Acute kidney injury urinary biomarker time-courses

Acute kidney injury detection using refined and physiological-feature augmented urine output

Acute kidney injury (AKI) is common in the intensive care unit, where it is associated with increased mortality. AKI is often defined using creatinine and urine output criteria. The creatinine-based definition is more reliable but less expedient, whereas the urine output based definition is rapid but less reliable. Our goal is to examine the urine output criterion and augment it with physiological features for better agreement with creatinine-based definitions of AKI. The objectives are threefold: (1) to characterize the baseline agreement of urine output and creatinine definitions of AKI; (2) to refine the urine output criteria to identify the thresholds that best agree with the creatinine-based definition; and (3) to build generalized estimating equation (GEE) and generalized linear mixed-effects (GLME) models with static and time-varying features to improve the accuracy of a near-real-time marker for AKI. We performed a retrospective observational study using data from two independent critical care databases, MIMIC-III and eICU, for critically ill patients who developed AKI in intensive care units. We found that the conventional urine output criterion (6 hr, 0.5 ml/kg/h) has specificity and sensitivity of 0.49 and 0.54 for MIMIC-III database; and specificity and sensitivity of 0.38 and 0.56 for eICU. Secondly, urine output thresholds of 12 hours and 0.6 ml/kg/h have specificity and sensitivity of 0.58 and 0.48 for MIMIC-III; and urine output thresholds of 10 hours and 0.6 ml/kg/h have specificity and sensitivity of 0.49 and 0.48 for eICU. Thirdly, the GEE model of four hours duration augmented with static and time-varying features can achieve a specificity and sensitivity of 0.66 and 0.61 for MIMIC-III; and specificity and sensitivity of 0.66 and 0.64 for eICU. The GLME model of four hours duration augmented with static and time-varying features can achieve a specificity and sensitivity of 0.71 and 0.55 for MIMIC-III; and specificity and sensitivity of 0.66 and 0.60 for eICU. The GEE model has greater performance than the GLME model, however, the GLME model is more reflective of the variables as fixed effects or random effects. The significant improvement in performance, relative to current definitions, when augmenting with patient features, suggest the need of incorporating these features when detecting disease onset and modeling at window-level rather than patient-level.

Impact of acute versus repetitive moderate intensity endurance exercise on kidney injury markers

Exercise may lead to kidney injury through several mechanisms. Urinary Kidney Injury Molecule-1 (uKIM1) and Neutrophil Gelatinase-Associated Lipocalin (uNGAL) are known biomarkers for acute kidney injury, but their response to repetitive exercise remains unknown. We examined the effects of a single versus repetitive bouts of exercise on markers for kidney injury in a middle-aged population. Sixty subjects (aged 29-78 years, 50% male) were included and walked 30, 40 or 50 km for three consecutive days. At baseline and after exercise day 1 and 3, a urine sample was collected to determine uNGAL and uKIM1. Furthermore, urinary cystatin C, creatinine, and osmolality were used to correct for dehydration-related changes in urinary concentration. Baseline uNGAL was 9.2 (5.2-14.7) ng/mL and increased to 20.7 (11.0-37.2) ng/mL and 14.2(8.0-26.3) ng/mL after day 1 and day 3, respectively, (P ≤ 0.001). Baseline uKIM1 concentration was 2.6 (1.4-6.0) ng/mL and increased to 5.2 (2.4-9.1) ng/mL (P = 0.002) after day 1, whereas uKIM1 was not different from baseline at day 3 (2.9 [1.4-6.4] ng/mL (P = 0.52)). Furthermore, both uNGAL and uKIM1 levels were higher after day 1 compared to day 3 (P < 0.01). When corrected for urinary cystatin C, creatinine, and osmolality, uNGAL demonstrated a similar response compared to the uncorrected data, whereas differences in uKIM1 between baseline, day 1 and day 3 (Ptime = 0.63) were no longer observed for cystatin C and creatinine corrected data. A single bout of prolonged exercise significantly increased uNGAL concentration, whereas no changes in uKIM1 were found. Repetitive bouts of exercise show that there is no cumulative effect of kidney injury markers.

Neutrophil Gelatinase-Associated Lipocalin as a Diagnostic Marker for Acute Kidney Injury in Oliguric Critically Ill Patients: A Post-Hoc Analysis

BACKGROUND

Oliguria occurs frequently in critically ill patients, challenging clinicians to distinguish functional adaptation from serum-creatinine-defined acute kidney injury (AKIsCr). We investigated neutrophil gelatinase-associated lipocalin (NGAL)'s ability to differentiate between these 2 conditions.

METHODS

This is a post-hoc analysis of a prospective cohort of adult critically ill patients. Patients without oliguria within the first 6 h of admission were excluded. Plasma and urinary NGAL were measured at 4 h after admission. AKIsCr was defined using the AKI network criteria with pre-admission serum creatinine or lowest serum creatinine value during the admission as the baseline value. Hazard ratios for AKIsCr occurrence within 72 h were calculated using Cox regression and adjusted for risk factors such as sepsis, pre-admission serum creatinine, and urinary output. Positive predictive values (PPV) and negative predictive values (NPV) were calculated for the optimal cutoffs for NGAL.

RESULTS

Oliguria occurred in 176 patients, and 61 (35%) patients developed AKIsCr. NGAL was a predictor for AKIsCr in univariate and multivariate analysis. When NGAL was added to a multivariate model including sepsis, pre-admission serum creatinine and lowest hourly urine output, it outperformed the latter model (plasma p = 0.001; urinary p = 0.048). Cutoff values for AKIsCr were 280 ng/ml for plasma (PPV 80%; NPV 79%), and 250 ng/ml for urinary NGAL (PPV 58%; NPV 78%).

CONCLUSIONS

NGAL can be used to distinguish oliguria due to the functional adaptation from AKIsCr, directing resources to patients more likely to develop AKIsCr.

The effects of environmental chemicals on renal function

The global incidence of chronic kidney disease (CKD) is increasing among individuals of all ages. Despite advances in proteomics, genomics and metabolomics, there remains a lack of safe and effective drugs to reverse or stabilize renal function in patients with glomerular or tubulointerstitial causes of CKD. Consequently, modifiable risk factors that are associated with a progressive decline in kidney function need to be identified. Numerous reports have documented the adverse effects that occur in response to graded exposure to a wide range of environmental chemicals. This Review summarizes the effects of such chemicals on four aspects of cardiorenal function: albuminuria, glomerular filtration rate, blood pressure and serum uric acid concentration. We focus on compounds that individuals are likely to be exposed to as a consequence of normal consumer activities or medical treatment, namely phthalates, bisphenol A, polyfluorinated alkyl acids, dioxins and furans, polycyclic aromatic hydrocarbons and polychlorinated biphenyls. Environmental exposure to these chemicals during everyday life could have adverse consequences on renal function and might contribute to progressive cumulative renal injury over a lifetime. Regulatory efforts should be made to limit individual exposure to environmental chemicals in an attempt to reduce the incidence of cardiorenal disease.

The clinical utility window for acute kidney injury biomarkers in the critically ill

INTRODUCTION

Acute Kidney Injury (AKI) biomarker utility depends on sample timing after the onset of renal injury. We compared biomarker performance on arrival in the emergency department (ED) with subsequent performance in the intensive care unit (ICU).

METHODS

Urinary and plasma Neutrophil Gelatinase-Associated Lipocalin (NGAL), and urinary Cystatin C (CysC), alkaline phosphatase, γ-Glutamyl Transpeptidase (GGT), α- and π-Glutathione S-Transferase (GST), and albumin were measured on ED presentation, and at 0, 4, 8, and 16 hours, and days 2, 4 and 7 in the ICU in patients after cardiac arrest, sustained or profound hypotension or ruptured abdominal aortic aneurysm. AKI was defined as plasma creatinine increase ≥ 26.5 μmol/l within 48 hours or ≥ 50% within 7 days.

RESULTS

In total, 45 of 77 patients developed AKI. Most AKI patients had elevated urinary NGAL, and plasma NGAL and CysC in the period 6 to 24 hours post presentation. Biomarker performance in the ICU was similar or better than when measured earlier in the ED. Plasma NGAL diagnosed AKI at all sampling times, urinary NGAL, plasma and urinary CysC up to 48 hours, GGT 4 to 12 hours, and π-GST 8 to 12 hours post insult. Thirty-one patients died or required dialysis. Peak 24-hour urinary NGAL and albumin independently predicted 30-day mortality and dialysis; odds ratios 2.87 (1.32 to 6.26), and 2.72 (1.14 to 6.48), respectively. Urinary NGAL improved risk prediction by 11% (IDI event of 0.06 (0.002 to 0.19) and IDI non-event of 0.04 (0.002 to 0.12)).

CONCLUSION

Early measurement in the ED has utility, but not better AKI diagnostic performance than later ICU measurement. Plasma NGAL diagnosed AKI at all time points. Urinary NGAL best predicted mortality or dialysis compared to other biomarkers.

TRIAL REGISTRATION

Australian and New Zealand Clinical Trials Registry ACTRN12610001012066. Registered 12 February 2010.