Next Article in Journal
Gestational Alcohol Exposure Altered DNA Methylation Status in the Developing Fetus
Next Article in Special Issue
The Novel HDAC8 Inhibitor WK2-16 Attenuates Lipopolysaccharide-Activated Matrix Metalloproteinase-9 Expression in Human Monocytic Cells and Improves Hypercytokinemia In Vivo
Previous Article in Journal
Phytochemicals Targeting Estrogen Receptors: Beneficial Rather Than Adverse Effects?
Previous Article in Special Issue
Hypoxia Inducible Factor-2 Alpha and Prolinhydroxylase 2 Polymorphisms in Patients with Acute Respiratory Distress Syndrome (ARDS)
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Issues of Acute Kidney Injury Staging and Management in Sepsis and Critical Illness: A Narrative Review

1
Department of Nephrology, Heidelberg University Hospital, 162, Im Neuenheimer Feld, D-69120 Heidelberg, Germany
2
Department of Anesthesiology, Heidelberg University Hospital, 110, Im Neuenheimer Feld, D-69120 Heidelberg, Germany
*
Author to whom correspondence should be addressed.
Int. J. Mol. Sci. 2017, 18(7), 1387; https://doi.org/10.3390/ijms18071387
Submission received: 7 June 2017 / Revised: 24 June 2017 / Accepted: 24 June 2017 / Published: 28 June 2017
(This article belongs to the Special Issue Sepsis)

Abstract

:
Acute kidney injury (AKI) has a high incidence on intensive care units around the world and is a major complication in critically ill patients suffering from sepsis or septic shock. The short- and long-term complications are thereby devastating and impair the quality of life. Especially in terms of AKI staging, the determination of kidney function and the timing of dialytic AKI management outside of life-threatening indications are ongoing matters of debate. Despite several studies, a major problem remains in distinguishing between beneficial and unnecessary “early” or even harmful renal replacement therapy (RRT). The latter might prolong disease course and renal recovery. AKI scores, however, provide an insufficient outcome-predicting ability and the related estimation of kidney function via serum creatinine or blood urea nitrogen (BUN)/urea is not reliable in AKI and critical illness. Kidney independent alterations of creatinine- and BUN/urea-levels further complicate the situation. This review critically assesses the current AKI staging, issues and pitfalls of the determination of kidney function and RRT timing, as well as the potential harm reflected by unnecessary RRT. A better understanding is mandatory to improve future study designs and avoid unnecessary RRT for higher patient safety and lower health care costs.

Graphical Abstract

1. Introduction

Acute kidney injury (AKI) is a disease entity with a high incidence on intensive care units (ICU) [1,2]. Up to 57% of all critically ill patients suffer from AKI [3] and in 50% of these cases, sepsis appears to be the most frequent contributing factor [1]. Mechanistically, the pathophysiology of AKI in sepsis has to be kept apart from ischemic AKI, where systemic hypotension and reduced renal blood flow (RBF) result in acute tubular necrosis. In septic AKI, strong evidence supports an RBF-independent microcirculatory dysfunction in renal parenchyma induced by inflammatory mediators, immune cell infiltration, and the deregulation of nitric oxide synthase [4,5]. The resulting redistribution of blood flow from renal medulla to the cortex, as well as a general deterioration of microcirculatory oxygenation, lead to tubular stress/injury and the formation of reactive oxygen species [4]. However, low blood pressure and renal hypo-perfusion also contribute to renal injury in septic shock.
In general, septic AKI has to be considered as a syndrome [5], characterized by the fulfillment of both the new Sepsis-3 criteria [6] and the AKI definition by Kidney Disease Improving Global Outcomes (KDIGO) [7]. The total AKI-associated mortality is thereby high (40–60%) [1,2,8,9] and the corresponding short- and long-term outcomes in the form of chronic (CKD) or end-stage renal disease (ESRD) are devastating [9,10]. The incidence of RRT-requiring AKI thereby accounts for 4–8% [1,2,11] and about 12–25% of these patients remain RRT-dependent [1,8,9]. In total, this represents a heavy burden on health care providers, where RRT is one of the most driving cost factors [12,13]. In addition, the quality of life of ICU patients treated with RRT is essentially impaired compared to other long-term critically ill survivors [14,15,16]. In order to improve AKI therapy and (long-term) outcomes in sepsis and critical illness, the precise measurement of renal function, reliable AKI staging, and optimal timing of renal replacement therapy (RRT) are essential. A better understanding is needed in light of the potential harm of RRT procedures and substantial health care costs. This review critically assesses our current knowledge of AKI staging, reviews problems in the determination of kidney function, and discusses the difficulties surrounding the timely initiation of RRT in order to give rise to potential improvements in AKI management and future study designs.

2. Staging of Acute Kidney Injury

The most recent concept of AKI staging was published by the Kidney Disease Improving Global Outcomes (KDIGO) group in 2012 [7] (Table 1) and defines AKI by changes in serum creatinine (SCr) and/or urine output (UO).
KDIGO merged the Acute Kidney Network (AKIN)- and RIFLE (Risk, Injury, Failure, Loss, End-Stage Kidney Disease)-criteria [17,18] to improve the sensitivity of AKI diagnosis and assessment of related in-hospital mortality [2,7,19]. This was achieved by merging both the absolute SCr rise from the baseline (AKIN: SCr ≥ 0.3 mg/dL or SCr ≥ 1.5-fold, RIFLE: only SCr ≥ 1.5-fold) and the time periods of SCr increases used by RIFLE and AKIN (AKIN: <48 h, RIFLE: within 1–7 days and >24 h). It is noteworthy that only slightly modified SCr and UO criteria are likewise integrated in the new sepsis definition via the Sepsis-related Organ Failure Assessment (SOFA) Score [20]. The SOFA score provides the basis for the international consensus definition of sepsis and septic shock [6] and emphasizes the importance of sepsis-related organ failure in critical illness.
The definition of baseline SCr, however, affects AKI classification. KDIGO suggest the lowest SCr within the first seven days of admission. The way to define baseline SCr is controversial [21,22,23,24,25,26]. A recent study found that the mean of the outpatient SCr values from seven to 356 days before admission was the most reliable number [21]. However, the most recent outpatient SCr was only slightly inferior and is much more applicable in clinical practice [21]. But often preexisting blood results are often absent and only the lowest inpatient SCr gives an idea about the baseline kidney function. The occasionally suggested back-calculation of baseline SCr by reversing the Modification of Diet in Renal Disease (MDRD) equation—assuming a normal glomerular filtration rate (GFR) of 75 mL/min—needs to be used with caution, especially in elderly patients [25,26]. Due to unknown preexisting CKD, the calculated baseline SCr may be underestimated [23]. Without having any information about the former kidney function and patient’s history, sometimes only a normal SCr value after a passed AKI episode proves the initial degree of AKI severity. It is noteworthy that if SCr does not return to normal levels, a differentiation between a pre-existing or a new onset CKD is challenging. The determination of parathormone levels and ultrasound scans of the kidneys are crucial to answer this question [27,28]. Thereby, elevated parathormone levels, as a marker for an impaired calcium-phosphate metabolism, and kidneys small in size, are major signs for chronic renal damage [27,28]. Nevertheless, the definition of baseline SCr can significantly influence AKI staging.

Outcomes and Staging

Recent studies investigated the ability of the KDIGO criteria to predict the outcome of AKI [29,30]. Compared to earlier studies [31,32,33], the authors showed an increased in-hospital mortality rate with a higher AKI stage, with odds ratios (OR) of 1.68 (95% Confidence Interval (CI) 0.74–3.84), 2.25 (95% CI 0.91–5.56), and 9.40 (95% CI 4.26–20.70) for AKI stage I, stage II, and stage III, respectively. Patients who fulfill both the SCr and UO criteria exhibit the highest long- and short-term mortality- and RRT-rates [29,30,34,35]. The KDIGO classification thereby prevails with a higher sensitivity for AKI diagnosis and is more predictive for hospital mortality compared to RIFLE and equivalent to AKIN [19]. A more detailed analysis of all 10 KDIGO-AKI definitions (Table 1) recently showed a remarkable difference in hospital mortality [29]. The UO criteria were linked to the highest mortality rate in any stage, with a 20% higher mortality rate in stage 3 compared to the corresponding SCr-based definition. The mortality was only higher in patients receiving RRT. Taken together, the mortality rate in stage 3 with its five definitions (Table 1) ranged from 27.6 to 55.6%, with SCr > 4 mg/dL representing the lowest mortality rate (27.6%). These findings emphasize a huge outcome variability within AKI stages, most notably in stage 3. A study by Vaara et al. analyzed the association between UO and the subsequent development of AKI by SCr-criteria, the need for RRT, and long-term mortality [35]. UO from <0.1 mL/kg/h for 3–6, 6–12 and 12–24 h were significantly associated with an increased risk of AKI, defined by SCr or the need for RRT with an OR of 2.17 (95% CI 1.35–3.48), 2.95 (95% CI 1.20–7.25), and 5.74 (95% CI 1.67–19.73), respectively. Comparable results were found for 90-days mortality. An UO of 0.1 to <0.3 mL/kg/h for more than 6 h and periods of UO < 0.1 mL/kg/h for longer than 3, 3–6, 6–12, 12–24, and >24 h were related to an increase in 90-days mortality with an OR of 1.96 (95% CI 1.13–3.38), 2.08 (95% CI 1.27–3.42), 3.04 (95% CI 1.50–6.15), 6.78 (95% CI 2.79–16.44), and 9.76 (95% CI 4.07–23.43), respectively. This emphasizes that the reduction in UO represents an independent risk factor for increased 90-day mortality.
Hence, these results may challenge the AKI staging by KDIGO due to a huge variation in the outcome parameters between SCr- and UO-criteria of the same AKI stage, most notably within the UO range <0.3 mL/kg/h. In the future integration of “renal damage” biomarkers (Table 2) in AKI, scoring may improve early AKI diagnosis, the staging and outcome predicting ability of AKI-staging, and might help to predict the potential need for RRT in the further clinical course [36,37,38].

3. Estimated Glomerular Filtration Rate and Its Limitations on Intensive Care Units

Ideally, and certainly in an intensive care unit (ICU) setting, knowledge of the real time GFR should not only provide the exact level of kidney dysfunction, but should also allow a more accurate dosing of drugs. Especially in sepsis patients, an adequate dosing of antibiotics is of great relevance [45].
Unfortunately, the SCr derived from the estimated glomerular filtration rate (eGFR) has major limitations in critically ill patients. After a single renal insult—for instance a period of ischemia—it takes at least 24–72 h before a new steady state in SCr levels is established [46,47]. Consequently, it is misleading to rely on actual SCr values for calculating the GFR. Multiple insults and variable SCr kinetics, as well as changes in the volume of distribution (VOD) and alterations in creatinine generation, further complicate the definition of renal function [48,49]. The “Chronic Kidney Disease Epidemiology Collaboration” (CKD-EPI)- and “Modification of Diet in Renal Disease” (MDRD)-formulas to calculate eGFR have been developed in stabile CKD [50,51] and are thus inappropriate for use in AKI [52]. A recent study evaluated the performance of measured creatinine clearance (CrCl) and GFR estimations by MDRD, CKD-EPI, and Cockcroft-Gold in comparison to a gold standard GFR measurement by chromium-ethylenediaminetetraacetic acid (51Cr-EDTA) [49]. As expected, CrCl showed poor precision due to the non-existing steady state during urine collection, but GFR equations showed an even higher error when applied. Thus, CrCl with short urine collection periods (2–4 h) might currently be the most feasible and reliable GFR measurement method for ICU patients [53]. This time frame reduces the likelihood for errors caused by non-steady state conditions, inaccurate time-recording, and incomplete urine collection [53,54,55,56]. However, CrCl still tends to overestimate the GFR by 10–20% due to GFR independent tubular creatinine secretion [57].
A newer, functional, endogenous GFR marker is Cystatin C. Cystatin is a 13 kD cysteine proteinase inhibitor [58] produced at a constant rate by almost every nucleated cell and exclusively eliminated via glomerular filtration [59,60]. In contrast to SCr, it is less influenced by muscle mass, age, sex, and race, and has one third of the VOD of SCr, allowing a faster steady state attainment and earlier AKI detection [60,61,62,63]. However, the superiority of Cystatin C over SCr for GFR estimation in critical illness [64,65,66,67], as well as the impact of inflammation and sepsis on cystatin C levels, is doubtful [68,69,70,71,72,73]. Furthermore, glucocorticoid therapy, thyroid disease, cancer, smoking, obesity, and diabetes may all substantially affect the Cystatin C serum concentration [68,69]. Thus, more reliable functional biomarkers with a small VOD and less metabolic interference are needed. The gold standard methods for GFR estimation, which repose on the clearance of exogenous marker (51Cr-EDTA, inulin), are not feasible on ICUs due to high costs and cumbersome assays [52].

4. Renal Replacement Therapy—Pitfalls and Timing

There are clear indications for the initiation of RRT (Figure 1). The optimal timing in the absence of these classic indications, however, is an ongoing matter of debate. Decreasing kidney function, electrolyte-/acid-base-disturbance, aggravating fluid overload (FO), and the progressive involvement of extra-renal organs are still the main decision criteria. The applied clinical and laboratory thresholds for RRT-initiation are controversial. In addition, confounding factors, which influence the blood urea nitrogen (BUN)/urea and SCr concentration, apart from kidney function, are often missed and may lead to a misjudgment in the diagnosis and severity of AKI, as well as RRT management.

4.1. Role of Serum Creatinine

Creatinine is an alkaline amid that is derived from the metabolism of skeletal muscle and from dietary meat intake. Mechanistically, one has to consider three distinct factors that influence the SCr concentration independently from kidney function: variation in creatinine production, tubular secretion, and analytical measurement issues.

4.2. Variation in Creatinine Production

The mean SCr values for men and women are 1.16 (median 1.09, 95th percentile 1.40) and 0.96 mg/dL (median 0.89, 95th percentile 1.18), respectively, and are higher in people of an Afro-American ethnicity, with values of 1.25 mg/dL in men (mean 1.16, 95th percentile 1.53) and 1.01 in women (median 0.92, 95th percentile 1.23) [76]. These differences are primarily explained by changes in body composition. Hence, old age, amputations, muscle wasting conditions, and malnutrition are associated with reduced creatinine production [77]. Especially in critical illness, malnutrition, an insufficient protein supply, and immobilization, the result of catabolism and muscle wasting can cause a significant drop in SCr levels [49,78,79]. Likewise, liver cirrhosis diminishes creatinine formation, secondary to decreased hepatic creatine synthesis [80], and reliable evidence supports an independent reduction in creatinine generation under septic conditions [81]. Considering that almost 50% of AKI cases on IUCs are sepsis-related [1,4], this is a relevant detail to keep in mind. In addition, an increase in the total body water level can mimic potential renal recovery or attenuates AKI severity by SCr dilution [48,82,83,84].
Other factors can lead to an artificial SCr increase such as a disproportional rise in SCr due to rhabdomyolysis. According to different authors, values beyond 2.0 up to 2.5 mg/dL/24 h or a disproportional increase in SCr compared to urea can indicate ongoing rhabdomyolysis [85,86,87]. In contrast, when the kidney function is totally lost, it is generally believed that SCr rises by approximately 1.0–1.5 mg/dL/24 h and does not exceed 2.0 mg/dL per day [85].

4.3. Variations in Tubular Creatinine Secretion

In total, proximal tubular creatinine secretion accounts for 10–20% of the total CrCl and increases to 50% in CKD when the GFR is dropping. Thus, CKD patients with a true GFR of 60–80 mL/min may still have an SCr value below 1 mg/dL [88,89,90]. Once the SCr level exceeds 1.5–2 mg/dL, the tubular secretory capacity is saturated and further injury leads to the expected rise in SCr [91].
More relevantly for ICU patients is drug interference with these organic cation secretory pathways. The drugs diminish proximal tubular creatinine secretion and lead to a GFR independent SCr rise, without an awareness of a misjudgment of kidney function. The SCr rise is reversible and normally does not exceed a range from 0.4–0.5 mg/dL, but might be higher in CKD patients when creatinine secretion is upregulated. Drugs that interfere with such pathways are trimethoprim, dronedarone, ranitidine, and cimetidine [49,92,93,94,95].

4.4. Creatinine Measurements

Drugs additionally interact with creatinine assays. The alkaline picrate method (Jaffé assay)—the standard colourimetric assay to determine SCr concentrations—typically interferes with other chromogens like cefoxitin and flucytosine [96,97]. This results in an artificial, kidney-independent increase in SCr. Clinically relevant is the interference of the Jaffé assay and acetoacetate in diabetic ketoacidosis. It can lead to rises of SCr from 0.5 to >2 mg/dL or more [98,99,100,101]. Other compounds that may artificially increase the colourimetric SCr concentration are glucose, IgM paraproteins, ketoacids, uric acid, hemolysed hemoglobin >600 mg/dL, ascorbic acid, cephalosporines, and dopamine [102,103]. The more expensive enzymatic assays are considered to be more precise, with less interference [102,104]. In contrast, hyperbilirubinemia affects the assays by decreasing the SCr levels. This effect has progressive dynamics beyond serum bilirubin concentrations of 9.9 and 19.9 mg/dL for kinetic Jaffé and enzymatic assays, respectively [102,104]. The magnitude of bilirubin interference is laboratory dependent, ranging from 1.9 to 30 mg/dL [80].
Even today, a universal and standardized creatinine assay is missing. SCr alterations ± 0.3 mg/dL between different laboratories are common [57]. In a study evaluating over 5000 laboratories, the overall mean SCr value ranged from 0.84 to 1.21 mg/dL when measuring a standardized sample by Jaffé or an enzymatic assay [99]. All factors which influence SCr levels independent from kidney function are summarized in Table 3.

4.5. Role of Blood Urea Nitrogen/Urea

Blood urea nitrogen (BUN) is a derived measure for the blood nitrogen content of urea (BUN mg/dL × 2.142 = urea mg/dL). With an average protein diet, a stable volume status, and balanced electrolytes, the ratio of BUN to SCr (BUN/SCr) in healthy individuals is approximately 10:1 [107,108]. Nitrogen retention occurs when the GFR is reduced to less than 30%. However, in contrast to SCr, the rate of urea production is less constant and altered by several factors beyond renal function [108,109].
Under normal conditions, 40–50% of the filtered urea is passively reabsorbed in the tubule to preserve a sufficient osmotic gradient in the renal medulla. In cases of volume depletion, urea reabsorption increases passively as a function of increased proximal sodium and water reabsorption, and further by antidiuretic hormone mediated diffusion in the collecting duct [108,110]. Altogether, this leads to a rise in BUN out of proportion to GFR and SCr.
The amount of BUN/urea formation depends on four aspects: dietary protein supply, rate of amino acid incorporation into tissue (anabolism), amino acid release from tissue (catabolism), and liver capacity to form urea [108]. Any variation in these metabolic pathways results in a disproportional BUN/SCr dissociation. Thus, a low protein diet or liver disease might be associated with near-normal BUN levels, despite a reduction in GFR [80,111]. In contrast, a high-protein diet, intestinal blood loss, and accelerated tissue breakdown due to malnutrition, trauma, glucocorticoid therapy, and immobilization are causes of an elevated urea production [79,108,112,113]. This primarily kidney-independent rise in blood nitrogen metabolites is called azotemia and should be considered apart from situations where urea serves as the surrogate parameter for other retained metabolites due to renal impairment (“uremia”). In accordance with data where “uremic symptoms” occur after urea loading when the urea levels exceed 300 mg/dL [114], a more delayed RRT initiation might be justified in azotemia. The identification and remediation of the underlying trigger factor is crucial in this context. Apart from azotemia, however, the latest data by Gaudry et al. supports a restrictive RRT initiation as long as the BUN level remains below 90 mg/dL (~urea 193 mg/dL) [74]. The safety of a delayed RRT initiation above this BUN level remains unclear.

4.6. Timing of Renal Replacement Therapy

The definition of “early” versus “late” RRT Initiation is controversial. Consequently, the related thresholds of BUN/urea, SCr [115,116], and UO [117] vary enormously across all studies and make them difficult to compare [118]. The study quality is thereby extremely heterogenic and the disease severity differs substantially [115,117,119].
Table 4 summarizes all relevant studies according to their study design and gives an overview of the variability of applied “early” and “late” RRT criteria, the final pre-dialytic SCr, and BUN/urea study cutoffs, as well as the corresponding mortality. Studies prior to 1990 are excluded in agreement with other authors due to improved RRT expertise and intensive care management [119]. In this context, meta-analyses [115,117,119], and especially observational studies [120,121,122,123,124], recently showed a tendency towards a reduced mortality or improved renal recovery under “early” RRT. This result is crucially driven by observational studies with significant heterogeneity and study quality [115,119]. However, after exclusion of observational studies, meta-analyses, as well as two recent RCTs showed no mortality differences [74,125].
In the end, a general problem across all studies that remains is the distinction between beneficial and unnecessary “early” RRT due to spontaneous renal recovery. Recent data supports this issue by showing a higher autonomous renal recovery rate in the “late” group and a delayed recovery under “early” RRT [74,116,125]. Gaudry et al. even showed an autonomous renal recovery of 49% in the “late” RRT group, with the lowest associated mortality (37.1%). However, patients in the “late” group without renal recovery revealed the highest mortality (61.8%). This might indicate that the early identification of patients without autonomous recovery, rather than RRT timing, is the real point of interest. Nevertheless, in the single center study by Zarbock et al., the mortality was significantly lower under “early” RRT [126]. However, the result may have been influenced by a diminished timeframe for autonomous renal recovery due to an RRT that was applied relatively early in the “late” RRT group in relation to other studies (Table 4) [74,126]. Hence, current data remains conflicting.
Taken together, RRT initiation before the development of life-threatening complications is desirable. The use of clear “cutoffs” (crea, urea/BUN) for RRT initiation remains questionable and is not recommended by the KDIGO guidelines. In rising FO, RRT should be applied restrictively as long as oliguria persists for less than 72 h, FO accounts for less than a 10% increase of body weight, and the oxygen demand remains stable [74,75]. In more severe cases of FO, RRT initiation remains an individual, clinical decision dependent on the underlying illness, hemodynamic stability, volume dependent cardiac output, and oxygen demand. Keeping these issues in mind, Figure 1 (“Heidelberg Standard”) provides an algorithm for RRT initiation.
In future study designs, the use of biomarkers for RRT timing and the identification of high risk patients might be of great interest. However, a better understanding of their role in heterogeneous AKI pathophysiology and the establishment of biomarker thresholds, which sufficiently predict AKI and outcomes in heterogeneous cohorts, are indispensable.
In this regard, the cell cycle arrest biomarkers “tissue inhibitor of metalloproteinase-2” (TIMP-2) and “insulin like growth factor binding protein-7 (IGFBP-7), which can be measured with a point-of-care device (Nephrocheck) [47], may represent the first milestones in this field. They have already proven a high diagnostic potential in predicting moderate and severe AKI 12 h after admission [41,42,127], but need to be validated for RRT initiation. As G1-cell cycle arrest molecules, both biomarker possess the advantage of indicating a very early impairment of (tubular) renal function and are verifiably involved in AKI pathogenesis [39,128,129]. In the future, not one, but rather a cluster of biomarkers (Table 2) may be needed to sub-classify heterogeneous AKI pathophysiology in order to improve the prediction of AKI with a need for RRT, as well as AKI diagnosis, staging, and long-term outcomes [130].

5. Potential Harm of Renal Replacement Therapy

Known from RRT initiation in ESRD [147], the subsequent loss of residual kidney function might also occur in AKI patients. In addition, renal recovery appears to be delayed after the “early” initiation of RRT [74,116,125]. The underlying factors which negatively affect renal function and recovery thereby rely on three mechanisms: decline in UO, RRT induced hypotension, and interference with inflammatory pathways. Thus, an optimal RRT timing and non-dialytic AKI management, which buys time for autonomous renal recovery, are crucial to reduce unnecessary RRT (Table 5).

5.1. Decline in Urine Output

RRT initiation is frequently accompanied by a fall in UO as a function of volume and urea removal [147,158]. However, so far, there is no reliable evidence that reduced UO by itself compromises renal recovery. Most patients who require RRT have less than 5–10% of their nephrons functioning and alterations in UO only take place in these remaining nephrons [159]. Consequently, reduced UO does not delay or alter the regeneration of the 90–95% of nephrons that are no longer functioning. In accordance, increasing UO via loop diuretics neither shortens AKI duration nor reduces the need for RRT, and might be associated with less renal recovery and an increased risk of death [154,160,161,162,163,164,165]. However, an appropriate use of diuretics is justified to prevent FO and electrolyte imbalance, particularly to facilitate sufficient mechanical ventilation [75,161,162,166].

5.2. Renal Replacement Therapy-Induced Hypotension

Decreased renal perfusion due to intravascular volume depletion, decreased cardiac output, and systemic hypotension are the most common mechanisms which prolong the course of renal injury [167,168]. The situation is aggravated by an impairment of renal autoregulation in AKI that leads to a microvascular imbalance, even with small changes in the systemic blood pressure [169]. Consequently, ischemia and reperfusion lead to the impairment of tubular transport mechanisms and acute tubular necrosis [4,170,171]. Especially in septic AKI, the drop in the tubular reabsorptive capacity might result in high sodium and chloride concentrations in distal tubules, which is then sensed by the macula densa and leads to a drop in the GFR via negative tubular glomerular feedback [171,172]. Furthermore, there is strong evidence that ischemic AKI impairs the expression of organic anion transporters (OAT)—essential for the excretion of toxic compounds—in proximal tubular cells. This mechanism is mediated by metabolites of cyclooxygenase 1 (COX-1), especially prostaglandin E2 [173]. The consecutive accumulation of toxic compounds might explain the resulting negative effects on renal perfusion, post-ischemic histological alterations, increased apoptosis, and on renal outcome, determined by GFR. In this context, Indomethacin, a COX-1 inhibitor, showed a remarkable ability to restore sufficient OAT expression and protection against renal damage after ischemic AKI, without affecting renal perfusion [174].
Returning to the underlying mechanism of RRT-induced hypotension, fluid removal and the derangement of solutes remain the primary causes [175]. Thus, hemofiltration procedures with less solute interference and a continuous type of application with gentle fluid removal, theoretically permit a higher hemodynamic stability than hemodialysis [176,177,178,179]. Despite these theoretical advantages of hemofiltration, the data on this issue is inconclusive. However, the hemodynamic instability during dialysis is not that relevant in clinical practice, especially in the Age of hybrid procedures like sustained low efficiency dialysis (SLED) [180,181,182,183]. In this context, observational studies have shown a tendency towards improved renal recovery under continuous hemofiltration, whereas a recent meta-analysis (excluding observational studies) and RCTs showed no difference [184,185,186,187]. The corresponding mortality rates were comparable in these studies. Hence, in accordance with recent data, there is no reliable evidence justifying a general preference for hemofiltration over dialysis procedures in clinical practice [181,188,189].

5.3. Activation of Inflammatory Pathways

Renal recovery may be hampered by the activation of inflammatory pathways via blood-dialyzer interaction [190]. At least in part, this is mediated by the upregulation of adhesion molecules like “intracellular adhesion molecule-1” (ICAM-1) on granulocytes. The level of complement activation is dialyzer membrane-dependent. Particularly, synthetic “biocompatible” membranes (polysulfone, polycarbonate, polymethylmethacrylate = PMMA)—in contrast to cuprophane—activate complement to a lesser extent and cause less neutropenia [191,192]. In most, but not all clinical studies, the use of biocompatible membranes was associated with higher renal recovery rates and improved survival [193,194,195,196]. Another relevant aspect during RRT might be the clearance of inflammation mediators, especially in septic AKI. On one hand there is evidence that pro-inflammatory cytokines like interleukin (IL) 6, IL 8, IL 10, and TNFα are associated with increased mortality in septic AKI and might be blamed for septic organ failure [4,197,198,199,200,201]. Thus, the unselective clearance of pro-inflammatory cytokines, mostly by adhesion to PMMA membranes or others [202,203,204], might promise beneficial effects on outcomes in sepsis [205]. On the other hand, cytokine clearances of each cytokine vary enormously and depend on the applied RRT procedures, as well as the filter membrane used [206]. Hence, the clearance of beneficial anti-inflammatory cytokines like IL-22 through RRT could also be a potential cause of harm for renal recovery [207,208]. Prospective, randomized clinical trials with “high cut off” membranes are needed to develop a better understanding of cytokine clearance and its effect on clinical outcomes in sepsis and heterogeneous AKI pathophysiology [209,210,211].

6. Conclusions

AKI is a major complication in critically ill patients suffering from sepsis or septic shock. Even moderate rises in SCr correlate with adverse short- and long-term outcomes. Thus, a differentiated AKI staging, which predicts future clinical outcomes, is mandatory for an appropriate initiation of therapeutic measures. Thereby, an independent clinical evaluation of crea und UO criteria in AKI staging—due to enormous outcome variation—is indispensable. Furthermore, the knowledge of the “true” GFR is fundamental in septic and critically ill patients. The at present methods used for estimating renal function are neither feasible in an ICU setting nor give an accurate estimate of “true” GFR. The establishment of a more reliable, functional marker for GFR-measurement is needed. The ability of BUN/urea and SCr to serve as an independent parameter for RRT initiation in AKI is questionable. However, taking clinical observations, potential confounders, and disease-related and dietary aspects into account, a differentiated analysis of urea and SCr alterations provides important information about renal function. Thereby, a key point is to distinguish between azotemia and developing uremia. Neglecting potential confounders of SCr-/urea-levels considerably influences AKI studies and might lead, at least in part, to the prevailing inconsistency.
In summary, RRT initiation remains an individual clinical decision based on expertise and special patient characteristics, leading to wide variation in practice. Furthermore, it is not RRT timing, but rather the early identification of patients without autonomous renal recovery, which may be the major point of interest. In the future, a set of biomarkers may help us to solve these issues and might elucidate septic and heterogeneous AKI pathophysiology. Until then, it is still a long way down the road. A better understanding of an appropriate use of RRT besides absolute indications is needed to avoid unnecessary RRT for higher patient safety and lower health care costs.

Acknowledgments

We acknowledge financial support by Deutsche Forschungsgemeinschaft and Ruprecht-Karls-Universität Heidelberg within the funding programme Open Access Publishing.

Authors Contributions

Christian Nusshag conceived the review, conducted the literature research, drafted the manuscript, and prepared the tables and figures. Markus A. Weigand, Martin Zeier, and Christian Morath provided additional literature and were involved in critically revising the article. Thorsten Brenner participated in the design of the review, helped to draft the manuscript, and critically revised the tables, figures, and the article.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

AKIAcute kidney injury
AKINAcute Kidney Injury Network
BUNBlood urea nitrogen
CKDChronic kidney disease
CKD-EPIChronic Kidney Disease Epidemiology Collaboration
COX-1Cyclooxygenase-1
CrClCreatinine clearance
51Cr-EDTAChromium-ethylenediaminetetraacetic acid
ESRDEnd-stage renal disease
GFRGlomerular filtration rate
eGFREstimated glomerular filtration rate
FOFluid overload
ICAM-1Intracellular adhesion molecule-1
ICUIntensive Care Unit
IGFBP-7Insulin like growth factor binding protein-7
KDIGOKidney Disease Improving Global Outcomes
ILInterleukin
MDRDModification of diet in renal disease
OATOrganic anion transporter
PMMAPolymethylmethacrylate
RBFRenal blood flow
RRTRenal replacement therapy
SCrSerum creatinine
TIMP-2Tissue inhibitor of metalloproteinase-2
TGFTubular glomerular feedback
TNFαTumor necrosis factor alpha
UOUrine output
VODVolume of distribution

References

  1. Uchino, S.; Kellum, J.A.; Bellomo, R.; Doig, G.S.; Morimatsu, H.; Morgera, S.; Schetz, M.; Tan, I.; Bouman, C.; Macedo, E.; et al. Acute renal failure in critically ill patients: A multinational, multicenter study. JAMA 2005, 294, 813–818. [Google Scholar] [CrossRef] [PubMed]
  2. Joannidis, M.; Metnitz, B.; Bauer, P.; Schusterschitz, N.; Moreno, R.; Druml, W.; Metnitz, P.G.H. Acute kidney injury in critically ill patients classified by AKIN versus RIFLE using the SAPS 3 database. Intensive Care Med. 2009, 35, 1692–1702. [Google Scholar] [CrossRef] [PubMed]
  3. Hoste, E.A.J.; Bagshaw, S.M.; Bellomo, R.; Cely, C.M.; Colman, R.; Cruz, D.N.; Edipidis, K.; Forni, L.G.; Gomersall, C.D.; Govil, D.; et al. Epidemiology of acute kidney injury in critically ill patients: The multinational AKI-EPI study. Intensive Care Med. 2015, 41, 1411–1423. [Google Scholar] [CrossRef] [PubMed]
  4. Ergin, B.; Kapucu, A.; Demirci-Tansel, C.; Ince, C. The renal microcirculation in sepsis. Nephrol. Dial. Transplant. 2015, 30, 169–177. [Google Scholar] [CrossRef] [PubMed]
  5. Bellomo, R.; Kellum, J.A.; Ronco, C.; Wald, R.; Mårtensson, J.; Maiden, M.; Bagshaw, S.M.; Glassford, N.J.; Lankadeva, Y.; Vaara, S.T.; et al. Acute kidney injury in sepsis. Intensive Care Med. 2017, 1–13. [Google Scholar] [CrossRef] [PubMed]
  6. Singer, M.; Deutschman, C.S.; Seymour, C.W.; Shankar-Hari, M.; Annane, D.; Bauer, M.; Bellomo, R.; Bernard, G.R.; Chiche, J.-D.; Coopersmith, C.M.; et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA 2016, 315, 801–810. [Google Scholar] [CrossRef] [PubMed]
  7. Kellum, J.A.; Lameire, N. KDIGO AKI Guideline Work Group Diagnosis, evaluation, and management of acute kidney injury: A KDIGO summary (Part 1). Crit. Care 2013, 17, 204. [Google Scholar] [CrossRef] [PubMed]
  8. Wald, R.; McArthur, E.; Adhikari, N.K.J.; Bagshaw, S.M.; Burns, K.E.A.; Garg, A.X.; Harel, Z.; Kitchlu, A.; Mazer, C.D.; Nash, D.M.; et al. Changing incidence and outcomes following dialysis-requiring acute kidney injury among critically ill adults: A population-based cohort study. Am. J. Kidney Dis. 2015, 65, 870–877. [Google Scholar] [CrossRef] [PubMed]
  9. Stads, S.; Fortrie, G.; van Bommel, J.; Zietse, R.; Betjes, M.G.H. Impaired kidney function at hospital discharge and long-term renal and overall survival in patients who received CRRT. Clin. J. Am. Soc. Nephrol. 2013, 8, 1284–1291. [Google Scholar] [CrossRef] [PubMed]
  10. Ishani, A.; Xue, J.L.; Himmelfarb, J.; Eggers, P.W.; Kimmel, P.L.; Molitoris, B.A.; Collins, A.J. Acute kidney injury increases risk of ESRD among elderly. J. Am. Soc. Nephrol. 2009, 20, 223–228. [Google Scholar] [CrossRef] [PubMed]
  11. Hoste, E.A.J.; Schurgers, M. Epidemiology of acute kidney injury: How big is the problem? Crit. Care Med. 2008, 36, S146–S151. [Google Scholar] [CrossRef] [PubMed]
  12. Srisawat, N.; Lawsin, L.; Uchino, S.; Bellomo, R.; Kellum, J.A. The BEST Kidney Investigators Cost of acute renal replacement therapy in the intensive care unit: Results from The Beginning and Ending Supportive Therapy for the Kidney (BEST Kidney) Study. Crit. Care 2010, 14, R46. [Google Scholar] [CrossRef] [PubMed]
  13. Farese, S.; Jakob, S.M.; Kalicki, R.; Frey, F.J.; Uehlinger, D.E. Treatment of acute renal failure in the intensive care unit: Lower costs by intermittent dialysis than continuous venovenous hemodiafiltration. Artif. Organs 2009, 33, 634–640. [Google Scholar] [CrossRef] [PubMed]
  14. Oeyen, S.; De Corte, W.; Benoit, D.; Annemans, L.; Dhondt, A.; Vanholder, R.; Decruyenaere, J.; Hoste, E. Long-term quality of life in critically ill patients with acute kidney injury treated with renal replacement therapy: A matched cohort study. Crit. Care 2015, 19, 1–11. [Google Scholar] [CrossRef] [PubMed]
  15. Orwelius, L.; Lobo, C.; Teixeira Pinto, A.; Carneiro, A.; Costa-Pereira, A.; Granja, C. Sepsis patients do not differ in health-related quality of life compared with other ICU patients. Acta Anaesthesiol. Scand. 2013, 57, 1201–1205. [Google Scholar] [CrossRef] [PubMed]
  16. Abelha, F.J.; Botelho, M.; Fernandes, V.; Barros, H. Outcome and quality of life of patients with acute kidney injury after major surgery. Nefrologia 2009, 29, 404–414. [Google Scholar] [PubMed]
  17. Bellomo, R.; Ronco, C.; Kellum, J.A.; Mehta, R.L.; Palevsky, P. 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]
  18. Mehta, R.L.; Kellum, J.A.; Shah, S.V.; Molitoris, B.A.; Ronco, C.; Warnock, D.G.; Levin, A. Acute kidney injury network: Report of an initiative to improve outcomes in acute kidney injury. Crit. Care 2007, 11, R31. [Google Scholar] [CrossRef] [PubMed]
  19. Luo, X.; Jiang, L.; Du, B.; Wen, Y.; Wang, M.; Xi, X. A comparison of different diagnostic criteria of acute kidney injury in critically ill patients. Crit. Care 2014, 18, R144. [Google Scholar] [CrossRef] [PubMed]
  20. Vincent, J.L.; Moreno, R.; Takala, J.; Willatts, S.; De Mendonça, A.; Bruining, H.; Reinhart, C.K.; Suter, P.M.; Thijs, L.G. The SOFA (Sepsis-related Organ Failure Assessment) score to describe organ dysfunction/failure. Intensive Care Med. 1996, 22, 707–710. [Google Scholar] [CrossRef] [PubMed]
  21. Siew, E.D.; Ikizler, T.A.; Matheny, M.E.; Shi, Y.; Schildcrout, J.S.; Danciu, I.; Dwyer, J.P.; Srichai, M.; Hung, A.M.; Smith, J.P.; et al. Estimating baseline kidney function in hospitalized patients with impaired kidney function. Clin. J. Am. Soc. Nephrol. 2012, 7, 712–719. [Google Scholar] [CrossRef] [PubMed]
  22. Siew, E.D.; Matheny, M.E.; Ikizler, T.A.; Lewis, J.B.; Miller, R.A.; Waitman, L.R.; Go, A.S.; Parikh, C.R.; Peterson, J.F. Commonly used surrogates for baseline renal function affect the classification and prognosis of acute kidney injury. Kidney Int. 2010, 77, 536–542. [Google Scholar] [CrossRef] [PubMed]
  23. Bagshaw, S.M.; Uchino, S.; Cruz, D.; Bellomo, R.; Morimatsu, H.; Morgera, S.; Schetz, M.; Tan, I.; Bouman, C.; Macedo, E.; et al. A comparison of observed versus estimated baseline creatinine for determination of RIFLE class in patients with acute kidney injury. Nephrol. Dial. Transplant. 2009, 24, 2739–2744. [Google Scholar] [CrossRef] [PubMed]
  24. Závada, J.; Hoste, E.; Cartin-Ceba, R.; Calzavacca, P.; Gajic, O.; Clermont, G.; Bellomo, R.; Kellum, J.A. A comparison of three methods to estimate baseline creatinine for RIFLE classification. Nephrol. Dial. Transplant. 2010, 25, 3911–3918. [Google Scholar] [CrossRef] [PubMed]
  25. Pickering, J.W.; Endre, Z.H. Back-calculating baseline creatinine with MDRD misclassifies acute kidney injury in the intensive care unit. Clin. J. Am. Soc. Nephrol. 2010, 5, 1165–1173. [Google Scholar] [CrossRef] [PubMed]
  26. Siew, E.D.; Peterson, J.F.; Eden, S.K.; Moons, K.G.; Ikizler, T.A.; Matheny, M.E. Use of multiple imputation method to improve estimation of missing baseline serum creatinine in acute kidney injury research. Clin. J. Am. Soc. Nephrol. 2013, 8, 10–18. [Google Scholar] [CrossRef] [PubMed]
  27. Meola, M.; Nalesso, F.; Petrucci, I.; Samoni, S.; Ronco, C. Ultrasound in Acute Kidney Disease. Contrib. Nephrol. 2016, 188, 11–20. [Google Scholar] [PubMed]
  28. Hedgeman, E.; Lipworth, L.; Lowe, K.; Saran, R.; Do, T.; Fryzek, J. International burden of chronic kidney disease and secondary hyperparathyroidism: A systematic review of the literature and available data. Int. J. Nephrol. 2015, 2015, 1–15. [Google Scholar] [CrossRef] [PubMed]
  29. Izawa, J.; Uchino, S.; Takinami, M. A detailed evaluation of the new acute kidney injury criteria by KDIGO in critically ill patients. J Anesth 2016, 30, 215–222. [Google Scholar] [CrossRef] [PubMed]
  30. Kellum, J.A.; Sileanu, F.E.; Murugan, R.; Lucko, N.; Shaw, A.D.; Clermont, G. Classifying AKI by urine output versus serum creatinine level. J. Am. Soc. Nephrol. 2015, 26, 2231–2238. [Google Scholar] [CrossRef] [PubMed]
  31. Ricci, Z.; Cruz, D.; Ronco, C. The RIFLE criteria and mortality in acute kidney injury: A systematic review. Kidney Int. 2008, 73, 538–546. [Google Scholar] [CrossRef] [PubMed]
  32. Bagshaw, S.M.; George, C.; Bellomo, R. A comparison of the RIFLE and AKIN criteria for acute kidney injury in critically ill patients. Nephrol. Dial. Transplant. 2008, 23, 1569–1574. [Google Scholar] [CrossRef] [PubMed]
  33. Lopes, J.A.; Fernandes, P.; Jorge, S.; Gonçalves, S.; Alvarez, A.; Costa e Silva, Z.; França, C.; Prata, M.M. Acute kidney injury in intensive care unit patients: A comparison between the RIFLE and the Acute Kidney Injury Network Classifications. Crit. Care 2008, 12, R110. [Google Scholar] [CrossRef] [PubMed]
  34. Macedo, E.; Malhotra, R.; Bouchard, J.; Wynn, S.K.; Mehta, R.L. Oliguria is an early predictor of higher mortality in critically ill patients. Kidney Int. 2011, 80, 760–767. [Google Scholar] [CrossRef] [PubMed]
  35. Vaara, S.T.; Parviainen, I.; Pettilä, V.; Nisula, S.; Inkinen, O.; Uusaro, A. Association of oliguria with the development of acute kidney injury in the critically ill. Kidney Int. 2015, 89, 200–208. [Google Scholar] [CrossRef] [PubMed]
  36. Murray, P.T.; Mehta, R.L.; Shaw, A.; Ronco, C.; Endre, Z.; Kellum, J.A.; Chawla, L.S.; Cruz, D.; Ince, C.; Okusa, M.D. Potential use of biomarkers in acute kidney injury: Report and summary of recommendations from the 10th Acute Dialysis Quality Initiative Consensus Conference. Kidney Int. 2014, 85, 513–521. [Google Scholar] [CrossRef] [PubMed]
  37. Endre, Z.H.; Kellum, J.A.; Di Somma, S.; Doi, K.; Goldstein, S.L.; Koyner, J.L.; Macedo, E.; Mehta, R.L.; Murray, P.T. Differential diagnosis of AKI in clinical practice by functional and damage biomarkers: Workgroup statements from the Tenth Acute Dialysis Quality Initiative Consensus Conference. Contrib. Nephrol. 2013, 182, 30–44. [Google Scholar] [PubMed]
  38. Dewitte, A.; Joannes-Boyau, O.; Sidobre, C.; Fleureau, C.; Bats, M.L.; Derache, P.; Leuillet, S.; Ripoche, J.; Combe, C.; Ouattara, A. kinetic eGFR and novel AKI biomarkers to predict renal recovery. Clin. J. Am. Soc. Nephrol. 2015, 10, 1900–1910. [Google Scholar] [CrossRef] [PubMed]
  39. Alge, J.L.; Arthur, J.M. Biomarkers of AKI: A review of mechanistic relevance and potential therapeutic implications. Clin. J. Am. Soc. Nephrol. 2015, 10, 147–155. [Google Scholar] [CrossRef] [PubMed]
  40. Emlet, D.R.; Pastor-Soler, N.; Marciszyn, A.; Wen, X.; Gomez, H.; Humphries, W.H., IV; Morrisroe, S.; Volpe, J.K.; Kellum, J.A. Insulin-like growth factor binding protein 7 and tissue inhibitor of metalloproteinases-2: Differential expression and secretion in human kidney tubule cells. AJP Renal Physiol. 2017, 312, F284–F296. [Google Scholar] [CrossRef] [PubMed]
  41. Bihorac, A.; Chawla, L.S.; Shaw, A.D.; Al-Khafaji, A.; Davison, D.L.; DeMuth, G.E.; Fitzgerald, R.; Gong, M.N.; Graham, D.D.; Gunnerson, K.; et al. Validation of cell-cycle arrest biomarkers for acute kidney injury using clinical adjudication. Am. J. Respir. Crit. Care. Med. 2014, 189, 932–939. [Google Scholar] [CrossRef] [PubMed]
  42. Hoste, E.A.J.; McCullough, P.A.; Kashani, K.; Chawla, L.S.; Joannidis, M.; Shaw, A.D.; Feldkamp, T.; Uettwiller-Geiger, D.L.; McCarthy, P.; Shi, J.; et al. Derivation and validation of cutoffs for clinical use of cell cycle arrest biomarkers. Nephrol. Dial. Transplant. 2014, 29, 2054–2061. [Google Scholar] [CrossRef] [PubMed]
  43. Kashani, K.; Cheungpasitporn, W.; Ronco, C. Biomarkers of acute kidney injury: The pathway from discovery to clinical adoption. Clin. Chem. Lab. Med. 2017. [Google Scholar] [CrossRef] [PubMed]
  44. Gist, K.M.; Goldstein, S.L.; Wrona, J.; Alten, J.A.; Basu, R.K.; Cooper, D.S.; Soranno, D.E.; Duplantis, J.; Altmann, C.; Gao, Z.; et al. Kinetics of the cell cycle arrest biomarkers (TIMP-2*IGFBP-7) for prediction of acute kidney injury in infants after cardiac surgery. Pediatr. Nephrol. 2017, 368–369. [Google Scholar] [CrossRef] [PubMed]
  45. Sime, F.B.; Roberts, J.A. Antibiotic dosing in critically ill patients receiving renal replacement therapy. Expert Rev. Clin. Pharmacol. 2015, 1–3. [Google Scholar] [CrossRef] [PubMed]
  46. Moran, S.M.; Myers, B.D. Course of acute renal failure studied by a model of creatinine kinetics. Kidney Int. 1985, 27, 928–937. [Google Scholar] [CrossRef] [PubMed]
  47. Endre, Z.H.; Pickering, J.W. Acute kidney injury: Cell cycle arrest biomarkers win race for AKI diagnosis. Nat. Rev. Nephrol. 2014, 10, 683–685. [Google Scholar] [CrossRef] [PubMed]
  48. Macedo, E.; Bouchard, J.; Soroko, S.H.; Chertow, G.M.; Himmelfarb, J.; Ikizler, T.A.; Paganini, E.P.; Mehta, R.L. Fluid accumulation, recognition and staging of acute kidney injury in critically-ill patients. Crit. Care 2010, 14, R82. [Google Scholar] [CrossRef] [PubMed]
  49. Bragadottir, G.; Redfors, B.; Ricksten, S.E. Assessing glomerular filtration rate (GFR) in critically ill patients with acute kidney injury-true GFR versus urinary creatinine clearance and estimating equations. Crit. Care 2013, 17, R108. [Google Scholar] [CrossRef] [PubMed]
  50. Levey, A.S.; Bosch, J.P.; Lewis, J.B.; Greene, T.; Rogers, N.; Roth, D. A more accurate method to estimate glomerular filtration rate from serum creatinine: A new prediction equation. Ann. Intern. Med. 1999, 130, 461–470. [Google Scholar] [CrossRef] [PubMed]
  51. Levey, A.S. A New equation to estimate glomerular filtration rate. Ann. Intern. Med. 2009, 150, 604–612. [Google Scholar] [CrossRef] [PubMed]
  52. Macedo, E.; Mehta, R.L. Measuring renal function in critically ill patients: Tools and strategies for assessing glomerular filtration rate. Curr. Opin. Crit. Care 2013, 19, 560–566. [Google Scholar] [CrossRef] [PubMed]
  53. Pickering, J.W.; Frampton, C.M.; Walker, R.J.; Shaw, G.M.; Endre, Z.H. Four hour creatinine clearance is better than plasma creatinine for monitoring renal function in critically ill patients. Crit. Care 2012, 16, R107. [Google Scholar] [CrossRef] [PubMed]
  54. Hoste, E.A.J.; Damen, J.; Vanholder, R.C.; Lameire, N.H.; Delanghe, J.R.; van den Hauwe, K.; Colardyn, F.A. Assessment of renal function in recently admitted critically ill patients with normal serum creatinine. Nephrol. Dial. Transplant. 2005, 20, 747–753. [Google Scholar] [CrossRef] [PubMed]
  55. Herrera-Gutiérrez, M.E.; Seller-Pérez, G.; Banderas-Bravo, E.; Muñoz-Bono, J.; Lebrón-Gallardo, M.; Fernandez-Ortega, J.F. Replacement of 24-h creatinine clearance by 2-h creatinine clearance in intensive care unit patients: A single-center study. Intensive Care Med. 2007, 33, 1900–1906. [Google Scholar] [CrossRef] [PubMed]
  56. Herget-Rosenthal, S.; Kribben, A.; Pietruck, F.; Ross, B.; Philipp, T. Two by two hour creatinine clearance—Repeatable and valid. Clin. Nephrol. 1999, 51, 348–354. [Google Scholar] [PubMed]
  57. Coresh, J.; Astor, B.C.; McQuillan, G.; Kusek, J.; Greene, T.; Van Lente, F.; Levey, A.S. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. Am. J. Kidney Dis. 2002, 39, 920–929. [Google Scholar] [CrossRef] [PubMed]
  58. Barrett, A.J.; Davies, M.E.; Grubb, A. The place of human γ-trace (cystatin C) amongst the cysteine proteinase inhibitors. Biochem. Biophys. Res. Commun. 1984, 120, 631–636. [Google Scholar] [CrossRef]
  59. Madero, M.; Sarnak, M.J.; Stevens, L.A. Serum cystatin C as a marker of glomerular filtration rate. Curr. Opin. Nephrol. Hypertens. 2006, 15, 610–616. [Google Scholar] [CrossRef] [PubMed]
  60. Nejat, M.; Pickering, J.W.; Walker, R.J.; Endre, Z.H. Rapid detection of acute kidney injury by plasma cystatin C in the intensive care unit. Nephrol. Dial. Transplant. 2010, 25, 3283–3289. [Google Scholar] [CrossRef] [PubMed]
  61. Zhang, Z.; Lu, B.; Sheng, X.; Jin, N. Cystatin C in prediction of acute kidney injury: A systemic review and meta-analysis. Am. J. Kidney Dis. 2011, 58, 356–365. [Google Scholar] [CrossRef] [PubMed]
  62. Herget-Rosenthal, S.; Bökenkamp, A.; Hofmann, W. How to estimate GFR-serum creatinine, serum cystatin C or equations? Clin. Biochem. 2007, 40, 153–161. [Google Scholar] [CrossRef] [PubMed]
  63. Dai, X.; Zeng, Z.; Fu, C.; Zhang, S.; Cai, Y.; Chen, Z. Diagnostic value of neutrophil gelatinase-associated lipocalin, cystatin C, and soluble triggering receptor expressed on myeloid cells-1 in critically ill patients with sepsis-associated acute kidney injury. Crit. Care 2015, 19, 223. [Google Scholar] [CrossRef] [PubMed]
  64. Carlier, M.; Dumoulin, A.; Janssen, A.; Picavet, S.; Vanthuyne, S.; Van Eynde, R.; Vanholder, R.; Delanghe, J.; De Schoenmakere, G.; De Waele, J.J.; et al. Comparison of different equations to assess glomerular filtration in critically ill patients. Intensive Care Med. 2015, 41, 427–435. [Google Scholar] [CrossRef] [PubMed]
  65. Pottel, H.; Delanaye, P.; Schaeffner, E.; Dubourg, L.; Eriksen, B.O.; Melsom, T.; Lamb, E.J.; Rule, A.D.; Turner, S.T.; Glassock, R.J.; et al. Estimating glomerular filtration rate for the full age spectrum from serum creatinine and cystatin C. Nephrol. Dial. Transplant. 2017, 32, 497–507. [Google Scholar] [CrossRef] [PubMed]
  66. Delanaye, P.; Cavalier, E.; Morel, J.; Mehdi, M.; Maillard, N.; Claisse, G.; Lambermont, B.; Dubois, B.E.; Damas, P.; Krzesinski, J.M.; et al. Detection of decreased glomerular filtration rate in intensive care units: Serum cystatin C versusserum creatinine. BMC Nephrol. 2014, 15, 877. [Google Scholar] [CrossRef] [PubMed]
  67. Diego, E.; Castro, P.; Soy, D.; Poch, E.; Nicolás, J.M. Predictive performance of glomerular filtration rate estimation equations based on cystatin C versus serum creatinine values in critically ill patients. Am. J. Health Syst. Pharm. 2016, 73, 206–215. [Google Scholar] [CrossRef] [PubMed]
  68. Liu, X.; Foster, M.C.; Tighiouart, H.; Anderson, A.H.; Beck, G.J.; Contreras, G.; Coresh, J.; Eckfeldt, J.H.; Feldman, H.I.; Greene, T.; et al. Non-GFR determinants of low-molecular-weight serum protein filtration markers in CKD. Am. J. Kidney Dis. 2016, 68, 892–900. [Google Scholar] [CrossRef] [PubMed]
  69. Stevens, L.A.; Schmid, C.H.; Greene, T.; Li, L.; Beck, G.J.; Joffe, M.M.; Froissart, M.; Kusek, J.W.; Zhang, Y.L.; Coresh, J.; et al. Factors other than glomerular filtration rate affect serum cystatin C levels. Kidney Int. 2009, 75, 652–660. [Google Scholar] [CrossRef] [PubMed]
  70. Mårtensson, J.; Martling, C.R.; Oldner, A.; Bell, M. Impact of sepsis on levels of plasma cystatin C in AKI and non-AKI patients. Nephrol. Dial. Transplant. 2012, 27, 576–581. [Google Scholar] [CrossRef] [PubMed]
  71. Filler, G.; Bökenkamp, A.; Hofmann, W.; Le Bricon, T.; Martínez-Brú, C.; Grubb, A. Cystatin C as a marker of GFR-history, indications, and future research. Clin. Biochem. 2005, 38, 1–8. [Google Scholar] [CrossRef] [PubMed]
  72. Leelahavanichkul, A.; Souza, A.C.P.; Street, J.M.; Hsu, V.; Tsuji, T.; Doi, K.; Li, L.; Hu, X.; Zhou, H.; Kumar, P.; et al. Comparison of serum creatinine and serum cystatin C as biomarkers to detect sepsis-induced acute kidney injury and to predict mortality in CD-1 mice. Am. J. Physiol. Renal. Physiol. 2014, 307, F939–F948. [Google Scholar] [CrossRef] [PubMed]
  73. Di Nardo, M.; Ficarella, A.; Ricci, Z.; Luciano, R.; Stoppa, F.; Picardo, S.; Picca, S.; Muraca, M.; Cogo, P. Impact of severe sepsis on serum and urinary biomarkers of acute kidney injury in critically ill children: An observational study. Blood Purif. 2013, 35, 172–176. [Google Scholar] [CrossRef] [PubMed]
  74. Gaudry, S.; Hajage, D.; Schortgen, F.; Martin-Lefevre, L.; Pons, B.; Boulet, E.; Boyer, A.; Chevrel, G.; Lerolle, N.; Carpentier, D.; et al. Initiation strategies for renal-replacement therapy in the intensive care unit. N. Engl. J. Med. 2016, 375, 122–133. [Google Scholar] [CrossRef] [PubMed]
  75. Zhang, L.; Chen, Z.; Diao, Y.; Yang, Y.; Fu, P. Associations of fluid overload with mortality and kidney recovery in patients with acute kidney injury: A systematic review and meta-analysis. J. Crit. Care 2015, 30, 860. [Google Scholar] [CrossRef] [PubMed]
  76. Jones, C.A.; McQuillan, G.M.; Kusek, J.W.; Eberhardt, M.S.; Herman, W.H.; Coresh, J.; Salive, M.; Jones, C.P.; Agodoa, L.Y. Serum creatinine levels in the US population: Third National Health And Nutrition Examination Survey. Am. J. Kidney Dis. 1998, 32, 992–999. [Google Scholar] [CrossRef]
  77. Thomas, M.E.; Blaine, C.; Dawnay, A.; Devonald, M.A.J.; Ftouh, S.; Laing, C.; Latchem, S.; Lewington, A.; Milford, D.V.; Ostermann, M. The definition of acute kidney injury and its use in practice. Kidney Int. 2014, 87, 62–73. [Google Scholar] [CrossRef] [PubMed]
  78. Clark, W.R.; Mueller, B.A.; Kraus, M.A.; Macias, W.L. Quantification of creatinine kinetic parameters in patients with acute renal failure. Kidney Int. 1998, 54, 554–560. [Google Scholar] [CrossRef] [PubMed]
  79. Oshima, T.; Deutz, N.E.; Doig, G.; Wischmeyer, P.E.; Pichard, C. Protein-energy nutrition in the ICU is the power couple: A hypothesis forming analysis. Clin. Nutr. 2016, 35, 968–974. [Google Scholar] [CrossRef] [PubMed]
  80. Sherman, D.S.; Fish, D.N.; Teitelbaum, I. Assessing renal function in cirrhotic patients: Problems and pitfalls. Am. J. Kidney Dis. 2003, 41, 269–278. [Google Scholar] [CrossRef] [PubMed]
  81. Doi, K.; Yuen, P.S.T.; Eisner, C.; Hu, X.; Leelahavanichkul, A.; Schnermann, J.; Star, R.A. Reduced production of creatinine limits its use as marker of kidney injury in sepsis. J. Am. Soc. Nephrol. 2009, 20, 1217–1221. [Google Scholar] [CrossRef] [PubMed]
  82. Liu, K.D.; Thompson, B.T.; Ancukiewicz, M.; Steingrub, J.S.; Douglas, I.S.; Matthay, M.A.; Wright, P.; Peterson, M.W.; Rock, P.; Hyzy, R.C.; et al. Acute kidney injury in patients with acute lung injury: Impact of fluid accumulation on classification of acute kidney injury and associated outcomes. Crit. Care Med. 2011, 39, 2665–2671. [Google Scholar] [CrossRef] [PubMed]
  83. Endre, Z.H.; Pickering, J.W. Biomarkers and creatinine in AKI: The trough of disillusionment or the slope of enlightenment? Kidney Int. 2013, 84, 644–647. [Google Scholar] [CrossRef] [PubMed]
  84. Perrone, R.D.; Madias, N.E.; Levey, A.S. Serum creatinine as an index of renal function: New insights into old concepts. Clin. Chem. 1992, 38, 1933–1953. [Google Scholar] [PubMed]
  85. Chen, S. Retooling the creatinine clearance equation to estimate kinetic GFR when the plasma creatinine is changing acutely. J. Am. Soc. Nephrol. 2013, 24, 877–888. [Google Scholar] [CrossRef] [PubMed]
  86. Bosch, X.; Poch, E.; Grau, J.M. Rhabdomyolysis and acute kidney injury. N. Engl. J. Med. 2009, 361, 62–72. [Google Scholar] [CrossRef] [PubMed]
  87. Woodrow, G.; Brownjohn, A.M.; Turney, J.H. The clinical and biochemical features of acute renal failure due to rhabdomyolysis. Ren. Fail. 1995, 17, 467–474. [Google Scholar] [CrossRef] [PubMed]
  88. Levey, A.S. Measurement of renal function in chronic renal disease. Kidney Int. 1990, 38, 167–184. [Google Scholar] [CrossRef] [PubMed]
  89. Perrone, R.D.; Steinman, T.I.; Beck, G.J.; Skibinski, C.I.; Royal, H.D.; Lawlor, M.; Hunsicker, L.G. Utility of radioisotopic filtration markers in chronic renal insufficiency: Simultaneous comparison of 125I-iothalamate, 169Yb-DTPA, 99mTc-DTPA, and inulin. Am. J. Kidney Dis. 1990, 16, 224–235. [Google Scholar] [CrossRef]
  90. Bostom, A.G.; Kronenberg, F.; Ritz, E. Predictive performance of renal function equations for patients with chronic kidney disease and normal serum creatinine levels. J. Am. Soc. Nephrol. 2002, 13, 2140–2144. [Google Scholar] [CrossRef] [PubMed]
  91. Shemesh, O.; Golbetz, H.; Kriss, J.P.; Myers, B.D. Limitations of creatinine as a filtration marker in glomerulopathic patients. Kidney Int. 1985, 28, 830–838. [Google Scholar] [CrossRef] [PubMed]
  92. Berg, K.J.; Gjellestad, A.; Nordby, G.; Rootwelt, K.; Djøseland, O.; Fauchald, P.; Mehl, A.; Narverud, J.; Talseth, T. Renal effects of trimethoprim in ciclosporin- and azathioprine-treated kidney-allografted patients. Nephron 1989, 53, 218–222. [Google Scholar] [CrossRef] [PubMed]
  93. Duncker, D.; Oswald, H.; Gardiwal, A.; Lüsebrink, U.; König, T.; Schreyer, H.; Klein, G. Stable cystatin C serum levels confirm normal renal function in patients with dronedarone-associated increase in serum creatinine. J. Cardiovasc. Pharmacol. Ther. 2013, 18, 109–112. [Google Scholar] [CrossRef] [PubMed]
  94. Hilbrands, L.B.; Artz, M.A.; Wetzels, J.F.; Koene, R.A. Cimetidine improves the reliability of creatinine as a marker of glomerular filtration. Kidney Int. 1991, 40, 1171–1176. [Google Scholar] [CrossRef] [PubMed]
  95. Rocci, M.L.; Vlasses, P.H.; Ferguson, R.K. Creatinine serum concentrations and H2-receptor antagonists. Clin. Nephrol. 1984, 22, 214–215. [Google Scholar] [PubMed]
  96. Mitchell, E.K. Flucytosine and false elevation of serum creatinine level. Ann. Intern. Med. 1984, 101, 278. [Google Scholar] [CrossRef] [PubMed]
  97. Saah, A.J.; Koch, T.R.; Drusano, G.L. Cefoxitin falsely elevates creatinine levels. JAMA 1982, 247, 205–206. [Google Scholar] [CrossRef] [PubMed]
  98. Molitch, M.E.; Rodman, E.; Hirsch, C.A.; Dubinsky, E. Spurious serum creatinine elevations in ketoacidosis. Ann. Intern. Med. 1980, 93, 280–281. [Google Scholar] [CrossRef] [PubMed]
  99. Miller, W.G.; Myers, G.L.; Ashwood, E.R.; Killeen, A.A.; Wang, E.; Thienpont, L.M.; Siekmann, L. Creatinine measurement: State of the art in accuracy and interlaboratory harmonization. Arch. Pathol. Lab. Med. 2005, 129, 297–304. [Google Scholar] [PubMed]
  100. Soldin, S.J.; Henderson, L.; Hill, J.G. The effect of bilirubin and ketones on reaction rate methods for the measurement of creatinine. Clin. Biochem. 1978, 11, 82–86. [Google Scholar] [CrossRef]
  101. Myers, G.L.; Miller, W.G.; Coresh, J.; Fleming, J.; Greenberg, N.; Greene, T.; Hostetter, T.; Levey, A.S.; Panteghini, M.; Welch, M.; et al. Recommendations for improving serum creatinine measurement: A report from the Laboratory Working Group of the National Kidney Disease Education Program. Clin. Chem. 2006, 52, 5–18. [Google Scholar] [CrossRef] [PubMed]
  102. Peake, M.; Whiting, M. Measurement of serum creatinine-current status and future goals. Clin. Biochem. Rev. 2006, 27, 173–184. [Google Scholar] [PubMed]
  103. Davenport, A.; Cholongitas, E.; Xirouchakis, E.; Burroughs, A.K. Pitfalls in assessing renal function in patients with cirrhosis-potential inequity for access to treatment of hepatorenal failure and liver transplantation. Nephrol. Dial. Transplant. 2011, 26, 2735–2742. [Google Scholar] [CrossRef] [PubMed]
  104. Delanghe, J.R.; Cobbaert, C.; Harmoinen, A.; Jansen, R.; Laitinen, P.; Panteghini, M. Focusing on the clinical impact of standardization of creatinine measurements: A report by the EFCC working group on creatinine standardization. Clin. Chem. Lab. Med. 2011, 49, 977–982. [Google Scholar] [CrossRef] [PubMed]
  105. Preiss, D.J.; Godber, I.M.; Lamb, E.J.; Dalton, R.N.; Gunn, I.R. The influence of a cooked-meat meal on estimated glomerular filtration rate. Ann. Clin. Biochem. 2007, 44, 35–42. [Google Scholar] [CrossRef] [PubMed]
  106. Pickering, J.W.; Ralib, A.M.; Endre, Z.H. Combining creatinine and volume kinetics identifies missed cases of acute kidney injury following cardiac arrest. Crit. Care 2013, 17, R7. [Google Scholar] [CrossRef] [PubMed]
  107. Conte, G.; Dal Canton, A.; Terribile, M.; Cianciaruso, B.; Di Minno, G.; Pannain, M.; Russo, D.; Andreucci, V.E. Renal handling of urea in subjects with persistent azotemia and normal renal function. Kidney Int. 1987, 32, 721–727. [Google Scholar] [CrossRef] [PubMed]
  108. Dossetor, J.B. Creatininemia versus uremia. Ann. Intern. Med. 1966, 65, 1287. [Google Scholar] [CrossRef] [PubMed]
  109. Uchino, S.; Bellomo, R.; Goldsmith, D. The meaning of the blood urea nitrogen/creatinine ratio in acute kidney injury. Clin. Kidney. J. 2012, 5, 187–191. [Google Scholar] [CrossRef]
  110. Möller, E.; McIntosh, J.F.; Van Slyke, D.D. Studies of urea excretion. II: Relationship between urine volume and the rate of urea excretion by normal adults. J. Clin. Investig. 1928, 6, 427–465. [Google Scholar] [CrossRef] [PubMed]
  111. Papadakis, M.A.; Arieff, A.I. Unpredictability of clinical evaluation of renal function in cirrhosis. Prospective study. Am. J. Med. 1987, 82, 945–952. [Google Scholar] [CrossRef]
  112. Macias, W.L.; Alaka, K.J.; Murphy, M.H.; Miller, M.E.; Clark, W.R.; Mueller, B.A. Impact of the nutritional regimen on protein catabolism and nitrogen balance in patients with acute renal failure. J. Parenter. Enteral Nutr. 1996, 20, 56–62. [Google Scholar] [CrossRef] [PubMed]
  113. Casaer, M.P.; Mesotten, D.; Schetz, M.R.C. Bench-to-bedside review: Metabolism and nutrition. Crit. Care 2008, 12, 222. [Google Scholar] [CrossRef] [PubMed]
  114. Keiserman, W. Effects of urea loading in patients with far advanced renal failure. Urology 1973, 1, 272. [Google Scholar] [CrossRef]
  115. Seabra, V.F.; Balk, E.M.; Liangos, O.; Sosa, M.A.; Cendoroglo, M.; Jaber, B.L. Timing of renal replacement therapy initiation in acute renal failure: A meta-analysis. Am. J. Kidney Dis. 2008, 52, 272–284. [Google Scholar] [CrossRef] [PubMed]
  116. Jamale, T.E.; Hase, N.K.; Kulkarni, M.; Pradeep, K.J.; Keskar, V.; Jawale, S.; Mahajan, D. Earlier-start versus usual-start dialysis in patients with community-acquired acute kidney injury: A randomized controlled trial. Am. J. Kidney Dis. 2013, 62, 1116–1121. [Google Scholar] [CrossRef] [PubMed]
  117. 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. Anestha 2014, 28, 557–563. [Google Scholar] [CrossRef] [PubMed]
  118. Wald, R.; Bagshaw, S.M. The timing of renal replacement therapy initiation in acute kidney injury. Crit. Care Med. 2014, 42, 1933–1934. [Google Scholar] [CrossRef] [PubMed]
  119. Karvellas, C.J.; Farhat, M.R.; Sajjad, I.; Mogensen, S.S.; Leung, A.A.; Wald, R.; Bagshaw, S.M. A comparison of early versus late initiation of renal replacement therapy in critically ill patients with acute kidney injury: A systematic review and meta-analysis. Crit. Care 2011, 15, R72. [Google Scholar] [CrossRef] [PubMed]
  120. Gaudry, S.; Hajage, D.; Schortgen, F.; Martin-Lefevre, L.; Ricard, J.; Dreyfuss, D. Comparison of two strategies for initiating renal replacement therapy in the ICU: Study protocol plan for a multicenter, randomized, controlled trial. Crit. Care 2015, 19, P299. [Google Scholar] [CrossRef]
  121. Jun, M.; Bellomo, R.; Cass, A.; Gallagher, M.; Lo, S.; Lee, J. Timing of renal replacement therapy and patient outcomes in the randomized evaluation of normal versus augmented level of replacement therapy study. Crit Care Med. 2014, 42, 1756–1765. [Google Scholar] [CrossRef] [PubMed]
  122. García-Fernández, N.; Pérez-Valdivieso, J.R.; Bes-Rastrollo, M.; Vives, M.; Lavilla, J.; Herreros, J.; Monedero, P.; GEDRCC. Timing of renal replacement therapy after cardiac surgery: A retrospective multicenter spanish cohort study. Blood Purif. 2011, 32, 104–111. [Google Scholar]
  123. Vaara, S.T.; Reinikainen, M.; Wald, R.; Bagshaw, S.M.; Pettila, V. Timing of RRT based on the presence of conventional indications. Clin. J. Am. Soc. Nephrol. 2014, 9, 1577–1585. [Google Scholar] [CrossRef] [PubMed]
  124. Leite, T.T.; Macedo, E.; Pereira, S.M.; Bandeira, S.R.; Pontes, P.H.; Garcia, A.S.; Militão, F.R.; Sobrinho, I.M.; Assunção, L.M.; Libório, A.B. Timing of renal replacement therapy initiation by AKIN classification system. Crit. Care 2013, 17, R62. [Google Scholar] [CrossRef] [PubMed]
  125. Wald, R.; Adhikari, N.K.J.; Smith, O.M.; Weir, M.A.; Pope, K.; Cohen, A.; Thorpe, K.; McIntyre, L.; Lamontagne, F.; Soth, M.; et al. Comparison of standard and accelerated initiation of renal replacement therapy in acute kidney injury. Kidney Int. 2015, 88, 1–8. [Google Scholar] [CrossRef] [PubMed]
  126. Zarbock, A.; Kellum, J.A. Timing of initiation of renal replacement therapy in critically ill patients with acute kidney injury-reply. JAMA 2016, 316, 1214. [Google Scholar] [CrossRef] [PubMed]
  127. Kashani, K.; Al-Khafaji, A.; Ardiles, T.; Artigas, A.; Bagshaw, S.M.; Bell, M.; Bihorac, A.; Birkhahn, R.; Cely, C.M.; Chawla, L.S.; et al. Discovery and validation of cell cycle arrest biomarkers in human acute kidney injury. Crit. Care 2013, 17, R25. [Google Scholar] [CrossRef] [PubMed]
  128. Bonventre, J.V.; Yang, L. Cellular pathophysiology of ischemic acute kidney injury. J. Clin. Investig. 2011, 121, 4210–4221. [Google Scholar] [CrossRef] [PubMed]
  129. Price, P.M.; Safirstein, R.L.; Megyesi, J. The cell cycle and acute kidney injury. Kidney Int. 2009, 76, 604–613. [Google Scholar] [CrossRef] [PubMed]
  130. Parikh, C.R.; Mansour, S.G. Perspective on clinical application of biomarkers in AKI. J. Am. Soc. Nephrol. 2017, 28, 1677–1685. [Google Scholar] [CrossRef] [PubMed]
  131. Sugahara, S.; Suzuki, H. Early start on continuous hemodialysis therapy improves survival rate in patients with acute renal failure following coronary bypass surgery. Hemodial. Int. 2004, 8, 320–325. [Google Scholar] [CrossRef] [PubMed]
  132. Durmaz, I.; Yagdi, T.; Calkavur, T.; Mahmudov, R.; Apaydin, A.Z.; Posacioglu, H.; Atay, Y.; Engin, C. Prophylactic dialysis in patients with renal dysfunction undergoing on-pump coronary artery bypass surgery. Ann. Thorac. Surg. 2003, 75, 859–864. [Google Scholar] [CrossRef]
  133. Bouman, C.S.C.; Oudemans-van Straaten, H.M.; Tijssen, J.G.P.; Zandstra, D.F.; Kesecioglu, J. Effects of early high-volume continuous venovenous hemofiltration on survival and recovery of renal function in intensive care patients with acute renal failure: A prospective, randomized trial. Crit. Care Med. 2002, 30, 2205–2211. [Google Scholar] [CrossRef] [PubMed]
  134. Bagshaw, S.M.; Uchino, S.; Bellomo, R.; Morimatsu, H.; Morgera, S.; Schetz, M.; Tan, I.; Bouman, C.; Macedo, E.; Gibney, N.; et al. Beginning and ending supportive therapy for the kidney (BEST Kidney) investigators timing of renal replacement therapy and clinical outcomes in critically ill patients with severe acute kidney injury. J. Crit Care 2009, 24, 129–140. [Google Scholar] [CrossRef] [PubMed]
  135. Liu, K.D. Timing of initiation of dialysis in critically ill patients with acute kidney injury. Clin. J. Am. Soc. Nephrol. 2006, 1, 915–919. [Google Scholar] [CrossRef] [PubMed]
  136. Ji, Q.; Mei, Y.; Wang, X.; Feng, J.; Cai, J.; Zhou, Y.; Sun, Y.; Xie, S.; Hu, D. Timing of continuous veno-venous hemodialysis in the treatment of acute renal failure following cardiac surgery. Heart Vessels 2011, 26, 183–189. [Google Scholar] [CrossRef] [PubMed]
  137. Carl, D.E.; Grossman, C.; Behnke, M.; Sessler, C.N.; Gehr, T.W.B. Effect of timing of dialysis on mortality in critically ill, septic patients with acute renal failure. Hemodial. Int. 2010, 14, 11–17. [Google Scholar] [CrossRef] [PubMed]
  138. Iyem, H.; Tavli, M.; Akcicek, F.; Büket, S. Importance of early dialysis for acute renal failure after an open-heart surgery. Hemodial. Int. 2009, 13, 55–61. [Google Scholar] [CrossRef] [PubMed]
  139. Shiao, C.C.; Wu, V.C.; Li, W.Y.; Lin, Y.F.; Hu, F.C.; Young, G.H.; Kuo, CC.; Kao, T.W.; Huang, D.M.; Chen, Y.M.; et al. Late initiation of renal replacement therapy is associated with worse outcomes in acute kidney injury after major abdominal surgery. Crit. Care 2009, 13, R171. [Google Scholar] [CrossRef] [PubMed]
  140. Manché, A.; Casha, A.; Rychter, J.; Farrugia, E.; Debono, M. Early dialysis in acute kidney injury after cardiac surgery. Interact. Cardiovasc. Thorac. Surg. 2008, 7, 829–832. [Google Scholar] [CrossRef] [PubMed]
  141. Andrade, L.; Cleto, S.; Seguro, A.C. Door-to-dialysis time and daily hemodialysis in patients with leptospirosis: Impact on mortality. Clin. J. Am. Soc. Nephrol. 2007, 2, 739–744. [Google Scholar] [CrossRef] [PubMed]
  142. Wu, V.C.; Ko, W.J.; Chang, H.W.; Chen, Y.S.; Chen, Y.W.; Chen, Y.M.; Hu, F.C.; Lin, Y.H.; Tsai, P.R.; Wu, K.D. Early renal replacement therapy in patients with postoperative acute liver failure associated with acute renal failure: Effect on postoperative outcomes. J. Am. Coll. Surg. 2007, 205, 266–276. [Google Scholar] [CrossRef] [PubMed]
  143. Piccinni, P.; Dan, M.; Barbacini, S.; Carraro, R.; Lieta, E.; Marafon, S.; Zamperetti, N.; Brendolan, A.; D’Intini, V.; Tetta, C.; et al. Early isovolaemic haemofiltration in oliguric patients with septic shock. Intensive Care Med. 2005, 32, 80–86. [Google Scholar] [CrossRef] [PubMed]
  144. Demirkilic, U.; Kuralay, E.; Yenicesu, M.; Caglar, K.; Oz, B.S.; Cingoz, F.; Gunay, C.; Yildirim, V.; Ceylan, S.; Arslan, M.; et al. Timing of replacement therapy for acute renal failure after cardiac surgery. J. Card. Surg. 2004, 19, 17–20. [Google Scholar] [CrossRef] [PubMed]
  145. Elahi, M.M.; Lim, M.Y.; Joseph, R.N.; Dhannapuneni, R.R.V.; Spyt, T.J. Early hemofiltration improves survival in post-cardiotomy patients with acute renal failure. Eur. J. Cardiothorac. Surg. 2004, 26, 1027–1031. [Google Scholar] [CrossRef] [PubMed]
  146. Gettings, L.G.; Reynolds, H.N.; Scalea, T. Outcome in post-traumatic acute renal failure when continuous renal replacement therapy is applied early vs. late. Intensive Care Med. 1999, 25, 805–813. [Google Scholar] [CrossRef] [PubMed]
  147. Cooper, B.A.; Branley, P.; Bulfone, L.; Collins, J.F.; Craig, J.C.; Fraenkel, M.B.; Harris, A.; Johnson, D.W.; Kesselhut, J.; Li, J.J.; et al. A randomized, controlled trial of early versus late initiation of dialysis. N. Engl. J. Med. 2010, 363, 609–619. [Google Scholar] [CrossRef] [PubMed]
  148. Porter, C.J.; Juurlink, I.; Bisset, L.H.; Bavakunji, R.; Mehta, R.L.; Devonald, M.A.J. A real-time electronic alert to improve detection of acute kidney injury in a large teaching hospital. Nephrol. Dial. Transplant. 2014, 29, 1888–1893. [Google Scholar] [CrossRef] [PubMed]
  149. Handler, S.M.; Kane-Gill, S.L.; Kellum, J.A. Optimal and early detection of acute kidney injury requires effective clinical decision support systems. Nephrol. Dial. Transplant. 2014, 29, 1802–1803. [Google Scholar] [CrossRef] [PubMed]
  150. Kirkendall, E.S.; Spires, W.L.; Mottes, T.A.; Schaffzin, J.K.; Barclay, C.; Goldstein, S.L. Development and performance of electronic acute kidney injury triggers to identify pediatric patients at risk for nephrotoxic medication-associated harm. Appl. Clin. Inform. 2014, 5, 313–333. [Google Scholar] [CrossRef] [PubMed]
  151. Perazella, M.A.; Coca, S.G. Three feasible strategies to minimize kidney injury in “incipient AKI”. Nat. Rev. Nephrol. 2013, 9, 484–490. [Google Scholar] [CrossRef] [PubMed]
  152. Mutter, T.C.; Ruth, C.A.; Dart, A.B. Hydroxyethyl starch (HES) versus other fluid therapies: Effects on kidney function. Cochrane Database Syst. Rev. 2013, CD007594. [Google Scholar] [CrossRef] [PubMed]
  153. Heung, M.; Wolfgram, D.F.; Kommareddi, M.; Hu, Y.; Song, P.X.; Ojo, A.O. Fluid overload at initiation of renal replacement therapy is associated with lack of renal recovery in patients with acute kidney injury. Nephrol. Dial. Transplant. 2012, 27, 956–961. [Google Scholar] [CrossRef] [PubMed]
  154. Ho, K.M.; Sheridan, D.J. Meta-analysis of frusemide to prevent or treat acute renal failure. BMJ 2006, 333, 420. [Google Scholar] [CrossRef] [PubMed]
  155. Brunkhorst, F.M.; Engel, C.; Bloos, F.; Meier-Hellmann, A.; Ragaller, M.; Weiler, N.; Moerer, O.; Gruendling, M.; Oppert, M.; Grond, S.; et al. Intensive insulin therapy and pentastarch resuscitation in severe sepsis. N. Engl. J. Med. 2008, 358, 125–139. [Google Scholar] [CrossRef] [PubMed]
  156. Kohli, H.S.; Bhaskaran, M.C.; Muthukumar, T.; Thennarasu, K.; Sud, K.; Jha, V.; Gupta, K.L.; Sakhuja, V. Treatment-related acute renal failure in the elderly: A hospital-based prospective study. Nephrol. Dial. Transplant. 2000, 15, 212–217. [Google Scholar] [CrossRef] [PubMed]
  157. Asfar, P.; Meziani, F.; Hamel, J.F.; Grelon, F.; Megarbane, B.; Anguel, N.; Mira, J.P.; Dequin, P.F.; Gergaud, S.; Weiss, N.; et al. High versus low blood-pressure target in patients with septic shock. N. Engl. J. Med. 2014, 370, 1583–1593. [Google Scholar] [CrossRef] [PubMed]
  158. Yeh, B.P.; Tomko, D.J.; Stacy, W.K.; Bear, E.S.; Haden, H.T.; Falls, W.F. Factors influencing sodium and water excretion in uremic man. Kidney Int. 1975, 7, 103–110. [Google Scholar] [CrossRef] [PubMed]
  159. Finn, W.F. Nephron heterogeneity in polyuric acute renal failure. J. Lab. Clin. Med. 1981, 98, 21–29. [Google Scholar] [PubMed]
  160. Bagshaw, S.M.; Delaney, A.; Haase, M.; Ghali, W.A.; Bellomo, R. Loop diuretics in the management of acute renal failure: A systematic review and meta-analysis. Crit. Care Resusc. 2007, 9, 60–68. [Google Scholar] [PubMed]
  161. Bagshaw, S.M.; Bellomo, R.; Kellum, J.A. Oliguria, volume overload, and loop diuretics. Crit. Care Med. 2008, 36, S172–S178. [Google Scholar] [CrossRef] [PubMed]
  162. Ejaz, A.A.; Mohandas, R. Are diuretics harmful in the management of acute kidney injury? Curr. Opin. Nephrol. Hypertens. 2014, 23, 155–160. [Google Scholar] [CrossRef] [PubMed]
  163. Van der Voort, P.H.J.; Boerma, E.C.; Koopmans, M.; Zandberg, M.; de Ruiter, J.; Gerritsen, R.T.; Egbers, P.H.M.; Kingma, W.P.; Kuiper, M.A. Furosemide does not improve renal recovery after hemofiltration for acute renal failure in critically ill patients: A double blind randomized controlled trial. Crit. Care Med. 2009, 37, 533–538. [Google Scholar] [CrossRef] [PubMed]
  164. Mehta, R.L. Diuretics, mortality, and nonrecovery of renal function in acute renal failure. JAMA 2002, 288, 2547–2553. [Google Scholar] [CrossRef] [PubMed]
  165. Wu, V.C.; Lai, C.F.; Shiao, C.C.; Lin, Y.F.; Wu, P.C.; Chao, C.T.; Hu, F.C.; Huang, T.M.; Yeh, Y.C.; Tsai, I.J.; et al. Effect of diuretic use on 30-day postdialysis mortality in critically ill patients receiving acute dialysis. PLoS ONE 2012, 7, e30836. [Google Scholar] [CrossRef] [PubMed]
  166. Wang, N.; Jiang, L.; Zhu, B.; Wen, Y.; Xi, X.M. Fluid balance and mortality in critically ill patients with acute kidney injury: A multicenter prospective epidemiological study. Crit. Care 2015, 19, 1–11. [Google Scholar] [CrossRef] [PubMed]
  167. Conger, J.D. Does hemodialysis delay recovery from acute renal failure? Semin. Dial. 1990, 3, 146–148. [Google Scholar] [CrossRef]
  168. Palevsky, P.M.; Baldwin, I.; Davenport, A.; Goldstein, S.; Paganini, E. Renal replacement therapy and the kidney: Minimizing the impact of renal replacement therapy on recovery of acute renal failure. Curr. Opin. Crit. Care 2005, 11, 548–554. [Google Scholar] [CrossRef] [PubMed]
  169. Adams, P.L.; Adams, F.F.; Bell, P.D.; Navar, L.G. Impaired renal blood flow autoregulation in ischemic acute renal failure. Kidney Int. 1980, 18, 68–76. [Google Scholar] [CrossRef] [PubMed]
  170. Malek, M.; Nematbakhsh, M. Renal ischemia/reperfusion injury; from pathophysiology to treatment. J. Renal Inj. Prev. 2014, 4, 1–8. [Google Scholar]
  171. Morrell, E.D.; Kellum, J.A.; Hallows, K.R.; Pastor-Soler, N.M. Epithelial transport during septic acute kidney injury. Nephrol. Dial. Transplant. 2014, 29, 1312–1319. [Google Scholar] [CrossRef] [PubMed]
  172. Singh, P.; Okusa, M.D. The role of tubuloglomerular feedback in the pathogenesis of acute kidney injury. Contrib. Nephrol. 2011, 174, 12–21. [Google Scholar] [PubMed]
  173. Preising, C.; Schneider, R.; Bucher, M.; Gekle, M.; Sauvant, C. Regulation of expression of renal organic anion transporters OAT1 and OAT3 in a model of ischemia/reperfusion injury. Cell Physiol. Biochem. 2015, 37, 1–13. [Google Scholar] [CrossRef] [PubMed]
  174. Schneider, R.; Meusel, M.; Betz, B.; Held, C.; Möller-Ehrlich, K.; Büttner-Herold, M.; Wanner, C.; Gekle, M.; Sauvant, C. Oat1/3 restoration protects against renal damage after ischemic AKI. Am. J. Physiol. Renal Physiol. 2015, 308, F198–F208. [Google Scholar] [CrossRef] [PubMed]
  175. Bergström, J.; Asaba, H.; Fürst, P.; Oulès, R. Dialysis, Ultrafiltration, and blood pressure. Blood Purif. 2006, 24, 222–229. [Google Scholar] [CrossRef] [PubMed]
  176. Henrich, W.L.; Woodard, T.D.; Blachley, J.D.; Gomez-Sanchez, C.; Pettinger, W.; Cronin, R.E. Role of osmolality in blood pressure stability after dialysis and ultrafiltration. Kidney Int. 1980, 18, 480–488. [Google Scholar] [CrossRef] [PubMed]
  177. Swartz, R.D.; Somermeyer, M.G.; Hsu, C.H. Preservation of plasma volume during hemodialysis depends on dialysate osmolality. Am. J. Nephrol. 1982, 2, 189–194. [Google Scholar] [CrossRef] [PubMed]
  178. Kimura, G.; Irie, A.; Kuroda, K.; Kojima, S.; Satani, M. Absence of transcellular fluid shift during haemofiltration. Proc. Eur. Dial. Transplant. Assoc. 1980, 17, 192–196. [Google Scholar] [PubMed]
  179. Schuenemann, B.; Borghardt, J.; Falda, Z.; Jacob, I.; Kramer, P.; Kraft, B.; Quellhorst, E. Reactions of blood pressure and body spaces to hemofiltration treatment. Trans. Am. Soc. Artif. Intern. Organs 1978, 24, 687–689. [Google Scholar] [PubMed]
  180. Kovacs, B.; Sullivan, K.J.; Hiremath, S.; Patel, R.V. The effect of sustained low efficient dialysis versus continuous renal replacement therapy on renal recovery after acute kidney injury in the intensive care unit: A systematic review and meta-analysis. Nephrology 2017, 22, 343–353. [Google Scholar] [CrossRef] [PubMed]
  181. Truche, A.S.; Darmon, M.; Bailly, S.; Clec’h, C.; Dupuis, C.; Misset, B.; Azoulay, E.; Schwebel, C.; Bouadma, L.; Kallel, H.; et al. Continuous renal replacement therapy versus intermittent hemodialysis in intensive care patients: Impact on mortality and renal recovery. Intensive Care Med. 2016, 42, 1408–1417. [Google Scholar] [CrossRef] [PubMed]
  182. Zhang, L.; Yang, J.; Eastwood, G.M.; Zhu, G.; Tanaka, A.; Bellomo, R. Extended daily dialysis versus continuous renal replacement therapy for acute kidney injury: A meta-analysis. Am. J. Kidney Dis. 2015, 66, 322–330. [Google Scholar] [CrossRef] [PubMed]
  183. Schwenger, V.; Weigand, M.A.; Hoffmann, O.; Dikow, R.; Kihm, L.P.; Seckinger, J.; Miftari, N.; Schaier, M.; Hofer, S.; Haar, C.; et al. Sustained low efficiency dialysis using a single-pass batch system in acute kidney injury—A randomized interventional trial: The renal replacement therapy study in intensive care unit patients. Crit. Care 2012, 16, R140. [Google Scholar] [CrossRef] [PubMed]
  184. Sun, Z.; Ye, H.; Shen, X.; Chao, H.; Wu, X.; Yang, J. Continuous venovenous hemofiltration versus extended daily hemofiltration in patients with septic acute kidney injury: A retrospective cohort study. Crit. Care 2014, 18, 1–9. [Google Scholar] [CrossRef] [PubMed]
  185. Wald, R.; Shariff, S.Z.; Adhikari, N.K.J.; Bagshaw, S.M.; Burns, K.E.A.; Friedrich, J.O.; Garg, A.X.; Harel, Z.; Kitchlu, A.; Ray, J.G. The association between renal replacement therapy modality and long-term outcomes among critically ill adults with acute kidney injury: A retrospective cohort study. Crit. Care Med. 2014, 42, 868–877. [Google Scholar] [CrossRef] [PubMed]
  186. Schneider, A.G.; Bellomo, R.; Bagshaw, S.M.; Glassford, N.J.; Lo, S.; Jun, M.; Cass, A.; Gallagher, M. Choice of renal replacement therapy modality and dialysis dependence after acute kidney injury: A systematic review and meta-analysis. Intensive Care Med. 2013, 39, 987–997. [Google Scholar] [CrossRef] [PubMed]
  187. Schefold, J.C.; von Haehling, S.; Pschowski, R.; Bender, T.O.; Berkmann, C.; Briegel, S.; Hasper, D.; Jörres, A. The effect of continuous versus intermittent renal replacement therapy on the outcome of critically ill patients with acute renal failure (CONVINT): A prospective randomized controlled trial. Crit. Care 2014, 18, 1–11. [Google Scholar] [CrossRef] [PubMed]
  188. Friedrich, J.O.; Wald, R.; Bagshaw, S.M.; Burns, K.E.; Adhikari, N.K. Hemofiltration compared to hemodialysis for acute kidney injury: Systematic review and meta-analysis. Crit. Care 2012, 16, R146. [Google Scholar] [CrossRef] [PubMed]
  189. Nash, D.M.; Przech, S.; Wald, R.; O'Reilly, D. Systematic review and meta-analysis of renal replacement therapy modalities for acute kidney injury in the intensive care unit. J. Crit. Care 2017, 41, 138–144. [Google Scholar] [CrossRef] [PubMed]
  190. Schulman, G.; Fogo, A.; Gung, A.; Badr, K.; Hakim, R. Complement activation retards resolution of acute ischemic renal failure in the rat. Kidney Int. 1991, 40, 1069–1074. [Google Scholar] [CrossRef] [PubMed]
  191. Cheung, A.K. Biocompatibility of hemodialysis membranes. J. Am. Soc. Nephrol. 1990, 1, 150–161. [Google Scholar] [PubMed]
  192. Hakim, R.M. Clinical implications of hemodialysis membrane biocompatibility. Kidney Int. 1993, 44, 484–494. [Google Scholar] [CrossRef] [PubMed]
  193. Hakim, R.M.; Wingard, R.L.; Parker, R.A. Effect of the dialysis membrane in the treatment of patients with acute renal failure. N. Engl. J. Med. 1994, 331, 1338–1342. [Google Scholar] [CrossRef] [PubMed]
  194. Schiffl, H.; Lang, S.M.; König, A.; Strasser, T.; Haider, M.C.; Held, E. Biocompatible membranes in acute renal failure: Prospective case-controlled study. Lancet 1994, 344, 570–572. [Google Scholar] [CrossRef]
  195. Himmelfarb, J.; Tolkoff Rubin, N.; Chandran, P.; Parker, R.A.; Wingard, R.L.; Hakim, R. A multicenter comparison of dialysis membranes in the treatment of acute renal failure requiring dialysis. J. Am. Soc. Nephrol. 1998, 9, 257–266. [Google Scholar] [PubMed]
  196. Subramanian, S.; Venkataraman, R.; Kellum, J.A. Influence of dialysis membranes on outcomes in acute renal failure: A meta-analysis. Kidney Int. 2002, 62, 1819–1823. [Google Scholar] [CrossRef] [PubMed]
  197. Bozza, F.A.; Salluh, J.I.; Japiassu, A.M.; Soares, M.; Assis, E.F.; Gomes, R.N.; Bozza, M.T.; Castro-Faria-Neto, H.C.; Bozza, P.T. Cytokine profiles as markers of disease severity in sepsis: A multiplex analysis. Crit. Care 2007, 11, R49. [Google Scholar] [CrossRef] [PubMed]
  198. Clermont, G.; Acker, C.G.; Angus, D.C.; Sirio, C.A.; Pinsky, M.R.; Johnson, J.P. Renal failure in the ICU: Comparison of the impact of acute renal failure and end-stage renal disease on ICU outcomes. Kidney Int. 2002, 62, 986–996. [Google Scholar] [CrossRef] [PubMed]
  199. Simmons, E.M.; Himmelfarb, J.; Sezer, M.T.; Chertow, G.M.; Mehta, R.L.; Paganini, E.P.; Soroko, S.; Freedman, S.; Becker, K.; Spratt, D.; et al. Plasma cytokine levels predict mortality in patients with acute renal failure. Kidney Int. 2004, 65, 1357–1365. [Google Scholar] [CrossRef] [PubMed]
  200. Kellum, J.A.; Kong, L.; Fink, M.P.; Weissfeld, L.A.; Yealy, D.M.; Pinsky, M.R.; Fine, J.; Krichevsky, A.; Delude, R.L.; Angus, D.C. Understanding the inflammatory cytokine response in pneumonia and sepsis: Results of the genetic and inflammatory markers of sepsis (GenIMS) study. Arch. Intern. Med. 2007, 167, 1655–1663. [Google Scholar] [CrossRef] [PubMed]
  201. Vandissel, J.; Vanlangevelde, P.; Westendorp, R.; Kwappenberg, K.; Frölich, M. Anti-inflammatory cytokine profile and mortality in febrile patients. Lancet 1998, 351, 950–953. [Google Scholar] [CrossRef]
  202. Nakamura, M.; Oda, S.; Sadahiro, T.; Hirayama, Y.; Watanabe, E.; Tateishi, Y.; Nakada, T.A.; Hirasawa, H. Treatment of severe sepsis and septic shock by CHDF using a PMMA membrane hemofilter as a cytokine modulator. Contrib. Nephrol. 2010, 166, 73–82. [Google Scholar] [PubMed]
  203. Galli, F.; Benedetti, S.; Floridi, A.; Canestrari, F.; Piroddi, M.; Buoncristiani, E.; Buoncristiani, U. Glycoxidation and inflammatory markers in patients on treatment with PMMA-based protein-leaking dialyzers. Kidney Int. 2005, 67, 750–759. [Google Scholar] [CrossRef] [PubMed]
  204. Mayeur, N.; Rostaing, L.; Nogier, M.B.; Jaafar, A.; Cointault, O.; Kamar, N.; Conil, J.M.; Fourcade, O.; Lavayssiere, L. Kinetics of plasmatic cytokines and cystatin C during and after hemodialysis in septic shock-related acute renal failure. Crit. Care 2010, 14, R115–R119. [Google Scholar] [CrossRef] [PubMed]
  205. Nakada, T.A.; Oda, S.; Matsuda, K.I.; Sadahiro, T.; Nakamura, M.; Abe, R.; Hirasawa, H. Continuous hemodiafiltration with PMMA hemofilter in the treatment of patients with septic shock. Mol. Med. 2008, 14, 257–263. [Google Scholar] [CrossRef] [PubMed]
  206. Atan, R.; Crosbie, D.; Bellomo, R. Techniques of extracorporeal cytokine removal: A systematic review of the literature. Blood Purif. 2012, 33, 88–100. [Google Scholar] [CrossRef] [PubMed]
  207. Weidenbusch, M.; Rodler, S.; Anders, H.J. Interleukin-22 in kidney injury and regeneration. Am. J. Physiol. Ren. Physiol. 2015, 308, F1041–F1046. [Google Scholar] [CrossRef] [PubMed]
  208. Xu, M.J.; Feng, D.; Wang, H.; Guan, Y.; Yan, X.; Gao, B. IL-22 ameliorates renal ischemia-reperfusion injury by targeting proximal tubule epithelium. J. Am. Soc. Nephrol. 2014, 25, 967–977. [Google Scholar] [CrossRef] [PubMed]
  209. Haase, M.; Bellomo, R.; Baldwin, I.; Haase-Fielitz, A.; Fealy, N.; Davenport, P.; Morgera, S.; Goehl, H.; Storr, M.; Boyce, N.; et al. Hemodialysis membrane with a high-molecular-weight cutoff and cytokine levels in sepsis complicated by acute renal failure: A phase 1 randomized trial. Am. J. Kidney Dis. 2007, 50, 296–304. [Google Scholar] [CrossRef] [PubMed]
  210. Honore, P.M.; Jacobs, R.; Joannes-Boyau, O.; De Regt, J.; De Waele, E.; Van Gorp, V.; Boer, W.; Verfaillie, L.; Spapen, H.D. Newly designed CRRT membranes for sepsis and SIRS-a pragmatic approach for bedside intensivists summarizing the more recent advances: A systematic structured review. ASAIO J. 2013, 59, 99–106. [Google Scholar] [CrossRef] [PubMed]
  211. Kogelmann, K.; Jarczak, D.; Scheller, M.; Drüner, M. Hemoadsorption by CytoSorb in septic patients: A case series. Crit. Care 2017, 21, 74. [Google Scholar] [CrossRef] [PubMed]
Figure 1. Algorithm for the initiation of renal replacement therapy (“Heidelberg Standard”) [74,75]. AKI, Acute kidney injury; BUN, Blood urea nitrogen; FO, Fluid overload; FiO2, Fractional inspired oxygen; K+, Potassium; O2, Oxygen; RRT, Renal replacement therapy. a Unexplained decline in mental status, nausea, vomiting, bleedings due to thrombocytophatia, pericarditis, pruritus. b RRT might be beneficial despite unstable hemodynamics, especially in cardiac decompensation or critical O2 demand. An individual risk-benefit analysis is mandatory.
Figure 1. Algorithm for the initiation of renal replacement therapy (“Heidelberg Standard”) [74,75]. AKI, Acute kidney injury; BUN, Blood urea nitrogen; FO, Fluid overload; FiO2, Fractional inspired oxygen; K+, Potassium; O2, Oxygen; RRT, Renal replacement therapy. a Unexplained decline in mental status, nausea, vomiting, bleedings due to thrombocytophatia, pericarditis, pruritus. b RRT might be beneficial despite unstable hemodynamics, especially in cardiac decompensation or critical O2 demand. An individual risk-benefit analysis is mandatory.
Ijms 18 01387 g001
Table 1. AKI staging by Kidney Disease Improving Global Outcomes (KDIGO) 2012 [29].
Table 1. AKI staging by Kidney Disease Improving Global Outcomes (KDIGO) 2012 [29].
AKIStage 1Stage 2Stage 3
Serum creatinineI: 1.5–1.9 times baseline a
II: ≥0.3 mg/dL increase within 48 h
I: 2.0–2.9 times baseline aI: ≥3 times baseline a
II: Increase ≥4 mg/dL
III: Initiation of RRT
Urine outputIII: <0.5 mL/kg/h for 6–12 hII: <0.5 mL/kg/h for ≥12 hIV: <0.3 mL/kg/h for ≥24 h
V: Anuria ≥12 h
AKI, Acute kidney injury; RRT, Renal replacement therapy; a SCr, Rise within seven days.
Table 2. Overview of promising “renal damage” biomarkers [39,40,41,42,43,44].
Table 2. Overview of promising “renal damage” biomarkers [39,40,41,42,43,44].
“Renal Damage” Biomarkers
“Indicate renal damage at a certain time point and give insights in heterogeneous AKI pathophysiology”
Molecular WeightOriginKineticsEvidence
NGAL
25 kDathick ascending limb and collecting ductsPeak approximately 6 h after injury
Detectable 3 h after injury
Sustained elevation up to 5 days
Reno-protective and anti-apoptotic
Bind to iron-siderophore complexes
Bacteriostatic agent
Iron-trafficking in developing renal epithelium
Induces tubulogenesis in nephrogenesis
KIM-1
38.7 kDaProliferating, dedifferentiated epithelial cells in proximal tubulePeak 48 h (2–3 days) after injuryReno-protective
Confers kidney cells to phagocytic cell type
Promote phagocytosis, role in tubular regeneration and renal recovery
Distinguish period of injury and recovery
IL-18
22 kDaPredominantly immune cellsPeak 12–18 h after injury
First detection within 6 h after injury
Promotes renal injury
Promotes inflammation via NF-κB, release of TNFα, iNOS and chemokines
L-FABP
14 kDaPredominantly proximal tubulePeak within 6 h after injuryReno-protective
Antioxidant
Gene induction by hypoxia = marker for renal hypoxia protection from reactive oxygen species promotes metabolism of fatty acids
TIMP-2
24 kDaProximal and distal tubule, predominantly distalPeak probably within 12–24 h after injuryReno-protective and pro-recovery role
Predicts AKI KDIGO stage 2–3 within 12 h
Induces G1 cell cycle arrest prevents cell death role in nephrogenesis special role not fully understood
IGFBP-7
29 kDaIn AKI proximal and distal tubule, predominantly proximal
Ubiquitously expressed
Peak probably within 12–24 h after injuryReno-protective by inducing G1-cell cycle arrest
Potentially impairs renal perfusion and recovery
Predicts AKI KDIGO stage 2–3 within 12 h
G1-cell cycle arrest marker
Known as tumor suppressor and regulator of cellular senescence
Potential deleterious effect as IGF-1 receptor antagonist
IFGBP-7, Insulin-like growth factor-binding protein-7; iNOS, Inducible nitric oxide synthase, IL 18, Interleukin 18 kDa; KIM-1, Kidney injury molecule-1; L-FABP, Liver-type fatty acid-binding protein; TIMP-2, Tissue inhibitor of metalloprotease-2; TNFα, Tumor necrosis factor alpha.
Table 3. Confounders of creatinine interpretation.
Table 3. Confounders of creatinine interpretation.
Rise in CreatinineFall in Creatinine
Acute rise in creatinine:Acute fall or attenuated rise in creatinine:
  • Dietary creatine/meat intake [105]
  • Enhanced creatinine formation
    Rhabdomyolysis [86,87]
  • Decreased GFR
    AKI [77]
  • Reduced tubular secretion [88,89,90,91]
    Trimethoprim, cimetidine, ranitidine, dronedarone [49,92,93,94,95]
  • Reduced creatinine formation
    In sepsis [81]
    Acute liver failure [80]
  • Increased volume of distribution [48,82,83,84,106]
    Acute fluid overload
Chronic creatinine elevation:Chronic reduction in creatinine:
  • Enhanced creatinine formation [76]
    Afro-American ethnicity
    Muscular body habitus
  • Decreased GFR
    CKD
  • Low dietary protein intake [79]
  • Reduced creatinine formation/low muscle mass/catabolic metabolism [49,76,78,79]
    Amputation
    Female sex, old age
    Muscle wasting
    Critical illness, malnutrition
    Insufficient protein supply
    Immobilization
    Liver cirrhosis
False creatinine elevation:False reduction in creatinine:
  • Jaffé assay
    Hyperglycemia & diabetic ketoacidosis [98,99,100,101]
    Delayed centrifugation
    Hemolysis [77]
    Drugs (cefoxitin, flucytosin, dopamine) [96,97,103]
    Ig M gammopathy, uric acid [77]
  • Enzymatic assay
    High total protein, lidocaine [77]
  • Jaffé assay
    Hyperbilirubinemia [80,102,104]
  • Enzymatic assay
    Hyperbilirubinemia [80,102,104]
AKI, Acute kidney injury; CKD, Chronic kidney disease; GFR, Glomerular filtration rate.
Table 4. Overview of relevant studies investigating the timing of renal replacement therapy after 1990.
Table 4. Overview of relevant studies investigating the timing of renal replacement therapy after 1990.
AuthorStudy DesignPatients Early/LatePurposed Early CriteriaPurposed Late CriteriaCutoff before Early RRTCutoff before Late RRTMortality Early/Late
Gaudry et al., 2016 [74]RCT311/308After randomization + AKI Stage IIIHyperkalemia > 6 mmol/L, metabolic acidosis pH < 7.15, pulmonary edema > 5 L O2, BUN > 112 mg/dL, Oliguria >72 hBUN 52 mg/dL
SCr 3.27 mg/dL
BUN 90 mg/dL
SCr 5.33 mg/dL
49%/50%
(p = 0.790)
Zarbock et al., 2016 [126]RCT112/119Within 8 h of KDIGO stage 2 diagnosisWithin 12 h of stage 3 diagnosisBUN 38.5 mg/dL
SCr 1.5 mg/dL
BUN 47.5 mg/dL
2.4 mg/dL
39%/55%
(p = 0.030)
Wald et al., 2015 [125]RCT48/33Within 12 h after fulfilling study criteriaPotassium > 6 mmol/L, bicarbonate < 10 mmol/L, Horowitz < 200+ infiltrates X-rayUrea 115.9 mg/dL
SCr 3.68 mg/dL
Urea 161.6 mg/dL
SCr 4.57 mg/dL
38%/37%
(p = 0.920)
Jamale et al., 2013 [116]RCT102/106BUN > 70 mg/dL or SCr > 7 mg/dLClinically indicated or jugged by nephrologistBUN > 71.7 mg/dL
SCr > 7.4 mg/dL
BUN 100.9 mg/dL
SCr 10.4 mg/dL
21%/12%
(p = 0.200)
Sugahara et al., 2004 [131]RCT14/143h after UO < 30 mL/h2 h after UO < 20 mL/hSCr 2.9 mg/dLSCr 3.0 mg/dLSurvival 86%/14%,
(p = 0.010)
Durmaz et al., 2003 [132]RCT21/2310% increase of SCr after surgery50% increase or UO < 400 mL/24 hBUN 53.7 mg/dL
SCr 3.1 mg/dL
BUN 65.0 mg/dL
SCr 4.3 mg/dL
4.7%/ 0%
(p = 0.048)
Bouman et al., 2002 [133]RCT35/36within 12 h: UO < 30 mL/h and 3 h CrCl < 20 mL/minUrea > 40 mmol/L or K > 6.5 mmol/L or severe pulmonary edemaUrea 17.1 mmol/LUrea 37.4 mmol/LSurvival 67%/75%
(p = 0.800)
Vaara et al., 2014 [123]Prospective cohort105/134RRT without classic indications = pre-emptiveClassic RRT indicationsUrea 19.1 mmol/L
SCr 2.6 mg/dL
Urea 23.2 mmol/L
SCr 3.7 mg/dL
27%/49%
(p = 0.010)
Leite et al., 2013 [124]Prospective cohort64/86<24 h after AKIN 3≥24 h after AKIN 3Urea 100.1 mg/dL
SCr 2.7 mg/dL
Urea 108.2 mg/dL
SCr 2.8 mg/dL
51%/82%
(p = 0.002)
Bagshaw et al., 2009 [134]Prospective cohort618/619
618/618
Median Urea of all patients
Median SCr of all patients
Urea < 24.2 mmol/L
SCr < 3.5 mg/dL
Urea >24.2 mmol/L
SCr >3.5 mg/dL
62%/59%
(p < 0.001)
Liu et al., 2006 [135]Prospective cohort122/121BUN ≤ 76 mg/dLBUN > 76 mg/dLBUN 47 mg/dL
SCr 3.4 mg/dL
BUN 115 mg/dL
SCr 4.7 mg/dL
Survival 65%/59%
(p = 0.090)
Gaudry et al., 2015 [120]Retrospective cohort34/27UO < 100 mL/8 h and no response to 50 mg furosemideSCr > 5 mg/dL or K >5.5 mEq/L irrespective of UONRNR24%/56%
(p = 0.016)
Jun et al., 2014 [121]Retrospective cohortI: 109
II: 110
III: 109
IV: 111
Time between meeting Rifle I and Randomization (=CRRT)
I: <7.1 h
II: ≥7.1 to 17.6 h
III: ≥17.6 to 46 h
IV: ≥46 h
I: urea 103.3 mg/dL, SCr 2.97 mg/dL (reference group)
II: urea 102.7 mg/dL, SCr 2.81 mg/dL
III: urea 124.7 mg/dL, SCr 3.59 mg/dL
IV: urea 173 mg/dL, SCr 3.75 mg/dL
I: 36%
II: 39%
III: 37%
IV: 40%
(p = 0.923)
Fernandez et al., 2011 [9]Retrospective cohort101/102Within first 3 days after surgeryAfter the third dayNRNR53%/80%
(p < 0.001)
Ji et al., 2011 [136]Retrospective cohort34/24Within 12 h UO ≤ 0.5 mg/kg/h after surgery + 50% increase in baseline of crea and urea12 h after the onset of early criteriaBUN 60.8 mg/dL
SCr 2.8 mg/dL
BUN 93.6 mg/dL
SCr 4.5 mg/dL
9%/38%
(p = 0.020)
Carl et al., 2010 [137]Retrospective cohort85/62BUN < 100 mg/dLBUN ≥ 100 mg/dLBUN 66 mg/dL
SCr 5 mg/dL
BUN 137 mg/dL
SCr 5.8 mg/dL
52%/68%
(p = NR)
Iyem et al., 2009 [138]Retrospective cohort95/90UO ≤ 0.5 mL/kg/h after surgery and 50% increase of baseline crea and urea48 h after the onset of early criteriaBUN 54.6 mg/dL
SCr 2.1 mg/dL
BUN 68.2 mg/dL
SCr 2.9 mg/dL
5%/7%
(p = NR, reported as not significant)
Shiao et al., 2009 [139]Retrospective cohort51/47RIFLE RiskRIFLE Injury/FailureBUN 68.8 mg/dL
SCr 3.3 mg/dL
BUN 81.9 mg/dL
SCr 3.8 mg/dL
43%/75%
(p = 0.002)
Manche et al., 2008 [140]Retrospective cohort56/15HyperkaliemiaUO <0.5 mL/kg/hUrea 14.4 mmol/L
SCr 2.64 mg/dL
Urea 35.2 mmol/L
SCr 4.56 mg/dL
Survival 75%/13%
(p < 0.001)
Andrade et al., 2007 [141]Retrospective cohort18/15On admission24 hUrea 107 mg/dLUrea 153 mg/dL17%/67%
(p = 0.010)
Wu et al., 2007 [142]Retrospective cohort54/26BUN < 80 mg/dLBUN > 80 mg/dLBUN 46.2 mg/dL
SCr 2.9 mg/dL
BUN 118.8 mg/dL
Scr 4.7 mg/dL
63%/85%
(p = 0.040)
Piccinni et al., 2005 [143]Retrospective cohort40/40Within 12 h after admission and diagnosis of septic shockClassic RRT indicationsBUN 120 mg/dL
SCr 1.8 mg/dL
BUN 110 mg/dL
SCr 1.7 mg/dL
Survival 55%/27%
(p = 0.005)
Demirkilic et al., 2004 [144]Retrospective cohort27/34UO < 100 mL/8 h despite 50 mg furosemideSCr > 5 mg/dL or K > 5.5 mmol/LNRNR24%/56%
(p = 0.016)
Elahi et al., 2004 [145]Retrospective cohort28/36UO < 100 mL/8 h
despite furosemide
Urea ≥ 30 mmol/L, Crea ≥ 250 mmol/L or K ≥ 6.5 mmol/LUrea 23.9 mg/dL
SCr 3.7 mg/dL
Urea 26.8 mg/dL
SCr 4.3 mg/dL
43%/22%
(p = < 0.050)
Gettings et al. 1999 [146]Retrospective cohort51/49BUN < 60 mg/dLBUN ≥ 60 mg/dLBUN 43 mg/dL
SCr 2.69 mg/dL
SCr 5.73 mg/dL a
BUN 94 mg/dL
SCr 3.59 mg/dL
SCr 6.5mg/dL a
Survival
39%/20%
(p = 0.041)
BUN, Blood urea nitrogen; d, Days; NR, Not reported; p-value, ≤0.05 statistical significance; RRT, Renal replacement therapy; RCT, Randomized controlled trial; UO, Urine output. a Patients with rhabdomyolysis.
Table 5. Non-dialytic management of acute kidney injury.
Table 5. Non-dialytic management of acute kidney injury.
StrategyTherapeutic Measures
Early AKI recognition [148,149,150]Remove obstruction in post-renal AKI
Appropriate fluid removal in pre-renal AKI
Avoidance of contrast agents and nephrotoxins
Enhanced AKI monitoring [148,149,150]Monitoring renal function parameter, electrolytes and urine output
Avoidance of nephrotoxines [148,149,150]Check medication
Discontinue nephrotoxic drugs
Appropriate intravenous fluid administration [151,152]Avoid sodium- and chloride-rich solution
Avoid hydroxyethyl starches
Use balanced electrolyte solutions
Preventing fluid overload/hyperkaliemia [75,151,153,154]Appropriate use of diuretics
Use of cation exchanger and loop diuretics
Cautious fluid administration
Low salt diet
Limiting potassium and phosphate intakeLow potassium and phosphate diet
Appropriate parenteral nutrition
Avoid potassium and phosphate-rich intravenous solutions or oral supplements
Optimization of renal perfusion pressure [155,156,157]Mean arterial pressure ≥ 65 or ≥ 80–85 mmHg in patients with chronic hypertension
Fluid administration
Use of catecholamines
Recognize and avoid azotemiaCheck for BUN/urea to SCr dissociation
Exclude low SCr production (muscle wasting, etc.)
Avoid excessive, nutritional protein supply
Evaluate metabolic status (catabolic vs. anabolic)
Check for gastrointestinal bleeding or steroid therapy
AKI, Acute kidney injury; BUN, Blood urea nitrogen.

Share and Cite

MDPI and ACS Style

Nusshag, C.; Weigand, M.A.; Zeier, M.; Morath, C.; Brenner, T. Issues of Acute Kidney Injury Staging and Management in Sepsis and Critical Illness: A Narrative Review. Int. J. Mol. Sci. 2017, 18, 1387. https://doi.org/10.3390/ijms18071387

AMA Style

Nusshag C, Weigand MA, Zeier M, Morath C, Brenner T. Issues of Acute Kidney Injury Staging and Management in Sepsis and Critical Illness: A Narrative Review. International Journal of Molecular Sciences. 2017; 18(7):1387. https://doi.org/10.3390/ijms18071387

Chicago/Turabian Style

Nusshag, Christian, Markus A. Weigand, Martin Zeier, Christian Morath, and Thorsten Brenner. 2017. "Issues of Acute Kidney Injury Staging and Management in Sepsis and Critical Illness: A Narrative Review" International Journal of Molecular Sciences 18, no. 7: 1387. https://doi.org/10.3390/ijms18071387

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