rel="nofollow" href="#ulink_22583081-6117-55bb-af96-41a2c32f4a59">16–18]. Where the urine volume is such that the normal solute load cannot be cleared, this will be reflected in classical changes in serum electrolytes, acid base parameters and traditional “markers” of renal function including SCr and urea. As such, urine output may be of limited sensitivity and specificity in defining AKI as is reflected in the poor performance of urinary biochemistry particularly in the intensive care unit (ICU) setting [19]. Moreover, the clinical response to isolated oliguria may result in unnecessary intervention such as inappropriate fluid therapy and therefore, the presence of oliguria should always be interpreted within the clinical context as a whole [20]. This is not to advocate ignoring the urine output: the transition from physiological to pathological oliguria is unlikely to be stepwise. Therefore, detection of renal dysfunction may be made earlier if oliguria is noted. For example, in a study on critically ill patients, the diagnosis of AKI based solely on the presence of oliguria found that approximately 50% of these patients proceeded to develop AKI based on SCr criteria 24 h later [21]. Similarly, in a mixed ICU cohort, 69% of oliguric patients subsequently developed creatinine criteria for AKI diagnosis [22]. These results imply that not all patients with oliguria develop changes in SCr and as such using urine output criteria will increase the number of patients classified as having AKI. Furthermore, in some cases, this may identify a different cohort of patients. What is clear is that where the AKI criteria are satisfied using both SCr and urine output, this portends a worse outcome [23].
The SCr and the derived glomerular filtration rate provide the mainstay for outpatient management of chronic kidney disease. Creatinine is neither reabsorbed nor metabolised by the kidney (although tubular secretion does occur) and is freely filtered across the glomerulus and as such serves as a marker of renal function. However, the use of the SCr as a marker for AKI is far from ideal. Although the formation of creatinine is relatively constant under most conditions outside the ICU, this is not the case in the critically ill or where there is considerable metabolic disturbance as is found in many causes of AKI. Changes in SCr may overestimate renal function as a result of secretion in the proximal tubule and increases can be seen following the administration of medications that inhibit tubular secretion despite no change in renal function. SCr metabolism may also be affected by conditions common to many ICU patients including sepsis that may reduce production rates considerably [24, 25]. In addition, creatinine is distributed in the total body water and may, therefore, be affected by variations in volume status although this is unlikely to be of any major practical significance [26]. Furthermore, in the critically ill, low SCr may be observed related to reduced muscle bulk, liver disease, poor nutritional status and also augmented renal clearance. Comparing creatinine measurements obtained from different laboratories may confound the diagnosis further. Perhaps the most important limitation regarding the SCr as a marker of AKI is the creatinine kinetics associated with acute dysfunction with 24–36 h needed to elapse after a definite renal insult before a rise in SCr is detectable in many cases [27, 28]. It follows that any attempts to either prevent AKI in patient populations or indeed identify patients at risk are thwarted by the fact that the variables used to define AKI, creatinine and urine output, are such imprecise tools. Hence, there has been much interest in the pursuit of a quantifiable indicator that will allow for the early detection of AKI. Understandably this has been earmarked as an area of considerable research interest driven, in part, by the clinical models of care based on other biomarkers with cardiac troponins being the best known examples.
AKI Biomarkers
Twenty years ago, an NIH study group defined a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to a therapeutic intervention” [29]. Therefore, biomarkers may inform as to the underlying aetiology of a condition as well as the probable response to therapy. Hence, they may be diagnostic and/or prognostic. Moreover, they may provide information as to the long-term outcome associated with the condition. Despite its limitations, SCr may be used as an example of a biomarker, as this will indicate a reduction in glomerular filtration rate, given it is a marker of filtration, which may be associated with an AKI and will also provide information with regard to the development and monitoring of CKD. However, extensive interest in biomarkers, particularly the so-called novel or molecular biomarkers with special focus on AKI, has been around early recognition of AKI, given the inherent flaws in employing standard measures as markers of acute injury. Therefore a strategy, whereby patients are identified early, may allow specific actions to be taken to attenuate the AKI process, although till date a considerable evidence gap exists with regard to such potential interventions.
As of now, there have been numerous studies on many different potential biomarkers of renal dysfunction under many different conditions. Some of the more intensely studied are outlined in Table 1. The predominant feature is that the best performing biomarkers tend to be markers of urinary infection and range from markers of “renal stress” (e.g., tissue Inhibitor of metalloproteinase-2 [TIMP-2]; insulin-like growth factor binding protein-7 [IGFBP-7]) to those of tubular damage (e.g., Kidney Injury Molecule [KIM-1]). Most studies on biomarkers of AKI have concentrated on the ability of the biomarker to predict the development of AKI. By definition this must be prediction of changes either in SCr and/or in urine output. Therefore, the imperfect tests for AKI are used as the gold-standard for the assessment of AKI biomarkers and this reliance on SCr and urine output detracts from any other information that these candidate molecules may be delivering. Furthermore, the kinetic profile of the biomarker may be entirely different when compared to the kinetics of SCr post insult and therefore, a biomarker may be elevated in the hours after an insult but probably will be undetectable by the time the SCr has risen. This is outlined graphically in Figure 1. For this reason, several studies have addressed the use of AKI biomarkers in the postoperative period. Here there is a timed insult and also the possibility to measure pre-insult markers in order to detect a rise.
Table 1. Summary of biomarkers for renal dysfunction
| Biomarker | Characteristics | Considerations |
| NGAL | A 25-kDa protein of the family of lipocalins with its capacity to bind iron-siderophore complexes (bacteriostatic function) | May be elevated in sepsis, chronic kidney disease and urinary tract infections Lack of specific cut-off values |
| IL-18 | A 24 kDa cytokine from the IL-1 family of cytokines (regulates innate and adaptive immunity) | No certain prediction of AKI in adults |
| L-FABP | A 14 kDa protein from the large superfamily of lipid binding proteins (aids the regulation of fatty acids uptake and the intracellular transport) | Strongly associated with anaemia in non-diabetic patients |
| KIM-1 | A 38.7 kDa type I transmembrane glycoprotein with an extracellular immunoglobulin-like domain topping a long mucin-like domain (tubular regeneration; mediates the phagocytosis of apoptotic cells) | May be elevated in the setting of chronic proteinuria and inflammatory diseases High cost and poor availability |
| IGFBP-7TIMP-2 | A 29-kDa secreted protein known to bind to and inhibit signalling through IGF-1 receptors (involved in G1 cell cycle arrest)A 21 kDa protein, endogenous inhibitors of metalloproteinase activities | May be elevated in diabetes |
| Calprotectin | A
|
