Next Article in Journal
Treatment of Peripheral Arterial Occlusive Disease around the Globe: Malta
Next Article in Special Issue
Risk Factors for Acute Kidney Injury Following Cardiac Surgery and Performance of Leicester Score in a Spanish Cohort
Previous Article in Journal
Does Humeral Component Version Affect Range of Motion and Clinical Outcomes in Reverse Total Shoulder Arthroplasty? A Systematic Review
Previous Article in Special Issue
Cardiac Surgery Associated AKI Prevention Strategies and Medical Treatment for CSA-AKI
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

CSA-AKI: Incidence, Epidemiology, Clinical Outcomes, and Economic Impact

1
Department of Anesthesia and Critical Care Medicine, University of Chicago, 5841 South Maryland Ave., MC4028, Chicago, IL 60637, USA
2
Section of Nephrology, Department of Medicine, University of Chicago, 5841 South Maryland Ave., Suite S-507, MC5100, Chicago, IL 60637, USA
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2021, 10(24), 5746; https://doi.org/10.3390/jcm10245746
Submission received: 15 November 2021 / Revised: 1 December 2021 / Accepted: 5 December 2021 / Published: 8 December 2021

Abstract

:
Cardiac surgery-associated acute kidney injury (CSA-AKI) is a common complication following cardiac surgery and reflects a complex biological combination of patient pathology, perioperative stress, and medical management. Current diagnostic criteria, though increasingly standardized, are predicated on loss of renal function (as measured by functional biomarkers of the kidney). The addition of new diagnostic injury biomarkers to clinical practice has shown promise in identifying patients at risk of renal injury earlier in their course. The accurate and timely identification of a high-risk population may allow for bundled interventions to prevent the development of CSA-AKI, but further validation of these interventions is necessary. Once the diagnosis of CSA-AKI is established, evidence-based treatment is limited to supportive care. The cost of CSA-AKI is difficult to accurately estimate, given the diverse ways in which it impacts patient outcomes, from ICU length of stay to post-hospital rehabilitation to progression to CKD and ESRD. However, with the global rise in cardiac surgery volume, these costs are large and growing.

1. Introduction

Acute kidney injury (AKI) is currently defined by increases in serum creatinine and decreases in urine output over time. The Kidney Disease Improving Global Outcomes (KDIGO) consensus definition of AKI defines stage 1 AKI as a rise of ≥0.3 mg/dL within 48 h or an increase of ≥1.5 times baseline over 7 days, or urine output of <0.5 mL/kg for 6 h with the subsequent stages representing more severe kidney injury ([1], Table 1).
AKI occurs in approximately 20–30% of patients following cardiac surgery, and while there is no specific definition of cardiac surgery-associated AKI (CSA-AKI), clinicians apply the aforementioned KDIGO criteria. This high incidence of CSA-AKI reflects an interaction between patient co-morbidities and their peri- and intra-operative care [2,3,4]. While the development of AKI in this population typically occurs in older, sicker patients who require more complex surgeries, there are patients without these risk factors who still develop CSA-AKI [5]. Many of these established preoperative risk factors lead to longer operations with prolonged exposure to cardio-pulmonary bypass (CPB) and aortic cross clamping; an extended duration of inadequate circulation; and accompanying supportive care measures including inotropes, vasopressors, fluid and blood administration, and mechanical circulatory support [3].
Standardizing the definition of AKI into the KDIGO definition (and its predecessors) has advanced our understanding of AKI and improved epidemiologic AKI research. Newer biomarkers may be able to quickly and accurately diagnose kidney injury and specify patient phenotypes, including those whose AKI will persist (longer duration) or progress (worsen severity) [6,7,8,9]. There are growing calls for these biomarkers to be incorporated into routine clinical practice for use in risk stratification and diagnosis of AKI [10,11]. The importance of a deeper understanding of CSA-AKI is further magnified when considering the large economic impact and adverse patient outcomes associated with AKI [12,13]. In this review, we will examine the incidence and epidemiology of CSA-AKI, risk stratification including the importance of emerging biomarkers, various treatments and bundles, patient outcomes, and economic impact.

1.1. Risk Factors and Scoring

Risk factors of CSA-AKI can be categorized into patient and intra- and postoperative factors. Currently, a patient’s preoperative risk factors are largely non-modifiable and include demographics, such as age and gender; conditions such as hypertension, hyperlipidemia, diabetes mellitus, and vascular disease; and end-organ sequelae such as chronic kidney or liver disease, anemia, and previous stroke [3] (Table 2).
Many if not all of these risk factors also underlie the indications for cardiac surgery with chronic kidney disease, often being amongst the most prominent factors associated with CSA-AKI [14]. The patient’s preoperative hemodynamics and urgency of the surgical indication (e.g., emergency aortic dissection repairs or coronary artery bypass grafting) also increase risk, especially in conditions such as acute coronary syndrome and cardiogenic shock that require an intra-aortic balloon pump (IABP). The three commonly used scoring systems that consolidate these risk factors into predictive models for postoperative AKI and receipt of renal replacement therapy (RRT) are the Cleveland Clinic model, the Mehta Score, and the Simplified Renal Index [15,16,17]. These three systems use differing patient variables and have varying discrimination, but the Cleveland Clinic model has the highest level of discrimination in one validation study with an area under the ROC of 0.86 for postoperative RRT and 0.81 for postoperative stage 2 AKI by AKI-Network (AKIN) criteria (which is identical to KDIGO stage 2) [18] (Table 3).
While there is a focus on preventing severe and dialysis-requiring AKI because it is a major cost-burden and carries the highest morbidity and mortality, it is important to remember that over 90% of CSA-AKI is stage 1 (though this is also associated with adverse patient outcomes compared to those who do not develop AKI) [19].
Non-patient factors that confer greater risk of AKI include more complex operations, such as combination CABG and valve repair/replacement that require longer time spent on CPB and with the aorta cross-clamped [3,13]. Additionally, difficulty separating from CPB or the need to go back to full CPB support are also associated with increased risk of AKI. Anesthetic management and patient physiology that lead to hypoperfusion, hypovolemia or anemia, venous congestion, and need for inotropes further exacerbate the risk [20].
Administering intravenous colloid or crystalloid can optimize the circulation by increasing preload, which may increase stroke volume and cardiac output. Modern indicators of whether a patient’s circulation will benefit from additional fluid (so-called “fluid responsiveness”) are generally based on dynamic tests where cardiac output, stroke volume, or pulse pressure are measured during different loading conditions. Some common tests include passive leg raise where the venous blood that typically pools in a patient’s legs is returned to the circulation by leg elevation, and the resulting change in cardiac output is measured by echocardiography or esophageal doppler and pulse pressure variation (PPV) where larger changes in pulse pressure (and stroke volume) over the positive pressure respiratory cycle indicate that administering more fluid will increase cardiac output [21,22]. These goal-directed endpoints of fluid administration perform better than static indicators, such as central venous pressure or pulmonary artery occlusion pressure, at predicting improvement in cardiac output after fluid administration [23]. However, the data on perioperative fluid administration are mixed on whether a liberal or restrictive perioperative strategy is optimal; it likely depends on specific patient pathophysiology with conditions such as aortic stenosis, requiring higher cardiac filling pressures and more fluid resuscitation [24]. Fluid overload, often defined as gaining 10% above admission weight (e.g., an 80 kg patient gaining 8 kg or more of retained fluid weight), has long been known to be associated with adverse outcomes in the setting of AKI [25]. This holds true in CSA-AKI as well, where several studies have shown that there is an association between the degree of positive fluid balance (intra- and postoperative) and the development of postoperative CSA-AKI as well as an association with other adverse patient outcomes [26,27].
An emerging area in risk stratification is the combination of patient demographic factors and novel serum and urine biomarkers, rather than creatinine and urine output [28,29]. The success of many preventative treatment strategies rests on the ability to correctly identify patients at highest risk of developing AKI, and assess this risk prior to major changes in serum creatinine or urine output. Before delving into novel blood and urine biomarkers, there is emerging literature around the concept of renal reserve and its ability to predict the future development of CSA-AKI. At its core is the concept that at baseline, the kidney is not working at its maximum glomerular filtration rate (GFR), and that if stressed (e.g., with a large protein load or in the setting of pregnancy), the kidney will begin to hyperfilter, increasing the GFR by more than 20% [30,31]. In a series of recent papers, Ronco and colleagues have demonstrated that patients with an increased renal reserve (larger increase in GFR following a protein load) are less likely to develop postoperative CSA-AKI. They measured preoperative renal reserve with a protocolized protein load of 1.2 g/kg and demonstrated that in a cohort of 110 patients undergoing cardiac surgery, reserves were significantly lower in those who went on to develop CSA-AKI, and that preoperative reserves provided an area under the ROC of 0.83 (95% CI 0.70–0.96) for the future development of postoperative AKI [32]. While the physiology behind renal reserve is well grounded, future studies should investigate its impact on AKI risk and determine if certain interventions can reduce the incidence of AKI in those with diminished reserves.

1.2. Diagnosis and Biomarkers

The current definition of AKI is based on the Kidney Disease Improving Global Outcomes (KDIGO) criteria (Table 1). As previously mentioned, there were consensus definitions prior to KDIGO with the Risk, Injury, Failure, Loss, End-stage (RIFLE) and AKI-Network (AKIN) being the most commonly used and reported, both in the setting of CSA-AKI and other forms of kidney injury [33,34]. The KDIGO criteria meld these other two and allow for earlier disease detection by including smaller increases in baseline creatinine [35]. Though representing an advance toward standardizing AKI diagnosis, this definition still relies exclusively on evidence of functional changes of the kidney in serum creatinine and urine output. Thus, the current system fails to quantify the cellular and tubular injury that precedes drops in glomerular filtration, which results in low urine output and renal dysfunction. Newer biomarkers involved in tubular ischemia and cell cycle arrest that allow prediction of progression to AKI include neutrophil gelatinase-associated lipocalin (NGAL), insulin-like growth factor-binding protein 7 (IGFBP7), and tissue inhibitor of metalloproteinases-2 (TIMP-2). Taken together, IGFBP7 and TIMP-2 concentrations in urine have demonstrated predictive capability in cardiac surgical AKI and are now FDA-approved under the name Nephrocheck® [8]. NGAL has been shown to independently predict duration of ICU and hospital length of stay, even when AKI was negative by creatinine measurements [6]. As these biomarkers become more widely used in clinical practice, they are likely to be incorporated into diagnostic criteria of AKI in the future [10]. An in-depth discussion of the benefits and limitations of these biomarkers of AKI are beyond the scope of this review and are discussed elsewhere within this edition.

1.3. Pathophysiology

The discovery and validation of new biomarkers are contingent on a more robust understanding of the pathophysiology of acute kidney injury, which is complex and heterogenous. While an in-depth discussion of the pathophysiology is beyond the scope of this paper, we will briefly discuss it here. At the organismal level, changes in hemodynamics play an important role in the development of CSA-AKI. Arterial hypotension, low perfusion from low cardiac output, elevated venous pressures, hypovolemia, anemia and hemolysis, ischemia and reperfusion, and changes from a pulsatile to non-pulsatile circulation during CPB all likely play a role [5] (Figure 1).
At the organ level, renal perfusion is highly controlled, since blood brings oxygen and nutrients but can also increase the filtration demands on the kidney. Higher blood flow requires more energy expenditure from ion transport pumps to main electrolyte gradients, increasing metabolic demand. The cortico-medullary junction, in particular, may be at elevated risk of ischemia given its low resting PO2 of 10–20 mmHg [36]. Any imbalance in oxygen delivery and consumption due to microemboli (atheroembolic or thromboembolic), arterial hypoxia, or low flow (due to arterial hypotension, venous hypertension, or neurohormonal vasoconstriction) can cause organ damage [37,38,39].
At the cellular level, the predominant mechanisms of injury include the interrelated cycle of inflammation and reactive oxide species (ROS) production. Contact of the circulating blood volume with the CPB circuit causes immune activation as evidenced by measurable increases in IL-6 (an inflammatory cytokine) and IL-10 (an anti-inflammatory cytokine), and, the higher the level of IL-6, the higher the corresponding risk of subsequent AKI [40]. In some studies, avoidance of CPB by “off-pump” techniques in CABG has been associated with lower rates of AKI, which will be discussed in more depth below [41,42,43].
Hemolysis, as a response to the extra-corporeal membrane and CPB circuit, also plays a role in CSA-AKI. It releases free hemoglobin which binds nitric oxide leading to vasoconstriction, increase ROS production, and induces heme oxygenase 1 expression which is associated with increased rates of AKI in experimental models and following cardiac surgery [44,45]. In a case-control study of 10 patients undergoing cardiac surgery who developed CSA-AKI compared to 10 risk-matched cardiac surgical patients who did not, free hemoglobin levels were more than double in the CSA-AKI group. [46].

2. Clinical Care

There have been several investigations into preventing the development of CSA-AKI by identifying those at high risk, and delivering algorithmic, bundled care [11,29,47]. These protocols aim to achieve an adequate intra- and postoperative circulation by an algorithmic approach to volume administration, pressors, and inotropes to avoid hypotension, venous congestion, and hypoperfusion [11,29,47,48,49]. Specific singular agent interventions have largely failed to prevent AKI; this is in part because of what we have labeled as CSA-AKI is likely a conglomerate of several pathophysiologic processes that all end in a common pathway of tubular injury (Table 4).
Once the diagnosis of CSA-AKI is established, specific treatments are lacking and limited to standard supportive critical care, adequate nutrition, glycemic control, and RRT [3]. However as discussed below, recent interventions that have combined early identification with biomarkers with kidney-focused care bundles have demonstrated promising outcomes [28,29].

2.1. Prevention

True primary prevention of AKI would be the most effective way to limit the subsequent harms associated with renal failure. However, while many different interventions have been studied, there is no definitive prevention for CSA-AKI [29,49] (Table 4). In general, despite physiologic plausibility and early success in animal models, all specific singular interventions have not reliably resulted in improvement in renal outcomes. These include pharmacologic agents, such as fenoldopam, so called “renal-dose” dopamine, sodium bicarbonate, acetaminophen, dexmedetomidine, propofol, N-acetylcysteine, and steroids; non-pharmacologic interventions, such as remote ischemic preconditioning; and changes in surgical technique, such as avoiding CPB or percutaneous valve replacement (Table 4). Flaws with these previous studies may have been the lack of standardized diagnostic criteria of AKI or the inability to accurately identify patients at high risk of AKI to appropriately tailor therapies.
To that end, Meersch, Zarbock et al. performed the PrevAKI trial, a single-center randomized controlled trial which identified cardiac surgical patients at high risk of AKI by using urinary TIMP-2 and IGFBP7 (Nephrocheck®) four hours after CPB (Table 5). In total, 276 patients were randomized to a control group where standard care included keeping MAP > 65 mmHg and CVP between 8–10 mmHG, and starting angiotensin converting enzyme inhibitors (ACEi) or angiotensin II receptor blockers (ARBs) once hemodynamics stabilized and the patient became hypertensive. The intervention group received a bundled care package consisting of strict KDIGO guidelines for avoidance of nephrotoxic agents, holding ACEi or ARBs for 48 h postoperatively, close monitoring of serum Cr and urine output, avoidance of hyperglycemia, consideration of alternatives to radiocontrast agents, and PiCCO catheter-guided algorithmic approach to hemodynamic and volume monitoring and management. The algorithm involved first administering crystalloid to a stroke volume variation of < 11, next adding dobutamine or epinephrine for a cardiac index of <3 L/min/m2, and finally using norepinephrine to achieve an MAP > 65 mmHg. Adherence to this protocol by the intervention group resulted in significantly more dobutamine (31.1% vs. 9.4%, p < 0.001), less hyperglycemia (50.7% vs. 75.4%, p < 0.001), and fewer ACEi/ARBs (10.9% vs. 30.4%, p < 0.001). The primary outcome was the occurrence of any stage KDIGO AKI at 72 h after surgery with secondary outcomes including AKI severity; mortality; RRT; persistent renal dysfunction (PRD; defined as a ≥0.5 rise in serum Cr from preoperative baseline); length of ICU stay and hospitalization; and a composite of death, RRT, and PRD. There was a statistically significant decrease in all-stage AKI in the intervention group compared to control (55.1% vs. 71.7%, p = 0.004, absolute risk reduction 16.6% with 95% CI 5.5–27.9%). KDIGO stage 2 and 3 AKI were also lower in the treatment group (29.7% vs. 44.9%, p = 0.009). There were no significant differences for any of the other secondary outcomes, which the authors hypothesized could be due to the relatively short follow-up of 90 d, the majority of AKI being mild or moderate (despite multiple observational studies correlating mild to moderate AKI with long term kidney decline), and most AKI being diagnosed based on oliguria (which has not been associated with poor outcomes in a specifically cardiac surgical cohort) [49]. This single-center study was used as a template for a multi-center study in PrevAKI 2, where the primary outcome was adherence to the bundled measures. Adherence was higher in the intervention group and led to increased use of crystalloid volume administration and dobutamine for a higher MAP than the control group. In the secondary outcomes, rates of moderate to severe AKI were lower in the intervention arm, but there were no statistically significant reductions in RRT or mortality. However, again, the study was underpowered with only 280 patients (Table 5) [29].
Another study identifying the importance of applying care bundles to patients at high risk of CSA-AKI was conducted by Engelman et al. They analyzed 435 patients before and 412 after the introduction of NephroCheck use to screen cardiac surgical patients (excluding those with preoperative Cr of >2.0 and on dialysis) on postoperative day one for risk of AKI. Different NephroCheck values were used for stratification. Values of <0.3 (ng/mL)2/1000 prompted normal care, “fast tracking” patients to stepdown units if they met other ICU discharge criteria. An intermediate group with NephroCheck values of 0.3–2.0 required hourly UOP monitoring, the avoidance of nephrotoxins (non-steroidal anti-inflammatory drugs, ARBs/ACEi, vancomycin, and gentamicin), repeat NephroCheck at 24 h, and, if the patient had urine output of <0.5 mL/kr/h for 3 h, the activation of an “acute kidney response team” (AKRT). NephroCheck values of >2.0 resulted in activating the AKRT, composed of intensivists, nephrologists, cardiac surgeons, nurses, and advanced practitioners. The AKRT used an algorithm based on the same KDIGO recommendations as the PrevAKI trial to avoid nephrotoxins, discontinue ACEi/ARBs, avoid hyperglycemia, closely monitor urine output, and manage hemodynamics. This was completed using an algorithmic approach to administer fluids, inotropes, and pressors to maintain a cardiac index > 2.5 L/min/M2, systolic blood pressure > 130 mmHg, mixed venous O2 > 60%, minimize serum lactate, and optimize echocardiographic parameters. The trial did not include information on the specific algorithm or differences in dosages of inotropes, pressors, and fluids between the two groups. The primary endpoint was the development of KDIGO stage 2 and 3 AKI by serum Cr only, which occurred in 10 patients (2.3%) before NephroCheck versus 1 patient (0.24%) after NephroCheck (p = 0.01). After propensity score matching, of 338 patients before and after the intervention, 8 (2.4%) had stage 2 or 3 AKI versus only 1 (0.3%; p = 0.04%). Importantly, given the low severe AKI rates in the cohort, they looked at secondary outcomes, such as total length of stay, cost, 30-day mortality, and 30-day readmission rate finding no significant difference. Without randomization or detailed data on differences in doses of fluid, inotrope, and pressor interventions, the authors concluded that this protocol is hypothesis generating, and needs to be tested a priori in a larger, multi-center randomized controlled trial (Table 5) [28].
Another area of interest in prevention of AKI is remote ischemic preconditioning (RIPC). Initially described for myocardial protection in the 1980s by Murry et al., the underlying mechanism involves using brief periods of ischemia to activate stress pathways, which attenuate injury when cells are subjected to subsequent ischemia [72]. Observations that ischemia acted on more distant tissues led to the concept of RIPC which has been demonstrated for other organs including the kidneys [73,74,75,76]. Multiple small clinical trials from 2007–2015 in various surgical populations suggested a benefit to renal outcomes from RIPC [77,78]. This led to several large, randomized, placebo-controlled trials published in 2015; the largest of these two, from Meybohm et al. and Hausenloy et al., comprised over 3000 patients undergoing cardiac surgery (CABG and/or valve repair and replacement) and failed to demonstrate any difference in outcomes, however the populations had relatively low rates of CKD and were not identified to be at elevated risk of AKI [67,68]. In an editorial in the British Journal of Anesthesia in 2020, Zarbock, Kellum et al. argued that RIPC may still be an effective preventative measure for perioperative AKI with better understanding of the interaction between the autonomic nervous system and RIPC. In the perioperative period, an anesthetized patient’s autonomic nervous system does not respond normally to any stimulus. Additionally, the autonomic nervous system of patients with cardiac dysfunction may alter the response to RIPC. Zarbock argues that RIPC may still be effective if it can be more appropriately tailored to individual patients and their autonomic nervous systems, perhaps warranting future investigation [79]. In a meta-analysis of RCTs, a sub-group analysis of RIPC in propofol-free anesthesia demonstrated a reduction in AKI (32.7% in RIPC vs. 47.5% in sham, RR 0.700, p = 0.014, 95% CI 0.527–0.930), though this difference did not persist in a Propofol-based anesthetic (23.7% in RIPC vs. 24.9%, RR 0.928, p = 0.39, 95% CI 0.781–1.102) [80]. This finding may be another suggestion of the importance of the interaction between RIPC and the autonomic effects of anesthetic agents.

2.2. Treatment

Treatment once a diagnosis of AKI is established is, at present, limited to standard supportive care, including, when appropriate, RRT. Though some experimental therapies, such as stem cell infusion and alkaline phosphatase have shown promise in animal models and septic humans, at present there have not been studies in the context of cardiac surgery [81,82,83,84]. Holding ACE-inhibitors and ARBs perioperatively is usually recommended due to associations with hypotension on induction of general anesthesia, but links to more significant outcomes, such as MI or AKI, are controversial [5]. In a recent meta-analysis of nine trials (five RCTs, four cohort studies) including 6022 patients on chronic ACEi/ARBs there was no difference in mortality (OR 0.97, 95% CI 0.62–1.51) or major adverse cardiac events (OR 1.12, 95% CI 0.82–1.52), though withholding ACEi/ARBs resulted in less intraoperative hypotension (OR 0.63, 95% CI 0.47–0.85) [85]. Avoiding nephrotoxins, such as NSAIDs is recommended in most AKI settings [1]. Though controversy remains about the impact of modern radiocontrast agents on renal function, using the lowest acceptable dose in a euvolemic patient for an indicated study or intervention is an acceptable approach [86,87]. Often the benefits, such as an interventional radiology procedure in an unstable, bleeding patient, will outweigh the risks of contrast exposure. In the case of bleeding, a timely intervention to minimize transfusion is especially important, since transfusion is associated with AKI [88,89,90].
Nutrition support is another aspect of modern critical care where AKI complicates clinical care. In the setting of AKI, especially if requiring RRT, clinicians must alter their traditional total intake goals as well as change their protein intake targets. Goals of at least 20–30 kcal/kg/day (with higher total calorie and protein requirements for patients on RRT) should be targeted by using enteral or parenteral support where appropriate [1,91]. Coupled with nutritional support is glycemic control, with the goal of a blood glucose concentration between 80 and 150 mg/dL [1].
In the case of severe AKI with oliguria, hyperkalemia, acidosis, or uremia, RRT is the therapeutic mainstay. The options of frequency, modality (either continuous or intermittent), and dose are not associated with outcome differences [3]. Continuous RRT provides more hemodynamic stability than intermittent treatments, and is often used in the critically ill population, but has never been consistently shown to improve patient outcomes. RRT in mechanical circulatory support has its own attendant complexities but most often a continuous technique is used [92]. Trials of early versus late timing of initiating RRT in AKI suggest a benefit to early initiation, as long as the patient population has a high likelihood of AKI progression [93,94,95]. However, a recent examination of RRT timing did not demonstrate improved patient outcomes in a large scale, international randomized controlled trial; in fact, early initiation (in a non-CSA-AKI specific population) was linked to a greater dependence on RRT 90 days later [96].

3. Outcomes and Cost

3.1. Outcomes

CSA-AKI is associated with significantly increased risk of morbidity and mortality in both the acute postoperative period and in the ensuing years following surgery [12]. The short-term morbidity associated with AKI includes infections, prolonged mechanical ventilation, strokes, and myocardial infarctions, all of which are associated with longer ICU and hospital length of stay [97,98]. In the near-term, post-discharge rehabilitation or healthcare requirements are more complex in patients with AKI, with 73.7% discharged to continuing care vs. 52.3% without AKI (p < 0.001) [13]. In addition to these other conditions, long-term sequelae of CSA-AKI include the development of incident chronic kidney disease (CKD) and progression of previously established CKD, including its most severe form, end-stage renal disease (ESRD) [99,100,101]. A 2012 systematic review and meta-analysis by Coca et al. attempted to quantify the risk of progression from AKI to CKD or ESRD. It included 13 studies involving patients from 1975–2005 in a mixed medical and surgical population (only one study specific to cardiac surgery), totaling nearly 1.5 million patients. The majority of the included studies were retrospective database analyses and had varying definitions of initial AKI, though follow-up was mostly over two years. They calculated pooled hazard ratios (HRs) of 8.8 (95% CI 3.1–25.5, p < 0.0001, Z = 4.02) and 3.1 (95% CI 1.9–5.0, p < 0.00001, Z = 4.58) for progression to CKD and ESRD, respectively, among patients with any definition and degree of AKI. Additionally, Coca et al. observed that increasing severity of AKI corresponded with increasing HR of CKD (mild AKI with HR 2.0, moderate AKI with HR 3.2, severe AKI with HR 28) and ESRD (mild with HR 2.3, moderate with HR 5.0, severe with HR 8.0). The Translational Research Investigating Biomarker Endpoints in AKI (TRIBE-AKI) cohort consisted of 1251 who underwent cardiac surgery at two Canadian study sites, with monitoring of renal function including urinary and serum biomarkers. A sub-group of 613 of these patients were monitored for progression to CKD over a median follow-up of 5.6 years, and demonstrated a similar pattern with increasing severity of AKI by AKIN criteria. Without in-hospital postoperative AKI, 23.8% of patients progressed to CKD, but with stage 2 or 3 AKI 50% progressed to CKD [102]. The progression to CKD after CTS-AKI represents another area where biomarkers may add additional prognostic information. In the TRIBE-AKI cohort, epidermal growth factor (EGF) and monocyte chemoattractant protein-1 (MCP-1) were strongly associated with the risk of progression to CKD [103].
For non-renal morbidity, Hansen et al. found a composite of myocardial infarction, heart failure, or stroke at 5 years after cardiac surgery to be 24.9% for patients with postoperative AKI versus 12.1% for patients without AKI [98]. Regardless of the outcome studied, increasing severity of AKI corresponds with an increasing likelihood of morbidity. Mortality is also highly correlated with CSA-AKI, both in the long and short term [4,12]. In their meta-analysis of global cardiac surgical patients, Hu et al. calculated in-hospital mortality to be over seven times higher in patients who developed AKI than in those who did not (10.7% vs. 1.37%), and mortality at 1 to 5 years to be over 2.5 times higher (30.0% vs. 11.9%) [4]. Small changes in Cr and duration of AKI also appear to be important prognostic factors [19,104]. In one single-center study even a small increase in Cr (Δ0.1 to 0.5 mg/dL) was associated with a threefold increase in 30-day mortality [104]. In a prospective observational study, Brown et al. found increased mortality in both the short and long term with a longer duration of AKI diagnosed by AKIN criteria. When using propensity-matching, they found an HR for death at five years of 1.71 (95% CI 1.37–2.13) with AKI of 1–2 days, 2.08 (95% CI 1.32–3.30) with AKI of 3–6 days, and 4.78 (95% CI 3.08–7.44) with AKI duration of >6 days [19]. Even complete resolution of AKI is not associated with a return to baseline mortality; in one single-center study, patients who had complete normalization of serum Cr following CTS-AKI still exhibited increased mortality at two years with a relative risk (RR) of 1.8 (p = 0.001) [99].

3.2. Cost

Mirroring the morbidity and mortality associated with AKI, the related costs are also increased in both the short and long term. Short-term costs are incurred from increased ICU and hospital LOS with the additional supportive interventions this entails (mechanical ventilation, antibiotic/pressor/intrope administration, RRT, etc.) [12,13]. In one study from Germany on TAVR patients, post-procedural stage 3 AKI was even more expensive than requiring placement of a second valve [105]. In a study of the largest in-patient registry of hospitals in the United States, Alshaikh et al. found an increase in hospital costs in post-cardiac surgical patients of almost $26,000 associated with AKI without RRT, and over $69,000 for AKI with RRT, leading to a total annual cost for AKI in cardiac surgical patients approaching 1 billion dollars [13]. Medium-term costs can be incurred from medically complex discharges; Hobson et al. found discharge to home after cardiac surgery occurred in 90% of patients without postoperative AKI versus only 68% of patients with AKI [97]. Long term costs related to associated comorbidities, such as cardiovascular disease and CKD or ESRD become even more difficult to calculate but are likely in the billions of dollars [12,13,106].

4. Conclusions

CSA-AKI is common in cardiac surgery and reflects a complex biological combination of patient pathology, perioperative stress, and medical management. Current diagnostic criteria, though increasingly standardized, are predicated on loss of renal function. The addition of diagnostic biomarkers to clinical practice may be able to identify patients at risk of renal injury earlier in their course. The accurate and timely identification of a high-risk population may in turn allow for bundled interventions to prevent the development of CSA-AKI, but further validation of these interventions is necessary. Once the diagnosis of CSA-AKI is established, treatment is limited to standard supportive care. The cost of CSA-AKI is difficult to accurately estimate, given the diverse ways in which it impacts patient outcomes, from ICU length of stay to post-hospital rehabilitation to progression to CKD and ESRD. However, with the global rise in surgical volume, including cardiac surgery, these costs are undoubtedly large and growing.

Author Contributions

A.S. and J.L.K. prepared and edited the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This publication received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

Koyner has received research funding from the NIH, Astute-Biomerieux, Bioporto, NxStage, Satellite Healthcare, Fresenius. He has received prior consulting fees from Astute-Biomerieux, Sphingotec and Bioporto and speaking fees from NxState Medical. Schurle has no disclosures.

References

  1. Khwaja, A. KDIGO clinical practice guidelines for acute kidney injury. Nephron. Clin. Pract. 2012, 120, c179–c184. [Google Scholar] [CrossRef]
  2. Lagny, M.G.; Jouret, F.; Koch, J.N.; Blaffart, F.; Donneau, A.F.; Albert, A.; Roediger, L.; Krzesinski, J.M.; Defraigne, J.O. Incidence and outcomes of acute kidney injury after cardiac surgery using either criteria of the RIFLE classification. BMC Nephrol. 2015, 16, 76. [Google Scholar] [CrossRef] [Green Version]
  3. O’Neal, J.B.; Shaw, A.D.; Billings, F.T.T. Acute kidney injury following cardiac surgery: Current understanding and future directions. Crit. Care 2016, 20, 187. [Google Scholar] [CrossRef] [Green Version]
  4. Hu, J.; Chen, R.; Liu, S.; Yu, X.; Zou, J.; Ding, X. Global Incidence and Outcomes of Adult Patients with Acute Kidney Injury after Cardiac Surgery: A Systematic Review and Meta-Analysis. J. Cardiothorac. Vasc. Anesth. 2016, 30, 82–89. [Google Scholar] [CrossRef]
  5. Nadim, M.K.; Forni, L.G.; Bihorac, A.; Hobson, C.; Koyner, J.L.; Shaw, A.; Arnaoutakis, G.J.; Ding, X.; Engelman, D.T.; Gasparovic, H.; et al. Cardiac and Vascular Surgery-Associated Acute Kidney Injury: The 20th International Consensus Conference of the ADQI (Acute Disease Quality Initiative) Group. J. Am. Heart Assoc. 2018, 7, e008834. [Google Scholar] [CrossRef] [Green Version]
  6. Haase, M.; Devarajan, P.; Haase-Fielitz, A.; Bellomo, R.; Cruz, D.N.; Wagener, G.; Krawczeski, C.D.; Koyner, J.L.; Murray, P.; Zappitelli, M.; et al. The outcome of neutrophil gelatinase-associated lipocalin-positive subclinical acute kidney injury: A multicenter pooled analysis of prospective studies. J. Am. Coll. Cardiol. 2011, 57, 1752–1761. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  7. Koyner, J.L.; Garg, A.X.; Coca, S.G.; Sint, K.; Thiessen-Philbrook, H.; Patel, U.D.; Shlipak, M.G.; Parikh, C.R.; Consortium, T.-A. Biomarkers predict progression of acute kidney injury after cardiac surgery. J. Am. Soc. Nephrol. 2012, 23, 905–914. [Google Scholar] [CrossRef] [PubMed]
  8. Meersch, M.; Schmidt, C.; Van Aken, H.; Martens, S.; Rossaint, J.; Singbartl, K.; Gorlich, D.; Kellum, J.A.; Zarbock, A. Urinary TIMP-2 and IGFBP7 as Early Biomarkers of Acute Kidney Injury and Renal Recovery following Cardiac Surgery. PLoS ONE 2014, 9, e93460. [Google Scholar]
  9. Massoth, C.; Kullmar, M.; Enders, D.; Kellum, J.A.; Forni, L.G.; Meersch, M.; Zarbock, A.; Progressive, A.K.I.G. Comparison of C-C motif chemokine ligand 14 with other biomarkers for adverse kidney events after cardiac surgery. J. Thorac. Cardiovasc. Surg. 2021. [Google Scholar] [CrossRef] [PubMed]
  10. Ostermann, M.; Zarbock, A.; Goldstein, S.; Kashani, K.; Macedo, E.; Murugan, R.; Bell, M.; Forni, L.; Guzzi, L.; Joannidis, M.; et al. Recommendations on Acute Kidney Injury Biomarkers from the Acute Disease Quality Initiative Consensus Conference: A Consensus Statement. JAMA Netw. Open 2020, 3, e2019209. [Google Scholar] [CrossRef] [PubMed]
  11. Engelman, D.T.; Ben Ali, W.; Williams, J.B.; Perrault, L.P.; Reddy, V.S.; Arora, R.C.; Roselli, E.E.; Khoynezhad, A.; Gerdisch, M.; Levy, J.H.; et al. Guidelines for Perioperative Care in Cardiac Surgery: Enhanced Recovery after Surgery Society Recommendations. JAMA Surg. 2019, 154, 755–766. [Google Scholar] [CrossRef] [PubMed]
  12. Lysak, N.; Bihorac, A.; Hobson, C. Mortality and cost of acute and chronic kidney disease after cardiac surgery. Curr. Opin. Anaesthesiol. 2017, 30, 113–117. [Google Scholar] [CrossRef] [Green Version]
  13. Alshaikh, H.N.; Katz, N.M.; Gani, F.; Nagarajan, N.; Canner, J.K.; Kacker, S.; Najjar, P.A.; Higgins, R.S.; Schneider, E.B. Financial Impact of Acute Kidney Injury after Cardiac Operations in the United States. Ann. Thorac. Surg. 2018, 105, 469–475. [Google Scholar] [CrossRef] [Green Version]
  14. Guan, C.; Li, C.; Xu, L.; Zhen, L.; Zhang, Y.; Zhao, L.; Zhou, B.; Che, L.; Wang, Y.; Xu, Y. Risk factors of cardiac surgery-associated acute kidney injury: Development and validation of a perioperative predictive nomogram. J. Nephrol. 2019, 32, 937–945. [Google Scholar] [CrossRef] [PubMed]
  15. Thakar, C.V.; Arrigain, S.; Worley, S.; Yared, J.P.; Paganini, E.P. A clinical score to predict acute renal failure after cardiac surgery. J. Am. Soc. Nephrol. 2005, 16, 162–168. [Google Scholar] [CrossRef] [Green Version]
  16. Mehta, R.H.; Grab, J.D.; O’Brien, S.M.; Bridges, C.R.; Gammie, J.S.; Haan, C.K.; Ferguson, T.B.; Peterson, E.D.; Society of Thoracic Surgeons National Cardiac Surgery Database Investigators. Bedside tool for predicting the risk of postoperative dialysis in patients undergoing cardiac surgery. Circulation 2006, 114, 2208–2216. [Google Scholar] [CrossRef] [PubMed]
  17. Wijeysundera, D.N.; Karkouti, K.; Dupuis, J.Y.; Rao, V.; Chan, C.T.; Granton, J.T.; Beattie, W.S. Derivation and validation of a simplified predictive index for renal replacement therapy after cardiac surgery. JAMA 2007, 297, 1801–1809. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Englberger, L.; Suri, R.M.; Li, Z.; Dearani, J.A.; Park, S.J.; Sundt, T.M.; Schaff, H.V. Validation of clinical scores predicting severe acute kidney injury after cardiac surgery. Am. J. Kidney Dis. 2010, 56, 623–631. [Google Scholar] [CrossRef]
  19. Brown, J.R.; Kramer, R.S.; Coca, S.G.; Parikh, C.R. Duration of acute kidney injury impacts long-term survival after cardiac surgery. Ann. Thorac. Surg. 2010, 90, 1142–1148. [Google Scholar] [CrossRef] [Green Version]
  20. Parolari, A.; Pesce, L.L.; Pacini, D.; Mazzanti, V.; Salis, S.; Sciacovelli, C.; Rossi, F.; Alamanni, F.; Monzino Research Group on Cardiac Surgery Outcomes. Risk factors for perioperative acute kidney injury after adult cardiac surgery: Role of perioperative management. Ann. Thorac. Surg. 2012, 93, 584–591. [Google Scholar] [CrossRef] [PubMed]
  21. Monnet, X.; Rienzo, M.; Osman, D.; Anguel, N.; Richard, C.; Pinsky, M.R.; Teboul, J.L. Passive leg raising predicts fluid responsiveness in the critically ill. Crit. Care Med. 2006, 34, 1402–1407. [Google Scholar] [CrossRef] [PubMed]
  22. Michard, F. Changes in arterial pressure during mechanical ventilation. Anesthesiology 2005, 103, 419–428. [Google Scholar] [CrossRef]
  23. Monnet, X.; Marik, P.E.; Teboul, J.L. Prediction of fluid responsiveness: An update. Ann. Intensive Care 2016, 6, 111. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  24. Smith, B.B.; Mauermann, W.J.; Yalamuri, S.M.; Frank, R.D.; Gurrieri, C.; Arghami, A.; Smith, M.M. Intraoperative Fluid Balance and Perioperative Outcomes after Aortic Valve Surgery. Ann. Thorac. Surg. 2020, 110, 1286–1293. [Google Scholar] [CrossRef] [PubMed]
  25. Bouchard, J.; Soroko, S.B.; Chertow, G.M.; Himmelfarb, J.; Ikizler, T.A.; Paganini, E.P.; Mehta, R.L.; Program to Improve Care in Acute Renal Disease Study Group. Fluid accumulation, survival and recovery of kidney function in critically ill patients with acute kidney injury. Kidney Int. 2009, 76, 422–427. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  26. Haase-Fielitz, A.; Haase, M.; Bellomo, R.; Calzavacca, P.; Spura, A.; Baraki, H.; Kutschka, I.; Albert, C. Perioperative Hemodynamic Instability and Fluid Overload are Associated with Increasing Acute Kidney Injury Severity and Worse Outcome after Cardiac Surgery. Blood Purif. 2017, 43, 298–308. [Google Scholar] [CrossRef]
  27. Kuo, G.; Chen, S.W.; Lee, C.C.; Chen, J.J.; Fan, P.C.; Wang, S.Y.; Tian, Y.C.; Chang, C.H. Latent Trajectories of Fluid Balance Are Associated with Outcomes in Cardiac and Aortic Surgery. Ann. Thorac. Surg. 2020, 109, 1343–1349. [Google Scholar] [CrossRef]
  28. Engelman, D.T.; Crisafi, C.; Germain, M.; Greco, B.; Nathanson, B.H.; Engelman, R.M.; Schwann, T.A. Using urinary biomarkers to reduce acute kidney injury following cardiac surgery. J. Thorac. Cardiovasc. Surg. 2020, 160, 1235–1246.e2. [Google Scholar] [CrossRef] [PubMed]
  29. Zarbock, A.; Kullmar, M.; Ostermann, M.; Lucchese, G.; Baig, K.; Cennamo, A.; Rajani, R.; McCorkell, S.; Arndt, C.; Wulf, H.; et al. Prevention of Cardiac Surgery-Associated Acute Kidney Injury by Implementing the KDIGO Guidelines in High-Risk Patients Identified by Biomarkers: The PrevAKI-Multicenter Randomized Controlled Trial. Anesth. Analg. 2021, 133, 292–302. [Google Scholar] [CrossRef]
  30. Ronco, C.; Brendolan, A.; Bragantini, L.; Chiaramonte, S.; Fabris, A.; Feriani, M.; Dell Aquila, R.; Milan, M.; Mentasti, P.; La Greca, G. Renal functional reserve in pregnancy. Nephrol. Dial. Transplant 1988, 3, 157–161. [Google Scholar]
  31. Bosch, J.P.; Saccaggi, A.; Lauer, A.; Ronco, C.; Belledonne, M.; Glabman, S. Renal functional reserve in humans. Effect of protein intake on glomerular filtration rate. Am. J. Med. 1983, 75, 943–950. [Google Scholar] [CrossRef]
  32. Husain-Syed, F.; Ferrari, F.; Sharma, A.; Danesi, T.H.; Bezerra, P.; Lopez-Giacoman, S.; Samoni, S.; de Cal, M.; Corradi, V.; Virzi, G.M.; et al. Preoperative Renal Functional Reserve Predicts Risk of Acute Kidney Injury after Cardiac Operation. Ann. Thorac. Surg. 2018, 105, 1094–1101. [Google Scholar] [CrossRef] [Green Version]
  33. Bellomo, R.; Ronco, C.; Kellum, J.A.; Mehta, R.L.; Palevsky, P.; Acute Dialysis Quality Initiative Workgroup. Acute renal failure—Definition, outcome measures, animal models, fluid therapy and information technology needs: The Second International Consensus Conference of the Acute Dialysis Quality Initiative (ADQI) Group. Crit. Care 2004, 8, R204–R212. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Mehta, R.L.; Kellum, J.A.; Shah, S.V.; Molitoris, B.A.; Ronco, C.; Warnock, D.G.; Levin, A.; Acute Kidney Injury Network. Acute Kidney Injury Network: Report of an initiative to improve outcomes in acute kidney injury. Crit. Care 2007, 11, R31. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  35. Luo, X.; Jiang, L.; Du, B.; Wen, Y.; Wang, M.; Xi, X.; Beijing Acute Kidney Injury Trial Workgroup. A comparison of different diagnostic criteria of acute kidney injury in critically ill patients. Crit. Care 2014, 18, R144. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  36. Brezis, M.; Rosen, S. Hypoxia of the renal medulla—Its implications for disease. N. Engl. J. Med. 1995, 332, 647–655. [Google Scholar] [CrossRef]
  37. Yan, T.K.; Li, X.L.; Xue, Y.; Wei, L.; Lin, S. Acute kidney injury induced by allergic conditions-associated renal cholesterol crystal embolism. Nefrologia 2012, 32, 856–857. [Google Scholar]
  38. Lannemyr, L.; Bragadottir, G.; Krumbholz, V.; Redfors, B.; Sellgren, J.; Ricksten, S.E. Effects of Cardiopulmonary Bypass on Renal Perfusion, Filtration, and Oxygenation in Patients Undergoing Cardiac Surgery. Anesthesiology 2017, 126, 205–213. [Google Scholar] [CrossRef]
  39. Salmasi, V.; Maheshwari, K.; Yang, D.; Mascha, E.J.; Singh, A.; Sessler, D.I.; Kurz, A. Relationship between Intraoperative Hypotension, Defined by Either Reduction from Baseline or Absolute Thresholds, and Acute Kidney and Myocardial Injury after Noncardiac Surgery: A Retrospective Cohort Analysis. Anesthesiology 2017, 126, 47–65. [Google Scholar] [CrossRef]
  40. Zhang, W.R.; Garg, A.X.; Coca, S.G.; Devereaux, P.J.; Eikelboom, J.; Kavsak, P.; McArthur, E.; Thiessen-Philbrook, H.; Shortt, C.; Shlipak, M.; et al. Plasma IL-6 and IL-10 Concentrations Predict AKI and Long-Term Mortality in Adults after Cardiac Surgery. J. Am. Soc. Nephrol. 2015, 26, 3123–3132. [Google Scholar] [CrossRef] [Green Version]
  41. Li, Z.; Fan, G.; Zheng, X.; Gong, X.; Chen, T.; Liu, X.; Jia, K. Risk factors and clinical significance of acute kidney injury after on-pump or off-pump coronary artery bypass grafting: A propensity score-matched study. Interact. Cardiovasc. Thorac. Surg. 2019, 28, 893–899. [Google Scholar] [CrossRef] [PubMed]
  42. Fathi, M.; Valaei, M.; Ghanbari, A.; Ghasemi, R.; Yaghubi, M. Comparison of Patient’s Kidney Function Based on Kidney Disease Improving Global Outcomes (KDIGO) Criteria and Clinical Parameters in Isolated Coronary Artery Bypass Graft (CABG) Surgery in On-Pump and Off-pump Methods in Patients with Low Cardiac Output Syndrome (LCOS) after Surgery. Anesth. Pain Med. 2020, 10, e100517. [Google Scholar] [PubMed] [Green Version]
  43. Garg, A.X.; Devereaux, P.J.; Yusuf, S.; Cuerden, M.S.; Parikh, C.R.; Coca, S.G.; Walsh, M.; Novick, R.; Cook, R.J.; Jain, A.R.; et al. Kidney function after off-pump or on-pump coronary artery bypass graft surgery: A randomized clinical trial. JAMA 2014, 311, 2191–2198. [Google Scholar] [CrossRef]
  44. Haase, M.; Bellomo, R.; Haase-Fielitz, A. Novel biomarkers, oxidative stress, and the role of labile iron toxicity in cardiopulmonary bypass-associated acute kidney injury. J. Am. Coll. Cardiol. 2010, 55, 2024–2033. [Google Scholar] [CrossRef] [Green Version]
  45. Billings, F.T.T.; Yu, C.; Byrne, J.G.; Petracek, M.R.; Pretorius, M. Heme Oxygenase-1 and Acute Kidney Injury following Cardiac Surgery. Cardiorenal Med. 2014, 4, 12–21. [Google Scholar] [CrossRef] [Green Version]
  46. Billings, F.T.T.; Ball, S.K.; Roberts, L.J.; Pretorius, M. Postoperative acute kidney injury is associated with hemoglobinemia and an enhanced oxidative stress response. Free Radic. Biol. Med. 2011, 50, 1480–1487. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Meersch, M.; Schmidt, C.; Hoffmeier, A.; Van Aken, H.; Wempe, C.; Gerss, J.; Zarbock, A. Prevention of cardiac surgery-associated AKI by implementing the KDIGO guidelines in high risk patients identified by biomarkers: The PrevAKI randomized controlled trial. Intensive Care Med. 2017, 43, 1551–1561. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  48. Landoni, G.; Bove, T.; Szekely, A.; Comis, M.; Rodseth, R.N.; Pasero, D.; Ponschab, M.; Mucchetti, M.; Bove, T.; Azzolini, M.L.; et al. Reducing mortality in acute kidney injury patients: Systematic review and international web-based survey. J. Cardiothorac. Vasc. Anesth. 2013, 27, 1384–1398. [Google Scholar] [CrossRef]
  49. Osawa, E.A.; Rhodes, A.; Landoni, G.; Galas, F.R.; Fukushima, J.T.; Park, C.H.; Almeida, J.P.; Nakamura, R.E.; Strabelli, T.M.; Pileggi, B.; et al. Effect of Perioperative Goal-Directed Hemodynamic Resuscitation Therapy on Outcomes Following Cardiac Surgery: A Randomized Clinical Trial and Systematic Review. Crit. Care Med. 2016, 44, 724–733. [Google Scholar] [CrossRef] [PubMed]
  50. Sun, H.; Xie, Q.; Peng, Z. Does Fenoldopam Protect Kidney in Cardiac Surgery? A Systemic Review and Meta-Analysis with Trial Sequential Analysis. Shock 2019, 52, 326–333. [Google Scholar] [CrossRef]
  51. Mehta, R.H.; Leimberger, J.D.; van Diepen, S.; Meza, J.; Wang, A.; Jankowich, R.; Harrison, R.W.; Hay, D.; Fremes, S.; Duncan, A.; et al. Levosimendan in Patients with Left Ventricular Dysfunction Undergoing Cardiac Surgery. N. Engl. J. Med. 2017, 376, 2032–2042. [Google Scholar] [CrossRef]
  52. Landoni, G.; Lomivorotov, V.V.; Alvaro, G.; Lobreglio, R.; Pisano, A.; Guarracino, F.; Calabro, M.G.; Grigoryev, E.V.; Likhvantsev, V.V.; Salgado-Filho, M.F.; et al. Levosimendan for Hemodynamic Support after Cardiac Surgery. N. Engl. J. Med. 2017, 376, 2021–2031. [Google Scholar] [CrossRef] [PubMed]
  53. Kellum, J.A.; Decker, J.M. Use of dopamine in acute renal failure: A meta-analysis. Crit. Care Med. 2001, 29, 1526–1531. [Google Scholar] [CrossRef] [PubMed]
  54. Lassnigg, A.; Donner, E.; Grubhofer, G.; Presterl, E.; Druml, W.; Hiesmayr, M. Lack of renoprotective effects of dopamine and furosemide during cardiac surgery. J. Am. Soc. Nephrol. 2000, 11, 97–104. [Google Scholar] [CrossRef] [PubMed]
  55. Barba-Navarro, R.; Tapia-Silva, M.; Garza-Garcia, C.; Lopez-Giacoman, S.; Melgoza-Toral, I.; Vazquez-Rangel, A.; Bazua-Valenti, S.; Bobadilla, N.; Wasung de Lay, M.; Baranda, F.; et al. The Effect of Spironolactone on Acute Kidney Injury after Cardiac Surgery: A Randomized, Placebo-Controlled Trial. Am. J. Kidney Dis. 2017, 69, 192–199. [Google Scholar] [CrossRef]
  56. Himmelfarb, J.; Chertow, G.M.; McCullough, P.A.; Mesana, T.; Shaw, A.D.; Sundt, T.M.; Brown, C.; Cortville, D.; Dagenais, F.; de Varennes, B.; et al. Perioperative THR-184 and AKI after Cardiac Surgery. J. Am. Soc. Nephrol. 2018, 29, 670–679. [Google Scholar] [CrossRef] [PubMed]
  57. Swaminathan, M.; Stafford-Smith, M.; Chertow, G.M.; Warnock, D.G.; Paragamian, V.; Brenner, R.M.; Lellouche, F.; Fox-Robichaud, A.; Atta, M.G.; Melby, S.; et al. Allogeneic Mesenchymal Stem Cells for Treatment of AKI after Cardiac Surgery. J. Am. Soc. Nephrol. 2018, 29, 260–267. [Google Scholar] [CrossRef] [Green Version]
  58. Thielmann, M.; Corteville, D.; Szabo, G.; Swaminathan, M.; Lamy, A.; Lehner, L.J.; Brown, C.D.; Noiseux, N.; Atta, M.G.; Squiers, E.C.; et al. Teprasiran, a Small Interfering RNA, for the Prevention of Acute Kidney Injury in High-Risk Patients Undergoing Cardiac Surgery: A Randomized Clinical Study. Circulation 2021, 144, 1133–1144. [Google Scholar] [CrossRef]
  59. Kim, J.H.; Kim, H.J.; Kim, J.Y.; Ahn, H.; Ahn, I.M.; Choe, W.J.; Lim, C.H. Meta-Analysis of Sodium Bicarbonate Therapy for Prevention of Cardiac Surgery-Associated Acute Kidney Injury. J. Cardiothorac. Vasc. Anesth. 2015, 29, 1248–1256. [Google Scholar] [CrossRef] [PubMed]
  60. Liu, Y.; Sheng, B.; Wang, S.; Lu, F.; Zhen, J.; Chen, W. Dexmedetomidine prevents acute kidney injury after adult cardiac surgery: A meta-analysis of randomized controlled trials. BMC Anesthesiol. 2018, 18, 7. [Google Scholar] [CrossRef] [Green Version]
  61. Mei, M.; Zhao, H.W.; Pan, Q.G.; Pu, Y.M.; Tang, M.Z.; Shen, B.B. Efficacy of N-Acetylcysteine in Preventing Acute Kidney Injury after Cardiac Surgery: A Meta-Analysis Study. J. Investig. Surg. 2018, 31, 14–23. [Google Scholar] [CrossRef]
  62. Billings, F.T.T.; Hendricks, P.A.; Schildcrout, J.S.; Shi, Y.; Petracek, M.R.; Byrne, J.G.; Brown, N.J. High-Dose Perioperative Atorvastatin and Acute Kidney Injury Following Cardiac Surgery: A Randomized Clinical Trial. JAMA 2016, 315, 877–888. [Google Scholar] [CrossRef] [PubMed]
  63. Penny-Dimri, J.C.; Cochrane, A.D.; Perry, L.A.; Smith, J.A. Characterising the Role of Perioperative Erythropoietin for Preventing Acute Kidney Injury after Cardiac Surgery: Systematic Review and Meta-Analysis. Heart Lung Circ. 2016, 25, 1067–1076. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  64. Mahesh, B.; Yim, B.; Robson, D.; Pillai, R.; Ratnatunga, C.; Pigott, D. Does furosemide prevent renal dysfunction in high-risk cardiac surgical patients? Results of a double-blinded prospective randomised trial. Eur. J. Cardiothorac. Surg. 2008, 33, 370–376. [Google Scholar] [CrossRef]
  65. Garg, A.X.; Chan, M.T.V.; Cuerden, M.S.; Devereaux, P.J.; Abbasi, S.H.; Hildebrand, A.; Lamontagne, F.; Lamy, A.; Noiseux, N.; Parikh, C.R.; et al. Effect of methylprednisolone on acute kidney injury in patients undergoing cardiac surgery with a cardiopulmonary bypass pump: A randomized controlled trial. CMAJ 2019, 191, E247–E256. [Google Scholar] [CrossRef] [Green Version]
  66. Van Driest, S.L.; Jooste, E.H.; Shi, Y.; Choi, L.; Darghosian, L.; Hill, K.D.; Smith, A.H.; Kannankeril, P.J.; Roden, D.M.; Ware, L.B. Association Between Early Postoperative Acetaminophen Exposure and Acute Kidney Injury in Pediatric Patients Undergoing Cardiac Surgery. JAMA Pediatr. 2018, 172, 655–663. [Google Scholar] [CrossRef] [Green Version]
  67. Hausenloy, D.J.; Candilio, L.; Evans, R.; Ariti, C.; Jenkins, D.P.; Kolvekar, S.; Knight, R.; Kunst, G.; Laing, C.; Nicholas, J.; et al. Remote Ischemic Preconditioning and Outcomes of Cardiac Surgery. N. Engl. J. Med. 2015, 373, 1408–1417. [Google Scholar] [CrossRef] [PubMed]
  68. Meybohm, P.; Bein, B.; Brosteanu, O.; Cremer, J.; Gruenewald, M.; Stoppe, C.; Coburn, M.; Schaelte, G.; Boning, A.; Niemann, B.; et al. A Multicenter Trial of Remote Ischemic Preconditioning for Heart Surgery. N. Engl. J. Med. 2015, 373, 1397–1407. [Google Scholar] [CrossRef]
  69. Shroyer, A.L.; Hattler, B.; Wagner, T.H.; Collins, J.F.; Baltz, J.H.; Quin, J.A.; Almassi, G.H.; Kozora, E.; Bakaeen, F.; Cleveland, J.C., Jr.; et al. Five-Year Outcomes after On-Pump and Off-Pump Coronary-Artery Bypass. N. Engl. J. Med. 2017, 377, 623–632. [Google Scholar] [CrossRef]
  70. Shah, K.; Chaker, Z.; Busu, T.; Shah, R.; Osman, M.; Alqahtani, F.; Alkhouli, M. Meta-Analysis Comparing Renal Outcomes after Transcatheter versus Surgical Aortic Valve Replacement. J. Interv. Cardiol. 2019, 2019, 3537256. [Google Scholar] [CrossRef] [Green Version]
  71. Siddiqui, W.J.; Alvarez, C.; Aslam, M.; Bakar, A.; Khan, M.H.; Aslam, A.; Hanif, M.O.; Hasni, S.F.; Ranganna, K.; Eisen, H.; et al. Meta-Analysis Comparing Outcomes and Need for Renal Replacement Therapy of Transcatheter Aortic Valve Implantation Versus Surgical Aortic Valve Replacement. Am. J. Cardiol. 2018, 122, 468–476. [Google Scholar] [CrossRef]
  72. Murry, C.E.; Jennings, R.B.; Reimer, K.A. Preconditioning with ischemia: A delay of lethal cell injury in ischemic myocardium. Circulation 1986, 74, 1124–1136. [Google Scholar] [CrossRef] [Green Version]
  73. Przyklenk, K.; Bauer, B.; Ovize, M.; Kloner, R.A.; Whittaker, P. Regional ischemic ‘preconditioning’ protects remote virgin myocardium from subsequent sustained coronary occlusion. Circulation 1993, 87, 893–899. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Jensen, H.A.; Loukogeorgakis, S.; Yannopoulos, F.; Rimpilainen, E.; Petzold, A.; Tuominen, H.; Lepola, P.; Macallister, R.J.; Deanfield, J.E.; Makela, T.; et al. Remote ischemic preconditioning protects the brain against injury after hypothermic circulatory arrest. Circulation 2011, 123, 714–721. [Google Scholar] [CrossRef] [Green Version]
  75. Tapuria, N.; Kumar, Y.; Habib, M.M.; Abu Amara, M.; Seifalian, A.M.; Davidson, B.R. Remote ischemic preconditioning: A novel protective method from ischemia reperfusion injury—A review. J. Surg. Res. 2008, 150, 304–330. [Google Scholar] [CrossRef] [PubMed]
  76. Er, F.; Nia, A.M.; Dopp, H.; Hellmich, M.; Dahlem, K.M.; Caglayan, E.; Kubacki, T.; Benzing, T.; Erdmann, E.; Burst, V.; et al. Ischemic preconditioning for prevention of contrast medium-induced nephropathy: Randomized pilot RenPro Trial (Renal Protection Trial). Circulation 2012, 126, 296–303. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  77. Zarbock, A.; Schmidt, C.; Van Aken, H.; Wempe, C.; Martens, S.; Zahn, P.K.; Wolf, B.; Goebel, U.; Schwer, C.I.; Rosenberger, P.; et al. Effect of remote ischemic preconditioning on kidney injury among high-risk patients undergoing cardiac surgery: A randomized clinical trial. JAMA 2015, 313, 2133–2141. [Google Scholar] [CrossRef] [PubMed]
  78. Zhou, H.; Yang, L.; Wang, G.; Zhang, C.; Fang, Z.; Lei, G.; Shi, S.; Li, J. Remote Ischemic Preconditioning Prevents Postoperative Acute Kidney Injury after Open Total Aortic Arch Replacement: A Double-Blind, Randomized, Sham-Controlled Trial. Anesth. Analg. 2019, 129, 287–293. [Google Scholar] [CrossRef] [PubMed]
  79. Zarbock, A.; Kellum, J.A.; Gourine, A.V.; Ackland, G.L. Salvaging remote ischaemic preconditioning as a therapy for perioperative acute kidney injury. Br. J. Anaesth. 2020, 124, 8–12. [Google Scholar] [CrossRef]
  80. Pierce, B.; Bole, I.; Patel, V.; Brown, D.L. Clinical Outcomes of Remote Ischemic Preconditioning Prior to Cardiac Surgery: A Meta-Analysis of Randomized Controlled Trials. J. Am. Heart Assoc. 2017, 6, e004666. [Google Scholar] [CrossRef] [Green Version]
  81. Bianchi, F.; Sala, E.; Donadei, C.; Capelli, I.; La Manna, G. Potential advantages of acute kidney injury management by mesenchymal stem cells. World J. Stem Cells 2014, 6, 644–650. [Google Scholar] [CrossRef] [PubMed]
  82. Herrera Sanchez, M.B.; Bruno, S.; Grange, C.; Tapparo, M.; Cantaluppi, V.; Tetta, C.; Camussi, G. Human liver stem cells and derived extracellular vesicles improve recovery in a murine model of acute kidney injury. Stem Cell Res. Ther. 2014, 5, 124. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  83. Toyohara, T.; Mae, S.; Sueta, S.; Inoue, T.; Yamagishi, Y.; Kawamoto, T.; Kasahara, T.; Hoshina, A.; Toyoda, T.; Tanaka, H.; et al. Cell Therapy Using Human Induced Pluripotent Stem Cell-Derived Renal Progenitors Ameliorates Acute Kidney Injury in Mice. Stem Cells Transl. Med. 2015, 4, 980–992. [Google Scholar] [CrossRef] [PubMed]
  84. Pickkers, P.; Heemskerk, S.; Schouten, J.; Laterre, P.F.; Vincent, J.L.; Beishuizen, A.; Jorens, P.G.; Spapen, H.; Bulitta, M.; Peters, W.H.; et al. Alkaline phosphatase for treatment of sepsis-induced acute kidney injury: A prospective randomized double-blind placebo-controlled trial. Crit. Care 2012, 16, R14. [Google Scholar] [CrossRef] [Green Version]
  85. Hollmann, C.; Fernandes, N.L.; Biccard, B.M. A Systematic Review of Outcomes Associated with Withholding or Continuing Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers before Noncardiac Surgery. Anesth. Analg. 2018, 127, 678–687. [Google Scholar] [CrossRef] [PubMed]
  86. Aspelin, P.; Aubry, P.; Fransson, S.G.; Strasser, R.; Willenbrock, R.; Berg, K.J. Nephrotoxic effects in high-risk patients undergoing angiography. N. Engl. J. Med. 2003, 348, 491–499. [Google Scholar] [CrossRef]
  87. Rudnick, M.R.; Leonberg-Yoo, A.K.; Litt, H.I.; Cohen, R.M.; Hilton, S.; Reese, P.P. The Controversy of Contrast-Induced Nephropathy with Intravenous Contrast: What Is the Risk? Am. J. Kidney Dis. 2020, 75, 105–113. [Google Scholar] [CrossRef] [Green Version]
  88. Karkouti, K.; Grocott, H.P.; Hall, R.; Jessen, M.E.; Kruger, C.; Lerner, A.B.; MacAdams, C.; Mazer, C.D.; de Medicis, E.; Myles, P.; et al. Interrelationship of preoperative anemia, intraoperative anemia, and red blood cell transfusion as potentially modifiable risk factors for acute kidney injury in cardiac surgery: A historical multicentre cohort study. Can. J. Anaesth. 2015, 62, 377–384. [Google Scholar] [CrossRef]
  89. Haase, M.; Bellomo, R.; Story, D.; Letis, A.; Klemz, K.; Matalanis, G.; Seevanayagam, S.; Dragun, D.; Seeliger, E.; Mertens, P.R.; et al. Effect of mean arterial pressure, haemoglobin and blood transfusion during cardiopulmonary bypass on postoperative acute kidney injury. Nephrol. Dial. Transplant 2012, 27, 153–160. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  90. Kindzelski, B.A.; Corcoran, P.; Siegenthaler, M.P.; Horvath, K.A. Postoperative acute kidney injury following intraoperative blood product transfusions during cardiac surgery. Perfusion 2018, 33, 62–70. [Google Scholar] [CrossRef]
  91. Brochard, L.; Abroug, F.; Brenner, M.; Broccard, A.F.; Danner, R.L.; Ferrer, M.; Laghi, F.; Magder, S.; Papazian, L.; Pelosi, P.; et al. An Official ATS/ERS/ESICM/SCCM/SRLF Statement: Prevention and Management of Acute Renal Failure in the ICU Patient: An international consensus conference in intensive care medicine. Am. J. Respir. Crit. Care Med. 2010, 181, 1128–1155. [Google Scholar] [CrossRef] [PubMed]
  92. Austin, D.; McCanny, P.; Aneman, A. Postoperative renal failure management in mechanical circulatory support patients. Ann. Transl. Med. 2020, 8, 833. [Google Scholar] [CrossRef] [PubMed]
  93. Zarbock, A.; Kellum, J.A.; Schmidt, C.; Van Aken, H.; Wempe, C.; Pavenstadt, H.; Boanta, A.; Gerss, J.; Meersch, M. Effect of Early vs. Delayed Initiation of Renal Replacement Therapy on Mortality in Critically Ill Patients with Acute Kidney Injury: The ELAIN Randomized Clinical Trial. JAMA 2016, 315, 2190–2199. [Google Scholar] [CrossRef] [Green Version]
  94. Liu, Y.; Davari-Farid, S.; Arora, P.; Porhomayon, J.; Nader, N.D. Early versus late initiation of renal replacement therapy in critically ill patients with acute kidney injury after cardiac surgery: A systematic review and meta-analysis. J. Cardiothorac. Vasc. Anesth. 2014, 28, 557–563. [Google Scholar] [CrossRef] [PubMed]
  95. Leite, T.T.; Macedo, E.; Pereira, S.M.; Bandeira, S.R.; Pontes, P.H.; Garcia, A.S.; Militao, F.R.; Sobrinho, I.M.; Assuncao, L.M.; Liborio, A.B. Timing of renal replacement therapy initiation by AKIN classification system. Crit. Care 2013, 17, R62. [Google Scholar] [CrossRef] [Green Version]
  96. STARRT-AKI Investigators; Canadian Critical Care Trials Group; Australian and New Zealand Intensive Care Society Clinical Trials Group; United Kingdom Critical Care Research Group; Canadian Nephrology Trials Network; Irish Critical Care Trials Group; Bagshaw, S.M.; Wald, R.; Adhikari, N.K.J.; Bellomo, R.; et al. Timing of Initiation of Renal-Replacement Therapy in Acute Kidney Injury. N. Engl. J. Med. 2020, 383, 240–251. [Google Scholar]
  97. Hobson, C.; Ozrazgat-Baslanti, T.; Kuxhausen, A.; Thottakkara, P.; Efron, P.A.; Moore, F.A.; Moldawer, L.L.; Segal, M.S.; Bihorac, A. Cost and Mortality Associated with Postoperative Acute Kidney Injury. Ann. Surg. 2015, 261, 1207–1214. [Google Scholar] [CrossRef] [PubMed]
  98. Hansen, M.K.; Gammelager, H.; Jacobsen, C.J.; Hjortdal, V.E.; Layton, J.B.; Rasmussen, B.S.; Andreasen, J.J.; Johnsen, S.P.; Christiansen, C.F. Acute Kidney Injury and Long-term Risk of Cardiovascular Events after Cardiac Surgery: A Population-Based Cohort Study. J. Cardiothorac. Vasc. Anesth. 2015, 29, 617–625. [Google Scholar] [CrossRef]
  99. Xu, J.R.; Zhu, J.M.; Jiang, J.; Ding, X.Q.; Fang, Y.; Shen, B.; Liu, Z.H.; Zou, J.Z.; Liu, L.; Wang, C.S.; et al. Risk Factors for Long-Term Mortality and Progressive Chronic Kidney Disease Associated with Acute Kidney Injury after Cardiac Surgery. Medicine 2015, 94, e2025. [Google Scholar] [CrossRef] [PubMed]
  100. Coca, S.G.; Singanamala, S.; Parikh, C.R. Chronic kidney disease after acute kidney injury: A systematic review and meta-analysis. Kidney Int. 2012, 81, 442–448. [Google Scholar] [CrossRef] [Green Version]
  101. Ryden, L.; Sartipy, U.; Evans, M.; Holzmann, M.J. Acute kidney injury after coronary artery bypass grafting and long-term risk of end-stage renal disease. Circulation 2014, 130, 2005–2011. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  102. Menez, S.; Moledina, D.G.; Garg, A.X.; Thiessen-Philbrook, H.; McArthur, E.; Jia, Y.; Liu, C.; Obeid, W.; Mansour, S.G.; Koyner, J.L.; et al. Results from the TRIBE-AKI Study found associations between postoperative blood biomarkers and risk of chronic kidney disease after cardiac surgery. Kidney Int. 2021, 99, 716–724. [Google Scholar] [CrossRef] [PubMed]
  103. Menez, S.; Ju, W.; Menon, R.; Moledina, D.G.; Thiessen Philbrook, H.; McArthur, E.; Jia, Y.; Obeid, W.; Mansour, S.G.; Koyner, J.L.; et al. Urinary EGF and MCP-1 and risk of CKD after cardiac surgery. JCI Insight 2021, 6. [Google Scholar] [CrossRef]
  104. Lassnigg, A.; Schmidlin, D.; Mouhieddine, M.; Bachmann, L.M.; Druml, W.; Bauer, P.; Hiesmayr, M. Minimal changes of serum creatinine predict prognosis in patients after cardiothoracic surgery: A prospective cohort study. J. Am. Soc. Nephrol. 2004, 15, 1597–1605. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  105. Gutmann, A.; Kaier, K.; Sorg, S.; von Zur Muhlen, C.; Siepe, M.; Moser, M.; Geibel, A.; Zirlik, A.; Ahrens, I.; Baumbach, H.; et al. Analysis of the additional costs of clinical complications in patients undergoing transcatheter aortic valve replacement in the German Health Care System. Int. J. Cardiol. 2015, 179, 231–237. [Google Scholar] [CrossRef]
  106. Chertow, G.M.; Burdick, E.; Honour, M.; Bonventre, J.V.; Bates, D.W. Acute kidney injury, mortality, length of stay, and costs in hospitalized patients. J. Am. Soc. Nephrol. 2005, 16, 3365–3370. [Google Scholar] [CrossRef] [Green Version]
Figure 1. Pathophysiology of AKI (reproduced from ADQI by Nadim et al., 2018 [5]). From https://pittccmblob.blob.core.windows.net/adqi/20fig.pdf (accessed on 6 December 2021).
Figure 1. Pathophysiology of AKI (reproduced from ADQI by Nadim et al., 2018 [5]). From https://pittccmblob.blob.core.windows.net/adqi/20fig.pdf (accessed on 6 December 2021).
Jcm 10 05746 g001
Table 1. KDIGO staging of AKI [1].
Table 1. KDIGO staging of AKI [1].
StageCreatinineUrine Output
11.5–1.9 times baseline, OR
≥0.3 mg/dL
<0.5 mL/kg/h × 6–12 h
22–2.9 times baseline<0.5 mL/kg/h for >12 h
3>3 times baseline, OR
>4 mg/dL, OR
Initiation of RRT
<0.3 mL/kg/h for >24 h, OR
Anuria > 12 h
Table 2. Risk factors for CSA-AKI [3].
Table 2. Risk factors for CSA-AKI [3].
PatientOperativePhysiologic
AgeSurgical ComplexityHypotension
Female GenderCPB DurationInotrope exposure
HTNInability to separate from CPBHypovolemia
CKDLow Hct during CPBVenous congestion
Liver dzAortic cross-clamp timeBlood transfusion
PVD/CVA Cardiogenic shock
Diabetes Diuretic usage
Anemia
Smoking
Table 3. Scoring systems for AKI (adapted from [18]).
Table 3. Scoring systems for AKI (adapted from [18]).
Cleveland ScoreMehta ScoreSRI Score
DefinitionPointsDefinitionPointsDefinitionPoints
Variable:
Age--VariesVaries--
Race--Nonwhite2--
SexFemale1----
Preop Renal functionSCr 1.2–2.1 mg/dL
SCr > 2.1 mg/dL
2
5
ScrVariesGFR 31–60 mL/min
GFR ≤ 30 mL/min
1
2
CHFYes1----
NYHA Class--IV3--
DiabetesInsulin-requiring1Oral control
Insulin-requiring
2
5
Any medication1
COPDYes1Yes3--
MI ≤ 21 d ago--Yes3--
LVEF<35%1--≤40%1
Previous SurgeryYes1Yes3Yes1
Preop IABPYes2--Yes1
Cardiogenic Shock--Yes7--
Surgical TimingEmergency2--Nonelective1
Surgical TypeCABG only
Valve only
CABG + valve, other
0
1
2
CABG
AV only
AV + CABG
MV only
MV + CABG
0
2
5
4
7
Other than CABG or ASD only1
Score Range 0–17 0–83
SRI = simplified renal index, SCr = serum creatinine, GFR = glomerular filtration rate, CHF = congestive heart failure, NYHA = New York Heart Association, COPD = chronic obstructive pulmonary disease, MI = myocardial infarction, LVEF = left ventricle ejection fraction, IABP = intra-aortic balloon pump, CABG = coronary artery bypass grafting, AV = aortic valve, MV = mitral valve, ASD = atrial septal defect.
Table 4. Single-agent therapies for treatment of AKI.
Table 4. Single-agent therapies for treatment of AKI.
TherapyOverviewSourceOutcome
PharmacologicFenoldopamMaybe less AKI but no change in overall outcomesMeta-analysis * [50], N = 1107 pts in 7 RCTsAKI (8.5% vs. 20.3%, RR 0.42 CI 0.26–0.69, p = 0.0006) but more hypotension (25.8% vs. 14.7%, RR 1.76 CI 1.29–2.39, p = 0.0003); no changes in mortality or RRT.
LevosimendanNo impactRCT, N = 849 [51]; RCT, N = 508 [52]No difference in mortality or renal outcomes in either prophylactic administration or to treat low LVEF postop
DopamineNo impactICU Meta-analysis, N = 1019 in 24 studies (17 RCTs) [53]; RCT, N = 126 [54]No impact on improvement of AKI in ICU patients; no change in incidence of AKI in cardiac surgical patients
SpironolactoneNo impactRCT, N = 233 [55]No difference in KDIGO AKI, trend toward harm (43% AKI in spironolactone group vs. 29% in placebo, p = 0.02)
Bone morphogenetic protein-7 agonist (THR-184)No differenceRCT, N = 452 [56]KDIGO CTS-AKI rates similar in pts with recognized risk factors for AKI (range 74%–79% for various doses of THR-184 vs. 78% in placebo, p = 0.43)
Mesenchymal stem cells (MSC)No differenceRCT, N = 156 [57]Pts with CSA-AKI got MSC v placebo with no difference in time to their Cr returning to preoperative baseline; median time to recovery was 15 d with MSC v 12 d with placebo (HR 0.81, CI 0.53–1.24, p = 0.32)
Teprasiran (small interfering RNA)Less AKIRCT, N = 360 [58]Pts at moderate to high risk of AKI by risk factors; all level AKI with teprasiran 36.9% vs. 49.7% in placebo (OR 0.58, 95% CI 0.37–0.92, p = 0.02)
Sodium bicarbonateNo differenceMeta-analysis, N = 1092 in 5 RCTs [59]Perioperative administration of sodium bicarbonate led to CSA-AKI rates of 42.6% vs. 41.3% in control (RR 0.95, 95% CI 0.74–1.22)
DexmedetomidineMay have AKI benefit, no mortality changeMeta-analysis, N = 1575 in 10 RCTs [60]Perioperative administration of dexmedetomidine resulted in lower CSA-AKI rates (8.7% vs. 12.3%, OR 0.65, CI 0.45–0.92, p = 0.02) but similar mortality (0.8% vs. 2.3%, OR 0.43, 95% CI 0.14–1.28)
N-acetylcysteine (NAC)No benefitMeta-analysis, N = 1391 in 10 studies [61]Perioperative administration of NAC resulted in similar CSA-AKI rates (RR 0.841, 95% CI 0.691–1.023, p = 0.083)
StatinsNo benefitRCT, N = 615 [62]No change in CSA-AKI patients either naïve to or on preoperative statins; trial stopped early for futility; 20.8% AKI in statin group, 19.5% in placebo group (RR 1.06, CI 0.78–1.46, p = 0.75)
ErythropoeitinMay benefit low-risk populations but overall no benefitMeta-analysis, N = 473 in 6 RCTs [63]Suggestion in sub-group analysis of reduced AKI when given prior to induction of anesthesia (OR 0.27, CI 0.13–0.54, p = 0.0002) and in low risk populations (OR 0.25, CI 0.11–0.56, p = 0.0008) but overall no difference (OR 0.69, CI 0.35–1.36, p = 0.28).
FurosemideNo benefitRCT, N = 126 [54]; RCT, N = 42 [64]In Lassnigg, furosemide led to increase in Cr of 0.3 vs. 0.1 in the placebo group (p < 0.001). In Mahesh in high-risk patients it increased UOP (3.4 mL/kg/h vs. 1.2 mL/kg/h, p < 0.001) without changing AKI rates (43% vs. 43%, RR 1.1, 95% CI 0.6–2.2)
SteroidsNo benefitRCT, N = 7286 [65]High-risk patients undergoing CPB at given methylprednisolone (250 mg IV ×2) vs. placebo had CSA-AKI rates of 40.6% in steroids vs. 39.2% in placebo (ARR 1.04, 95% CI 0.96–1.11)
AcetaminophenMay benefitRetrospective cohort in pediatric cardiac surgery, N = 666 [66]Postoperative acetaminophen exposure had a dose-dependent protective effect on CSA-AKI (OR for AKI 0.86 (95% CI 0.82–0.90) for each additional 10 mg/kg of acetaminophen
TechnicalRemote ischemic PreconditioningNo benefitRCT, N = 1612 [67]; RCT, N = 1385 [68]See text
Cardiopulmonary bypass avoidance (off-pump CABG)No overall benefitRCT, N = 2392 [43]; RCT, N = 2203 [69]Garg demonstrated lower incidence of CSA-AKI in off-pump vs. on-pump CABG (17.5% vs. 20.8% for RR 0.83, 95% CI 0.72–0.97) but no difference in kidney function at 1 year (17.1% vs. 15.3%, RR 1.10 95% CI 0.95–1.29). Shroyer’s 5-year follow-up demonstrated decreased survival with off-pump CABG technique with a rate of death in the off-pump group of 15.2% vs. 11.9% in the on-pump group (RR 1.28, 95% CI 1.03–1.58).
Percutaneous valve replacementMay benefitMeta-analysis, N = 19,954 in 20 propensity-matched studies and 6 RCTs [70]; meta-analysis, N = 5536 in 6 RCTs [71]Shah found lower AKI at 30 days after TAVR than SAVR (7.1% vs. 12.1%, OR 0.52, 95% CI 0.39–0.68) but similar incidence of RRT (2.8% vs. 4.1%, OR 0.78, 95% CI 0.49–1.25). Siddiqui included renal outcomes at 1 year and found no difference (OR 0.65, 95% CI 0.32–1.32).
* Unless otherwise marked, studies are in a cardiac surgical patient population. AKI = acute kidney injury, RCT = randomized controlled trial, RR = relative risk, CI = confidence interval, RRT = renal replacement therapy, LVEF = left ventricle ejection fraction, ICU = intensive care unit, KDIGO = kidney disease improving global outcomes, CSA-AKI = cardiac surgery associated-acute kidney injury, Cr = creatinine, HR = hazard ratio, OR = odds ratio, UOP = urine output, CPB = cardiopulmonary bypass, ARR = adjusted relative risk, CABG = coronary artery bypass grafting.
Table 5. Bundled care trials.
Table 5. Bundled care trials.
DesignOutcomePatientsInterventionResults
PrevAKI 1 [49]Single center prospective RCTPrimary: all KDIGO stage AKI within 72 h postop276 patients (138 control and 138 intervention) undergoing on-pump cardiac surgery at high risk of AKI by Nephrocheck® 4 h post-CPBBundled care including discontinuing ACEi/ARBs, avoiding nephrotoxins, and an algorithmic approach to hemodynamic management (see text) resulting in more dobutamine, less hyperglycemia, and fewer ACEi/ARBs in intervention groupLower rate of all-stage AKI (71.7% in control vs. 55.1% in intervention, p = 0.004, OR 0.483, 95% CI 0.293–0.796)
PrevAKI 2 [29]Multicenter prospective RCTPrimary: adherence to bundled care278 patients (142 control and 136 intervention) undergoing on-pump cardiac surgery at high risk of AKI by Nephrocheck® 4 h post-CPBBundled care including discontinuing ACEi/ARBs, avoiding nephrotoxins, and an algorithmic approach to hemodynamic management resulting in more dobutamine and more crystalloid in intervention groupIncreased adherence to bundle (4.2% in control vs. 65.4% in intervention, p < 0.001, OR 42.92, 95% CI 17.61–104.60); secondary outcomes without difference in all-stage AKI (41.5% in control vs. 46.3%) but less stage 2 and 3 AKI (23.9% in control vs. 14.0%, OR 0.52, 95% CI 0.28–0.96)
Engelman [28]QI initiative with pre- and post-implementation comparisonPrimary: incidence of KDIGO stage 2 and 3 AKI435 patients undergoing cardiac surgery before Nephrocheck® use vs. 412 patients afterActivation of kidney response team in at-risk patients (based on Nephrocheck®) which advised targeted hemodynamic management, liberalized transfusion, and avoidance of nephrotoxins; no specific algorithms or in-group treatment differences reportedLower stage 2 and 3 AKI after implementation (2.3% pre vs. 0.24% post, p = 0.01)
QI = quality improvement.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Schurle, A.; Koyner, J.L. CSA-AKI: Incidence, Epidemiology, Clinical Outcomes, and Economic Impact. J. Clin. Med. 2021, 10, 5746. https://doi.org/10.3390/jcm10245746

AMA Style

Schurle A, Koyner JL. CSA-AKI: Incidence, Epidemiology, Clinical Outcomes, and Economic Impact. Journal of Clinical Medicine. 2021; 10(24):5746. https://doi.org/10.3390/jcm10245746

Chicago/Turabian Style

Schurle, Alan, and Jay L. Koyner. 2021. "CSA-AKI: Incidence, Epidemiology, Clinical Outcomes, and Economic Impact" Journal of Clinical Medicine 10, no. 24: 5746. https://doi.org/10.3390/jcm10245746

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop