Silvia Coelho

Cystatin C as a marker of acute kidney injury in the emergency department

BACKGROUND AND OBJECTIVESnThe diagnosis of acute kidney injury (AKI) is usually based on changes in serum creatinine, which is a poor marker of early renal dysfunction. The discriminative and predictive abilities of serum and urinary cystatin C were examined for the prediction of AKI.nnnDESIGN, SETTING, PARTICIPANTS, & MEASUREMENTSnIn this prospective cohort study, serum and urinary cystatin C were serially measured in a heterogeneous group of patients (n = 616) presenting to a tertiary care emergency department. The primary outcome was AKI, classified according to RIFLE and AKIN criteria. The secondary outcome was an adjudication based on clinical criteria to AKI, prerenal azotemia, chronic kidney disease (CKD), and normal kidney function.nnnRESULTSnPatients were adjudicated to have AKI in 21.1%, prerenal azotemia in 25.8%, CKD in 2.4%, and normal kidney function in 50.7%. For the diagnosis of AKI, the discriminatory ability of urinary creatinine and cystatin C was marginal. Both serum cystatin C and serum creatinine (at presentation and 6 hours later) showed high discriminatory ability for the diagnosis of AKI. However, only serum cystatin C attained a significant early predictive power (Hosmer-Lemeshow P value > 0.05). Serum cystatin C could differentiate between AKI and prerenal azotemia, but not between AKI and CKD.nnnCONCLUSIONSnSerum cystatin C is an early, predictive biomarker of AKI, which outperforms serum creatinine in the heterogeneous emergency department setting. However, neither biomarker discriminated between AKI and CKD. Additional biomarkers continue to be needed for improved specificity in the diagnosis of community-acquired AKI.

Plasma NGAL for the Diagnosis of AKI in Patients Admitted from the Emergency Department Setting

BACKGROUND AND OBJECTIVESnThe purpose of this study was to determine the accuracy of plasma neutrophil gelatinase-associated lipocalin as a marker of AKI in patients admitted from the emergency department.nnnDESIGN, SETTING, PARTICIPANTS, & MEASUREMENTSnIn this prospective cohort study, patients (n=616) admitted from the emergency department from March to November of 2008 were classified according to clinical criteria as AKI, transient azotemia, stable CKD, and normal function. Plasma neutrophil gelatinase-associated lipocalin was measured serially. A logistic regression model using clinical characteristics was fitted to the data, and a second model included discretized plasma neutrophil gelatinase-associated lipocalin. Performance of the models was evaluated by Hosmer-Lemeshow goodness-of-fit test, area under the receiver operating characteristic curve, net reclassification improvement, integrated discrimination improvement, and predictiveness curve.nnnRESULTSnTwenty-one percent of patients were classified as AKI; the highest median levels of plasma neutrophil gelatinase-associated lipocalin were in the AKI group (146-174 ng/ml at various time points) and increased with AKI severity (207-244 ng/ml for Acute Kidney Injury Network classification stage>2). The discriminative ability of plasma neutrophil gelatinase-associated lipocalin for AKI diagnosis (area under the curve, 0.77-0.82 at various time points) improved with higher grades of severity (area under the curve, 0.85-0.89 for AKIN>2). Plasma neutrophil gelatinase-associated lipocalin discriminated AKI from normal function and transient azotemia (area under the curve, 0.85 and 0.73, respectively). Patients were classified into three grades of AKI risk according to plasma neutrophil gelatinase-associated lipocalin levels (low, moderate [i.e., the gray zone], and high). Patients with plasma neutrophil gelatinase-associated lipocalin in the high-risk category displayed a 10-fold greater risk of AKI (odds ratio, 9.8; 95% confidence interval, 5.6 to 16.9). The addition of plasma neutrophil gelatinase-associated lipocalin to the clinical model yielded a net reclassification improvement of 94.3% and an integrated discrimination improvement of 0.122.nnnCONCLUSIONnPlasma neutrophil gelatinase-associated lipocalin is an accurate biomarker for prediction of AKI in patients admitted from the emergency department. This work proposes a three-grade classification of AKI risk based on plasma neutrophil gelatinase-associated lipocalin levels.

Hemoglobin A1c in patients on peritoneal dialysis: how should we interpret it?

Almost half the patients on peritoneal dialysis are diabetic and glycemic control is essential to improve both patient and technique survival. Hemoglobin A1c (HbA1c) is widely used in the general population for diabetes diagnosis and monitoring as it highly correlates with blood glucose levels and outcomes. Its use has been extrapolated to the peritoneal dialysis population, despite HbA1c being commonly underestimated. In renal failure patients, HbA1c is influenced by variables affecting not only glycemia but also hemoglobin and the time of interaction between the two. Importantly, the impact of these variables differs in peritoneal dialysis compared to non‐dialysis chronic kidney disease and hemodialysis patients.

What is the Role of HbA1c in Diabetic Hemodialysis Patients

The definition of a good glycemic control in patients with diabetes mellitus on hemodialysis is far from settled. In the general population, hemoglobin A1c is highly correlated with the average glycemia of the last 8–12 weeks. However, in hemodialysis patients, the correlation of hbA1c with glycemia is weaker as it also reflects changes in hemoglobin characteristics and red blood cells half‐life. As expected, studies show that the association between HbA1c and outcomes in these patients differ from the general population. Therefore, the value of HbA1c in the treatment of hemodialysis patients has been questioned. Guidelines are generally cautious in their recommendations about possible targets of HbA1c in this population. Indeed, the risk of not treating hyperglycemia should be weighed against the particularly high risk of precipitating hypoglycemia in dialysis patients. In this review, a critical analysis of the current role of HbA1c in the care of hemodialysis patients is presented.

DO WE REALLY KNOW THE MEANING OF SODIUM REMOVAL

The continuing pursuit to improve outcomes in peritoneal dialysis (PD) patients has led to a broader and more comprehensive definition of dialysis adequacy that includes fluid status in addition to solute clearance (1–3). However, the effect of fluid status on survival has not been easy to determine, because of both the lack of a consensus unit of measurement (or a combination of measures such as blood pressure, extracellular volume, and cardiac parameters) and the lack of a clear definition of what constitutes “ideal” fluid status. Investigators have tried to infer the effect of fluid status on outcomes through surrogate markers of fluid balance such as ultrafiltration, sodium intake, and sodium removal (3–5). However, fluid status not only reflects the balance between input and output of salt and water, but also is influenced by demographic factors—for example, sex, comorbidities, and especially cardiac function and inflammatory status with their associated hypoalbuminemia and muscle wasting (6–9). Bioimpedance analysis (BIA) offers one of the most promising noninvasive tools for assessing body composition and, indirectly, fluid status. An increased ratio of extracellular water to total body water (ECW/TBW), measured using BIA, has proved to be a powerful predictor of reduced survival (10). In this context, studies that combine measurement of body composition with measured sodium intake and removal are of interest. Last year, Jie Dong and colleagues showed that a higher intake of sodium and calories was associated with better survival (9). In this issue of Peritoneal Dialysis International, they develop a more holistic approach than that in their first analysis, introducing sodium and fluid removal and parameters of nutrition, including body composition analysis determined from baseline BIA measurements, in their survival analysis (11). They show that higher sodium removal, analyzed as a timedependent variable, is an independent predictor of survival that loses significance when adjusted for parameters of nutrition, especially lean body mass. Furthermore, they divided their population of 305 prevalent continuous ambulatory PD patient into those with “high” and “low” sodium removal, demonstrating that the former group had significantly higher intakes of energy and sodium. The conclusion would therefore seem to be that if patients eat more, they will be better nourished, will excrete more salt, and thus will live longer. This proposition is likely to be true, but in reality may be not quite that simple. The purpose of the present commentary is to dig a little deeper into the data and see what lies behind the results and what those results may imply with regard to current practice. To that end, we raise 3 questions, treated in the subsections that follow.

Is the management of diabetes different in dialysis patients

Diabetes is highly and increasingly prevalent in the dialysis population and negatively impacts both quality and quantity of life. Nevertheless, the best approach to these patients is still debatable. The question of whether the management of diabetes should be different in dialysis patients does not have a clear yes or no answer but is divided into too many sub‐issues that should be carefully considered. In this review, lifestyle, cardiovascular risk, and hyperglycemia management are explored, emphasizing the possible pros and cons of a similar approach to diabetes in dialysis patients compared to the general population.

Can We Really Discuss About RRT Starting Time Before We Have a Recovery Biomarker

Recently, Besen and Das published a meta-analysis reviewing the outcomes of early versus late initiation of renal replacement therapy (RRT). They included patients with and without acute kidney injury (AKI) for whom RRT was started with purification goals. They showed that early start of RRT was not associated with better morbidity or mortality outcomes. Nevertheless, since the last decade and mainly in the last couple of years, the month when a study or a meta-analysis does not come out contemplating about the best RRT starting timing is rare, with early and late start showing better outcomes in alternating publications. The eternal question remains. Early and late are still nonconsensual terms and seem to have different meanings according to the population studied (cardiac surgery patients, maybe because they have a higher rate of progressing AKI, seem to benefit from an earlier start of RRT than a mixed critical care population). What is consensual, is that we don’t want to restrain dialysis until it is too late for someone who will eventually really need it. Similarly, we don’t want to start dialysis to someone who would never need it and add a burden of potential catheter and technique complications, besides the financial and logistical costs. We urgently need a recovery biomarker or panel of biomarkers that can approach us to personalized medicine and help us predict for individual patients the probability of short-term recovery. Namely, we need biomarkers that can help us predict the progression of AKI to persistent AKI and from here to acute kidney disease and chronic kidney disease. In a future that we forecast not long, clinical studies should include biomarkers in the definition of early and late start of RRT.