with urinary (TIMP-2) × (IGFBP7) greater than or equal to 0.5 ng/mL2/1000 4 hours after cardiopulmonary bypass had a significantly increased rate of acute kidney injury compared with patients with lower urinary (TIMP-2) × (IGFBP7) (RR, 299%; 95% CI, 188%-473%; P < .001) (eFigure 1B in Supplement 2).

High-mobility group box 1, a damage-associated molecular pattern, was measured at baseline and after the intervention before cardiopulmonary bypass. Urinary HMGB-1 was similar in both groups at baseline. However, it significantly increased immediately after remote ischemic preconditioning (Figure 2C). In multivariable logistic regression analysis, preoperative serum creatinine level and previous heart surgery were associated with increased risk for acute kidney injury, whereas post–remote ischemic preconditioning HMGB-1 (OR, 0.75; 95% CI, 0.61-0.91; P = .005) and (TIMP-2) × (IGFBP7) (OR, 0.57; 95% CI, 0.35-0.94; P = .03) were associated with lower risk for acute kidney injury (Table 3). Furthermore, both HMGB-1 and remote ischemic preconditioning were significant predictors of post–remote ischemic preconditioning (TIMP-2) × (IGFBP7) ≥ 0.5 ng/mL2/1000 (Table 3).

Table Graphic Jump LocationTable 3.  Predictors of Acute Kidney Injury (AKI) and Concentration of Tissue Inhibitor of Metalloproteinases × Insulinlike Growth Factor–Binding Protein 7 Increase, Using Multivariable Logistic Regression

The results of this multicenter, randomized, double-blind, clinical trial confirm the findings of a previous single-center study that remote ischemic preconditioning reduces the rate of acute kidney injury after cardiac surgery in high-risk patients.10 In our study, the intervention achieved more than a 15% absolute reduction in the rate of perioperative acute kidney injury. Especially the occurrence of moderate and severe acute kidney injury was reduced by remote ischemic preconditioning. We furthermore showed a benefit from remote ischemic preconditioning with a reduced use of renal replacement therapy and a shorter length of intensive care unit stay. Finally, we found that remote ischemic preconditioning reduced the post–cardiopulmonary bypass expression of biomarkers of acute kidney injury, including neutrophil gelatinase-associated lipocalin and the recently approved biomarker panel (TIMP-2) × (IGFBP7). Remote ischemic preconditioning increased pre–cardiopulmonary bypass release of the “alarm” markers (TIMP-2) × (IGFBP7) while having no effect on the damage marker neutrophil gelatinase-associated lipocalin. This scenario is consistent with the known roles of TIMP-2 and IGFBP7 in the induction of G1 cell-cycle arrest, an epithelial defense mechanism.19

Several small feasibility and controlled clinical trials provided evidence that remote ischemic preconditioning can reduce myocardial injury during coronary bypass surgery,20 during surgical repair of congenital heart defects,21 and before percutaneous coronary interventions.22 Two studies have reported a protective effect of remote ischemic preconditioning on renal function.10,23 In contrast to these studies, 3 other trials failed to demonstrate renal protection with remote ischemic preconditioning (see eFigure 2 in the Supplement).9,11,24 Our study provides new insight into the heterogeneity of treatment effect observed across these trials. Although the mechanisms responsible for the benefit of remote ischemic preconditioning are not completely understood, one possible explanation is that damage-associated molecular patterns released from the ischemic tissue engage self-protective mechanisms in the kidney such as cell-cycle arrest (see eFigure 3 in the Supplement). We measured HMGB-1, a well-known damage-associated molecular pattern, in urine and found that remote ischemic preconditioning resulted in increased release of this molecule. Early increases in HMGB-1 and (TIMP-2) × (IGFBP7) were strongly associated with lower risk for acute kidney injury. However, not all patients responded to remote ischemic preconditioning with increased HMGB-1 release or increases in urine (TIMP-2) × (IGFBP7). Future studies of this intervention might benefit from monitoring these biomarkers.

Differences in outcomes across remote ischemic preconditioning trials might also have been due to differences in study protocols, confounding comorbidities, anesthetic regimens, and surgical technique. Because ours is the first study to our knowledge to measure biomarkers, it is not possible to know whether previous trials with negative results failed to induce changes in these intermediate end points. In our protocol, patients with diabetes treated with sulfonylurea medications were excluded because these drugs inhibit adenosine triphosphate–sensitive potassium-channel conductance and may impede the effects of remote ischemic preconditioning.25 Although volatile anesthetics might have a preconditioning effect,26,27 we excluded the use of propofol because it may mitigate the effects of remote ischemic preconditioning.15 In our trial, we included only patients with a high risk for acute kidney injury, as identified by a Cleveland Clinic Foundation score greater than or equal to 6.14 We focused on this particularly high-risk patient population because 2 consensus conferences concluded that they would be most likely to benefit from remote ischemic preconditioning.28

The pathophysiology of acute kidney injury is complex and still incompletely understood. New evidence suggests that adaptive responses by tubular epithelial cells to injurious signals are responsible for renal dysfunction and that renal inflammation and microcirculatory dysfunction further amplify these mechanisms.7,29 Remote ischemic preconditioning induces the release of various molecules that appear to mediate the protective effect of this intervention.5 Here, we demonstrate that these mediators might be inducing G1 cell-cycle arrest in the kidney, as indicated by increased urinary (TIMP-2) × (IGFBP7) after remote ischemic preconditioning. Cell-cycle arrest has been implicated in acute kidney injury,30,31 and urinary (TIMP-2) × (IGFBP7) has been shown to be predictive of acute kidney injury in patients undergoing cardiac surgery,18 as well as in general intensive care unit populations.32 However, cell-cycle arrest is a self-defense mechanism. When exposed to stress, epithelial cells may enter a short period of G1 cell-cycle arrest19 until the danger has passed or injury has been repaired. High-mobility group box-1 is an endogenous damage-associated molecular pattern molecule that can serve as an early mediator in the context of sterile inflammation, with release occurring as a consequence of acute cellular stress, hypoxia, or necrosis.33 Extracellular HMGB-1 can bind to several pattern recognition receptors, including Toll-like receptors, which can directly or indirectly induce cell-cycle arrest.29 Our data are in line with those of a recent animal study demonstrating that preconditioning with recombinant HMGB-1 provides protection against acute kidney injury.34 We hypothesized that HMGB-1 (and other damage-associated molecular patterns) is released after remote ischemic preconditioning and these molecules induce cell-cycle arrest in tubular epithelial cells (see eFigure 3). Increases in urine (TIMP-2) × (IGFBP7) immediately after remote ischemic preconditioning should therefore be protective from subsequent kidney injury induced by cardiac surgery, whereas late increases in these markers (for example, after cardiopulmonary bypass) should herald acute kidney injury. Our results fit this scenario exactly.

In cardiac surgery, perioperative acute kidney injury is closely associated with postoperative morbidity and mortality in the short and long term.2,3537 Several studies demonstrated an association between acute kidney injury and increased morbidity, short-term and long-term mortality, and use of resources in various patient populations.2,3541 This relationship holds true even with small increases of serum creatinine level for cardiac surgery patients.2,35,39,41 Remote ischemic preconditioning could thus represent a simple and promising strategy to provide protection to the kidney and improve postoperative outcomes. Such measures would be particularly desirable to deal with the increasingly challenging risk profiles of patients who are referred for cardiac surgery.

Study Limitations

Our study is not without limitations. Although this was a multicenter trial, it was adequately powered only to analyze prospectively the rate of perioperative acute kidney injury and thus a phase 2 equivalent study. The secondary end points, for which the study was not powered but which were assessed in view of a significant effect on the primary end point, indicated reduced kidney damage (by acute kidney injury stage, as well as by urinary (TIMP-2) × (IGFBP7) and [neutrophil gelatinase-associated lipocalin]) in patients undergoing remote ischemic preconditioning. The use of renal replacement therapy was reduced in the intervention group as well. Although the critical care physicians treating the patients were blinded to the study group allocation, initiation of renal replacement therapy was at their discretion. Among critically ill patients with acute kidney injury, the timing of renal replacement therapy initiation remains an area of considerable controversy.13 Another limitation of this study is that although we have found important associations with intermediary end points, we cannot prove mechanism. Future experimental and clinical studies are needed to better establish the relationship between damage-associated molecular patterns, cell-cycle arrest, and rate or severity of acute kidney injury. Likewise, future studies will need to address the optimal methods for remote ischemic preconditioning and whether benefits are consistent across patients with various risks for acute kidney injury, such as those with preexisting chronic kidney disease or with lower Cleveland Clinic Foundation score. We did not detect a reduction in mortality between the 2 groups; as expected, this secondary end point is uncommon and our study was too small. According to our 30-day mortality results, we would need more than 4000 patients (183 deaths) to detect a difference in the mortality with 80% power. It remains to be determined whether preventing cardiac surgery–associated acute kidney injury with remote ischemic preconditioning will reduce morbidity, mortality, and use of resources other than renal replacement therapy.

Among high-risk patients undergoing cardiac surgery, remote ischemic preconditioning compared with control significantly reduced the rate of acute kidney injury and use of renal replacement therapy. The observed reduction in the rate of acute kidney injury and the need for renal replacement warrant further investigation.

Section Editor: Derek C. Angus, MD, MPH, Associate Editor, JAMA (angusdc@upmc.edu).

Corresponding Author: Alexander Zarbock, MD, Department of Anesthesiology, Critical Care Medicine and Pain Therapy, University Hospital Münster, Albert-Schweitzer-Campus 1, Gebäude A1, 48149 Münster, Germany (zarbock@uni-muenster.de).

Published Online: May 29, 2015. doi:10.1001/jama.2015.4189.

Author Contributions: Drs Zarbock and Meersch had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Zarbock, Schmidt, Wempe, Martens, Haeberle, Görlich, Meersch.

Acquisition, analysis, or interpretation of data: Zarbock, Schmidt, Van Aken, Wempe, Zahn, Wolf, Goebel, Schwer, Rosenberger, Görlich, Kellum, Meersch.

Drafting of the manuscript: Zarbock, Görlich, Meersch.

Critical revision of the manuscript for important intellectual content: Zarbock, Schmidt, Van Aken, Wempe, Martens, Zahn, Wolf, Goebel, Schwer, Rosenberger, Haeberle, Görlich, Kellum, Meersch.

Statistical analysis: Zarbock, Görlich, Kellum, Meersch.

Obtained funding: Zarbock.

Administrative, technical, or material support: Zarbock, Schmidt, Wempe, Zahn, Wolf, Goebel, Schwer, Rosenberger, Kellum, Meersch.

Study supervision: Zarbock, Schmidt, Van Aken, Martens, Zahn, Wolf.

Conflict of Interest Disclosures: All authors have completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Dr Zarbock reports receiving grant support and lecture fees from Astute Medical, unrelated to the current study. Dr Kellum reports receiving grant support and consulting fees from Astute Medical and Alere, unrelated to the current study. Drs Zarbock and Kellum have filed a patent application on the use of the biomarkers together with remote ischemic preconditioning.

Funding/Support: The study was funded by the German Research Foundation (ZA428/6-1 to Dr Zarbock).

Role of the Funder/Sponsor: The study sponsor had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

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PubMed   |  Link to Article
Kharbanda  RK, Nielsen  TT, Redington  AN.  Translation of remote ischaemic preconditioning into clinical practice. Lancet. 2009;374(9700):1557-1565.
PubMed   |  Link to Article
Domanski  MJ, Mahaffey  K, Hasselblad  V,  et al.  Association of myocardial enzyme elevation and survival following coronary artery bypass graft surgery. JAMA. 2011;305(6):585-591.
PubMed   |  Link to Article
Gassanov  N, Nia  AM, Caglayan  E, Er  F.  Remote ischemic preconditioning and renoprotection: from myth to a novel therapeutic option? J Am Soc Nephrol. 2014;25(2):216-224.
PubMed   |  Link to Article
Jaeschke  H.  Mechanisms of liver injury, II: mechanisms of neutrophil-induced liver cell injury during hepatic ischemia-reperfusion and other acute inflammatory conditions. Am J Physiol Gastrointest Liver Physiol. 2006;290(6):G1083-G1088.
PubMed   |  Link to Article
Choi  YS, Shim  JK, Kim  JC,  et al.  Effect of remote ischemic preconditioning on renal dysfunction after complex valvular heart surgery: a randomized controlled trial. J Thorac Cardiovasc Surg. 2011;142(1):148-154.
PubMed   |  Link to Article
Zimmerman  RF, Ezeanuna  PU, Kane  JC,  et al.  Ischemic preconditioning at a remote site prevents acute kidney injury in patients following cardiac surgery. Kidney Int. 2011;80(8):861-867.
PubMed   |  Link to Article
Gallagher  SM, Jones  DA, Kapur  A,  et al.  Remote ischemic preconditioning has a neutral effect on the incidence of kidney injury after coronary artery bypass graft surgery. Kidney Int. 2015;87(2):473-481.
PubMed   |  Link to Article
Endre  ZH.  Renal ischemic preconditioning: finally some good news for prevention of acute kidney injury. Kidney Int. 2011;80(8):796-798.
PubMed   |  Link to Article
KDIGO AKI Work Group.  KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl. 2012;2:1-138.
Link to Article
Thakar  CV, Arrigain  S, Worley  S, Yared  JP, Paganini  EP.  A clinical score to predict acute renal failure after cardiac surgery. J Am Soc Nephrol. 2005;16(1):162-168.
PubMed   |  Link to Article
Kottenberg  E, Thielmann  M, Bergmann  L,  et al.  Protection by remote ischemic preconditioning during coronary artery bypass graft surgery with isoflurane but not propofol—a clinical trial. Acta Anaesthesiol Scand. 2012;56(1):30-38.
PubMed   |  Link to Article
Murphy  GS, Hessel  EA  II, Groom  RC.  Optimal perfusion during cardiopulmonary bypass: an evidence-based approach. Anesth Analg. 2009;108(5):1394-1417.
PubMed   |  Link to Article
Thielmann  M, Kottenberg  E, Kleinbongard  P,  et al.  Cardioprotective and prognostic effects of remote ischaemic preconditioning in patients undergoing coronary artery bypass surgery: a single-centre randomised, double-blind, controlled trial. Lancet. 2013;382(9892):597-604.
PubMed   |  Link to Article
Meersch  M, Schmidt  C, Van Aken  H,  et al.  Urinary TIMP-2 and IGFBP7 as early biomarkers of acute kidney injury and renal recovery following cardiac surgery. PLoS One. 2014;9(3):e93460.
PubMed   |  Link to Article
Yang  QH, Liu  DW, Long  Y, Liu  HZ, Chai  WZ, Wang  XT.  Acute renal failure during sepsis: potential role of cell cycle regulation. J Infect. 2009;58(6):459-464.
PubMed   |  Link to Article
Hausenloy  DJ, Mwamure  PK, Venugopal  V,  et al.  Effect of remote ischaemic preconditioning on myocardial injury in patients undergoing coronary artery bypass graft surgery: a randomised controlled trial. Lancet. 2007;370(9587):575-579.
PubMed   |  Link to Article
Cheung  MM, Kharbanda  RK, Konstantinov  IE,  et al.  Randomized controlled trial of the effects of remote ischemic preconditioning on children undergoing cardiac surgery: first clinical application in humans. J Am Coll Cardiol. 2006;47(11):2277-2282.
PubMed   |  Link to Article
Bøtker  HE, Kharbanda  R, Schmidt  MR,  et al.  Remote ischaemic conditioning before hospital admission, as a complement to angioplasty, and effect on myocardial salvage in patients with acute myocardial infarction: a randomised trial. Lancet. 2010;375(9716):727-734.
PubMed   |  Link to Article
Ali  ZA, Callaghan  CJ, Lim  E,  et al.  Remote ischemic preconditioning reduces myocardial and renal injury after elective abdominal aortic aneurysm repair: a randomized controlled trial. Circulation. 2007;116(11)(suppl):I98-I105.
PubMed
Venugopal  V, Laing  CM, Ludman  A, Yellon  DM, Hausenloy  D.  Effect of remote ischemic preconditioning on acute kidney injury in nondiabetic patients undergoing coronary artery bypass graft surgery: a secondary analysis of 2 small randomized trials. Am J Kidney Dis. 2010;56(6):1043-1049.
PubMed   |  Link to Article
Engler  RL, Yellon  DM.  Sulfonylurea KATP blockade in type II diabetes and preconditioning in cardiovascular disease: time for reconsideration. Circulation. 1996;94(9):2297-2301.
PubMed   |  Link to Article
Landoni  G, Biondi-Zoccai  GG, Zangrillo  A,  et al.  Desflurane and sevoflurane in cardiac surgery: a meta-analysis of randomized clinical trials. J Cardiothorac Vasc Anesth. 2007;21(4):502-511.
PubMed   |  Link to Article
Yu  CH, Beattie  WS.  The effects of volatile anesthetics on cardiac ischemic complications and mortality in CABG: a meta-analysis. Can J Anaesth.2006;53(9):906-918.
PubMed   |  Link to Article
Hausenloy  DJ, Erik Bøtker  H, Condorelli  G,  et al.  Translating cardioprotection for patient benefit: position paper from the Working Group of Cellular Biology of the Heart of the European Society of Cardiology. Cardiovasc Res. 2013;98(1):7-27.
PubMed   |  Link to Article
Gomez  H, Ince  C, De Backer  D,  et al.  A unified theory of sepsis-induced acute kidney injury: inflammation, microcirculatory dysfunction, bioenergetics, and the tubular cell adaptation to injury. Shock. 2014;41(1):3-11.
PubMed   |  Link to Article
Boonstra  J, Post  JA.  Molecular events associated with reactive oxygen species and cell cycle progression in mammalian cells. Gene. 2004;337:1-13.
PubMed   |  Link to Article
Devarajan  P.  Update on mechanisms of ischemic acute kidney injury. J Am Soc Nephrol. 2006;17(6):1503-1520.
PubMed   |  Link to Article
Kashani  K, Al-Khafaji  A, Ardiles  T,  et al.  Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013;17(1):R25:1-12.
PubMed   |  Link to Article
Tsung  A, Tohme  S, Billiar  TR.  High-mobility group box-1 in sterile inflammation. J Intern Med. 2014;276(5):425-443.
PubMed   |  Link to Article
Wu  H, Steenstra  R, de Boer  EC,  et al.  Preconditioning with recombinant high-mobility group box 1 protein protects the kidney against ischemia-reperfusion injury in mice. Kidney Int. 2014;85(4):824-832.
PubMed   |  Link to Article
Ryckwaert  F, Boccara  G, Frappier  JM, Colson  PH.  Incidence, risk factors, and prognosis of a moderate increase in plasma creatinine early after cardiac surgery. Crit Care Med. 2002;30(7):1495-1498.
PubMed   |  Link to Article
Dasta  JF, Kane-Gill  SL, Durtschi  AJ, Pathak  DS, Kellum  JA.  Costs and outcomes of acute kidney injury (AKI) following cardiac surgery. Nephrol Dial Transplant. 2008;23(6):1970-1974.
PubMed   |  Link to Article
Zappitelli  M, Bernier  PL, Saczkowski  RS,  et al.  A small post-operative rise in serum creatinine predicts acute kidney injury in children undergoing cardiac surgery. Kidney Int. 2009;76(8):885-892.
PubMed   |  Link to Article
Chertow  GM, Lazarus  JM, Christiansen  CL,  et al.  Preoperative renal risk stratification. Circulation. 1997;95(4):878-884.
PubMed   |  Link to Article
Parikh  CR, Coca  SG, Wang  Y, Masoudi  FA, Krumholz  HM.  Long-term prognosis of acute kidney injury after acute myocardial infarction. Arch Intern Med. 2008;168(9):987-995.
PubMed   |  Link to Article
Lafrance  JP, Miller  DR.  Acute kidney injury associates with increased long-term mortality. J Am Soc Nephrol. 2010;21(2):345-352.
PubMed   |  Link to Article
Chertow  GM, Burdick  E, Honour  M, Bonventre  JV, Bates  DW.  Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16(11):3365-3370.
PubMed   |  Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.
Participant Flow of Remote Ischemic Preconditioning in Patients Undergoing Cardiac Surgery
Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.
Analysis of Acute Kidney Injury Biomarkers

A, Analysis of urine (TIMP-2) × (IGFBP7) before and after remote ischemic preconditioning (RIPC) and cardiopulmonary bypass (CPB) (pre-RIPC, P = .33; post-RIPC, P = <.01; 4 h after CPB, P = .01; 12 h after CPB, P = .01; 24 h after CPB, P = .35) (lower and upper limit of the reference range, 0.03 [2.5 percentile] and 1.93 [97.5 percentile], respectively). B, Analysis of urine neutrophil gelatinase-associated lipocalin (NGAL) concentrations before and after RIPC and CPB (pre-RIPC, P = .79; post-RIPC, P = .72; 4 h after CPB, P = .04; 12 h after CPB, P = .74; 24 h after CPB, P = .28) (reference range, 153 ng/mL; 90% CI, 142 to 182 ng/mL). C, Analysis of HMGB-1 concentrations before and after RIPC (pre-RIPC, P = .23; post-RIPC, P = <.01) (reference range: mean, 0.39 ng/mL; upper limit of the reference range, 1.4 ng/mL [97.5 percentile]). Error bars indicate 95% CI. All P values are for comparison of RIPC vs control. HMGB-1 indicates high-mobility group box 1; (TIMP-2) × (IGFBP7) indicates the product of urine IGFBP7 (insulinlike growth factor–binding protein 7) and TIMP-2 (tissue inhibitor of metalloproteinases 2).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1.  Baseline and Operative Characteristics
Table Graphic Jump LocationTable 2.  Primary and Secondary Study Outcomes, by Group
Table Graphic Jump LocationTable 3.  Predictors of Acute Kidney Injury (AKI) and Concentration of Tissue Inhibitor of Metalloproteinases × Insulinlike Growth Factor–Binding Protein 7 Increase, Using Multivariable Logistic Regression

References

Thakar  CV, Worley  S, Arrigain  S, Yared  JP, Paganini  EP.  Improved survival in acute kidney injury after cardiac surgery. Am J Kidney Dis. 2007;50(5):703-711.
PubMed   |  Link to Article
Hobson  CE, Yavas  S, Segal  MS,  et al.  Acute kidney injury is associated with increased long-term mortality after cardiothoracic surgery. Circulation. 2009;119(18):2444-2453.
PubMed   |  Link to Article
Rosner  MH, Okusa  MD.  Acute kidney injury associated with cardiac surgery. Clin J Am Soc Nephrol. 2006;1(1):19-32.
PubMed   |  Link to Article
Landoni  G, Bove  T, Székely  A,  et al.  Reducing mortality in acute kidney injury patients: systematic review and international web-based survey. J Cardiothorac Vasc Anesth. 2013;27(6):1384-1398.
PubMed   |  Link to Article
Kharbanda  RK, Nielsen  TT, Redington  AN.  Translation of remote ischaemic preconditioning into clinical practice. Lancet. 2009;374(9700):1557-1565.
PubMed   |  Link to Article
Domanski  MJ, Mahaffey  K, Hasselblad  V,  et al.  Association of myocardial enzyme elevation and survival following coronary artery bypass graft surgery. JAMA. 2011;305(6):585-591.
PubMed   |  Link to Article
Gassanov  N, Nia  AM, Caglayan  E, Er  F.  Remote ischemic preconditioning and renoprotection: from myth to a novel therapeutic option? J Am Soc Nephrol. 2014;25(2):216-224.
PubMed   |  Link to Article
Jaeschke  H.  Mechanisms of liver injury, II: mechanisms of neutrophil-induced liver cell injury during hepatic ischemia-reperfusion and other acute inflammatory conditions. Am J Physiol Gastrointest Liver Physiol. 2006;290(6):G1083-G1088.
PubMed   |  Link to Article
Choi  YS, Shim  JK, Kim  JC,  et al.  Effect of remote ischemic preconditioning on renal dysfunction after complex valvular heart surgery: a randomized controlled trial. J Thorac Cardiovasc Surg. 2011;142(1):148-154.
PubMed   |  Link to Article
Zimmerman  RF, Ezeanuna  PU, Kane  JC,  et al.  Ischemic preconditioning at a remote site prevents acute kidney injury in patients following cardiac surgery. Kidney Int. 2011;80(8):861-867.
PubMed   |  Link to Article
Gallagher  SM, Jones  DA, Kapur  A,  et al.  Remote ischemic preconditioning has a neutral effect on the incidence of kidney injury after coronary artery bypass graft surgery. Kidney Int. 2015;87(2):473-481.
PubMed   |  Link to Article
Endre  ZH.  Renal ischemic preconditioning: finally some good news for prevention of acute kidney injury. Kidney Int. 2011;80(8):796-798.
PubMed   |  Link to Article
KDIGO AKI Work Group.  KDIGO clinical practice guideline for acute kidney injury. Kidney Int Suppl. 2012;2:1-138.
Link to Article
Thakar  CV, Arrigain  S, Worley  S, Yared  JP, Paganini  EP.  A clinical score to predict acute renal failure after cardiac surgery. J Am Soc Nephrol. 2005;16(1):162-168.
PubMed   |  Link to Article
Kottenberg  E, Thielmann  M, Bergmann  L,  et al.  Protection by remote ischemic preconditioning during coronary artery bypass graft surgery with isoflurane but not propofol—a clinical trial. Acta Anaesthesiol Scand. 2012;56(1):30-38.
PubMed   |  Link to Article
Murphy  GS, Hessel  EA  II, Groom  RC.  Optimal perfusion during cardiopulmonary bypass: an evidence-based approach. Anesth Analg. 2009;108(5):1394-1417.
PubMed   |  Link to Article
Thielmann  M, Kottenberg  E, Kleinbongard  P,  et al.  Cardioprotective and prognostic effects of remote ischaemic preconditioning in patients undergoing coronary artery bypass surgery: a single-centre randomised, double-blind, controlled trial. Lancet. 2013;382(9892):597-604.
PubMed   |  Link to Article
Meersch  M, Schmidt  C, Van Aken  H,  et al.  Urinary TIMP-2 and IGFBP7 as early biomarkers of acute kidney injury and renal recovery following cardiac surgery. PLoS One. 2014;9(3):e93460.
PubMed   |  Link to Article
Yang  QH, Liu  DW, Long  Y, Liu  HZ, Chai  WZ, Wang  XT.  Acute renal failure during sepsis: potential role of cell cycle regulation. J Infect. 2009;58(6):459-464.
PubMed   |  Link to Article
Hausenloy  DJ, Mwamure  PK, Venugopal  V,  et al.  Effect of remote ischaemic preconditioning on myocardial injury in patients undergoing coronary artery bypass graft surgery: a randomised controlled trial. Lancet. 2007;370(9587):575-579.
PubMed   |  Link to Article
Cheung  MM, Kharbanda  RK, Konstantinov  IE,  et al.  Randomized controlled trial of the effects of remote ischemic preconditioning on children undergoing cardiac surgery: first clinical application in humans. J Am Coll Cardiol. 2006;47(11):2277-2282.
PubMed   |  Link to Article
Bøtker  HE, Kharbanda  R, Schmidt  MR,  et al.  Remote ischaemic conditioning before hospital admission, as a complement to angioplasty, and effect on myocardial salvage in patients with acute myocardial infarction: a randomised trial. Lancet. 2010;375(9716):727-734.
PubMed   |  Link to Article
Ali  ZA, Callaghan  CJ, Lim  E,  et al.  Remote ischemic preconditioning reduces myocardial and renal injury after elective abdominal aortic aneurysm repair: a randomized controlled trial. Circulation. 2007;116(11)(suppl):I98-I105.
PubMed
Venugopal  V, Laing  CM, Ludman  A, Yellon  DM, Hausenloy  D.  Effect of remote ischemic preconditioning on acute kidney injury in nondiabetic patients undergoing coronary artery bypass graft surgery: a secondary analysis of 2 small randomized trials. Am J Kidney Dis. 2010;56(6):1043-1049.
PubMed   |  Link to Article
Engler  RL, Yellon  DM.  Sulfonylurea KATP blockade in type II diabetes and preconditioning in cardiovascular disease: time for reconsideration. Circulation. 1996;94(9):2297-2301.
PubMed   |  Link to Article
Landoni  G, Biondi-Zoccai  GG, Zangrillo  A,  et al.  Desflurane and sevoflurane in cardiac surgery: a meta-analysis of randomized clinical trials. J Cardiothorac Vasc Anesth. 2007;21(4):502-511.
PubMed   |  Link to Article
Yu  CH, Beattie  WS.  The effects of volatile anesthetics on cardiac ischemic complications and mortality in CABG: a meta-analysis. Can J Anaesth.2006;53(9):906-918.
PubMed   |  Link to Article
Hausenloy  DJ, Erik Bøtker  H, Condorelli  G,  et al.  Translating cardioprotection for patient benefit: position paper from the Working Group of Cellular Biology of the Heart of the European Society of Cardiology. Cardiovasc Res. 2013;98(1):7-27.
PubMed   |  Link to Article
Gomez  H, Ince  C, De Backer  D,  et al.  A unified theory of sepsis-induced acute kidney injury: inflammation, microcirculatory dysfunction, bioenergetics, and the tubular cell adaptation to injury. Shock. 2014;41(1):3-11.
PubMed   |  Link to Article
Boonstra  J, Post  JA.  Molecular events associated with reactive oxygen species and cell cycle progression in mammalian cells. Gene. 2004;337:1-13.
PubMed   |  Link to Article
Devarajan  P.  Update on mechanisms of ischemic acute kidney injury. J Am Soc Nephrol. 2006;17(6):1503-1520.
PubMed   |  Link to Article
Kashani  K, Al-Khafaji  A, Ardiles  T,  et al.  Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit Care. 2013;17(1):R25:1-12.
PubMed   |  Link to Article
Tsung  A, Tohme  S, Billiar  TR.  High-mobility group box-1 in sterile inflammation. J Intern Med. 2014;276(5):425-443.
PubMed   |  Link to Article
Wu  H, Steenstra  R, de Boer  EC,  et al.  Preconditioning with recombinant high-mobility group box 1 protein protects the kidney against ischemia-reperfusion injury in mice. Kidney Int. 2014;85(4):824-832.
PubMed   |  Link to Article
Ryckwaert  F, Boccara  G, Frappier  JM, Colson  PH.  Incidence, risk factors, and prognosis of a moderate increase in plasma creatinine early after cardiac surgery. Crit Care Med. 2002;30(7):1495-1498.
PubMed   |  Link to Article
Dasta  JF, Kane-Gill  SL, Durtschi  AJ, Pathak  DS, Kellum  JA.  Costs and outcomes of acute kidney injury (AKI) following cardiac surgery. Nephrol Dial Transplant. 2008;23(6):1970-1974.
PubMed   |  Link to Article
Zappitelli  M, Bernier  PL, Saczkowski  RS,  et al.  A small post-operative rise in serum creatinine predicts acute kidney injury in children undergoing cardiac surgery. Kidney Int. 2009;76(8):885-892.
PubMed   |  Link to Article
Chertow  GM, Lazarus  JM, Christiansen  CL,  et al.  Preoperative renal risk stratification. Circulation. 1997;95(4):878-884.
PubMed   |  Link to Article
Parikh  CR, Coca  SG, Wang  Y, Masoudi  FA, Krumholz  HM.  Long-term prognosis of acute kidney injury after acute myocardial infarction. Arch Intern Med. 2008;168(9):987-995.
PubMed   |  Link to Article
Lafrance  JP, Miller  DR.  Acute kidney injury associates with increased long-term mortality. J Am Soc Nephrol. 2010;21(2):345-352.
PubMed   |  Link to Article
Chertow  GM, Burdick  E, Honour  M, Bonventre  JV, Bates  DW.  Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J Am Soc Nephrol. 2005;16(11):3365-3370.
PubMed   |  Link to Article
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Multimedia

Supplement 1.

Trial Protocol

Supplemental Content
Supplement 2.

Collaborators

The RenalRIPC Investigators

eTable 1. Cleveland Clinic Foundation Score

eTable 2. KDIGO criteria

eFigure 1. Percentage of patients with postoperative AKI stratified by urinary (TIMP-2) × (IGFBP7) concentration

eFigure 2. Forest plot randomized controlled trials

eFigure 3. Proposed conceptual model for how RIPC results in fewer AKI events

Supplementary References

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