Predicting acute kidney injury: current status and future challenges

A simple risk score for prediction of sepsis associated-acute kidney injury in critically ill patients

BACKGROUND

Sepsis is common and frequently fatal condition in critically ill patients and is a major cause of acute kidney injury (AKI). In this retrospective study, we sought to develop a comprehensive risk score model of sepsis associated-AKI (SA-AKI).

METHODS

A total of 2617 patients were randomly assigned to a development (1554 patients) and a validation group (777 patients). The risk score model for SA-AKI was developed with multivariate regression analysis in development group and the model was further evaluated on validation group.

RESULTS

We identified 16 independent predictors of SA-AKI in development group (age ≥ 60 years, hypertension/coronary heart disease, diabetes, chronic kidney disease, heart failure, chronic obstructive pulmonary disease, acute severe pancreatitis, hypotension, hypoproteinemia, lactic acidosis, the length of stay in intensive care unit(ICU), 60 g/L<hemoglobin < 90 g/L, hemoglobin ≤ 60 g/L, and ≥ 2 failed organs. This model had excellent performance characteristics in validation cohort(c statistic 0.857, 95% CI 0.839-0.874).

CONCLUSION

The novel risk score model for SA-AKI in ICU can identify patients at high risk to develop AKI. Application of this model could help clinicians to stratify patients for primary prevention, surveillance and early therapeutic intervention to improve care and prognosis of sepsis patients in ICU.

Development and validation of an automated algorithm for identifying patients at higher risk for drug-induced acute kidney injury

PURPOSE

Using information from institutional electronic health records, we aimed to develop dynamic predictive models to identify patients at high risk of acute kidney injury (AKI) among those who received a nephrotoxic medication during their hospital stay.

METHODS

Candidate predictors were measured for each of the first 5 hospital days where a patient received a nephrotoxic medication (risk model days) to predict an AKI, using logistic regression with reduced backward variables elimination in 100 bootstrap samples. An AKI event was defined as an increase of serum creatinine ≥ 200% of a baseline SCr within 5 days after a risk model day. Final models were internally validated by replication in 100 bootstrap samples and a risk score for each patient was calculated from the validated model. As performance measures, the area under the receiver operation characteristic curves (AUC) and the number of AKI events among patients who had high risk scores were estimated.

RESULTS

The study population included 62,561 admissions followed by 1,212 AKI events (1.9 events/100 admissions). We constructed 5 risk models corresponding to the first 5 hospital days where patients were exposed to at least one nephrotoxic medication. Validated AUCs of the 5 models ranged from 0.78 to 0.81. Depending on risk model day, admissions ranked in the 90th percentile of the risk score captured between 43% to 49% of all AKI events.

CONCLUSION

A dynamic prediction model was built successfully for inpatient AKI with excellent discriminative validity and good calibration, allowing clinicians to focus on a select high-risk population that captures the majority of AKI events.

Plasma S100A8/A9 heterodimer is an early prognostic marker of acute kidney injury associated with cardiac surgery

AIM

We investigated whether plasma levels of the inflammation marker S100A8/A9, could predict acute kidney injury (AKI) onset in patients undergoing cardiac surgery necessitating cardiopulmonary bypass (CPB).

PATIENTS & METHODS

Plasma levels of S100A8/A9 and other neutrophil cytosolic proteins were measured in 39 patients pre- and immediately post-CPB.

RESULTS

All markers increased significantly post-CPB with S100A8/A9, S100A12 and myeloperoxidase levels significantly higher in patients who developed AKI within 7 days. S100A8/A9 had good prognostic utility for AKI, with an area under the receiver operating characteristic curve of 0.81 (95% CI: 0.676-0.949) and a cut-off value of 10.6 μg/ml (85.7% sensitivity and 75% specificity) irrespective of age.

CONCLUSION

Plasma S100A8/A9 levels immediately after cardiac surgery, can predict onset of AKI, irrespective of age.

Urine volume as a predicting factor for furosemide clearance during continuous infusion in AKI septic shock patients on hemodiafiltration

BACKGROUND

This study assessed the contribution of intracorporeal (IC) and extracorporeal clearance (EC) of furosemide in patients with septic acute kidney injury (AKI), and the relationship between plasma concentrations and urine volume.

METHODS

Prospective cohort observational study of 15 patients with septic AKI undergoing continuous veno-venous hemodiafiltration (CVVHDF) divided according to urine volume (< 500 ml/12 h, Oliguria group, n = 5; > 500 ml/12 h, Diuresis group, n = 10) during continuous infusion of furosemide (120 mg/12 h) at steady-state condition. Plasma and effluent furosemide concentrations were determined by high-performance liquid chromatography (HPLC)-mass spectrometry every 12 h for 48 h.

RESULTS

Furosemide plasma concentrations and total body clearance (TBC) were 6.14 mg/l and 22.1 ml/min for the Oliguria group, and 2.63 mg/l and 54.4 ml/min for the Diuresis group, respectively (p < 0.05). When urine volume was < 500 ml/24 h, the furosemide plasma concentrations peaked at the potentially toxic value of 13.0 mg/l. Furosemide EC was not relevant for the Diuresis group, but it represented 18% of TBC for the Oliguria group. Furosemide plasma concentrations correlated positively with dose infusion for both groups (r = 0.728 and 0.685, p < 0.05), and negatively with urine volume only for the Diuresis (r = - 0.578, p < 0.01) but not for the Oliguria group (r = - 0.089, p = 0.715).

CONCLUSIONS

For patients with urine volume > 500 ml/12 h continuous infusion of furosemide up to 480 mg/24 h leads to increasing urine volume, which can predict furosemide plasma levels within its safety range. When the urine volume is lower, the furosemide plasma levels are increased beyond any further diuretic efficacy.

Drug therapy and other factors associated with the development of acute kidney injury in critically ill patients: a cross-sectional study

BACKGROUND

Acute kidney injury (AKI) is associated with a significant increase in morbidity, mortality, and health care costs. In intensive care units (ICU), AKI is commonly multifactorial and frequently involves diverse factors, such as hypovolemia, sepsis, and the use of nephrotoxic drugs. We aimed to investigate drug therapy and other factors associated with the development of AKI in a Brazilian public hospital.

METHODS

This is a cross-sectional study involving critically ill patients at an ICU of a tertiary hospital. All data on sequential serum creatinine (SCr) level, glomerular filtration rate (GFR), and urine output were collected during ICU stay. The primary outcome was the occurrence of AKI assessed by the Acute Kidney Injury Network (AKIN) criterion. Sociodemographics, clinical data and drug therapy were considered as covariates. Factors associated with AKI were assessed using logistic regression.

RESULTS

Overall, 122 participants were included in the study. Median age was 46.0 (interquartile range, IQ = 29.0-69.0) years, with a predominance of men (58.2%). Mean number of prescribed drugs throughout ICU stay was 22.0 ± 9.4. The number of potentially nephrotoxic drugs ranged from two to 24 per patient. A total of 29 (23.8%) ICU patients developed AKI. In the AKI-group, patients were older and showed higher Acute Physiology and Chronic Health Evaluation II (APACHE II) scores at admission, higher rates of sedation, mechanical ventilation, and infection. More drugs in general and specifically more vasoactive drugs were prescribed for AKI group. Patients who developed AKI tended to have extended stays in the ICU and a lower probability of being discharged alive than patients with no AKI development. Model adjustments of logistic regression showed that the number of medications (OR 1.15; 95% CI [1.05-1.27]) was the only factor associated with AKI in this study. This association was independent of drug nephrotoxicity.

DISCUSSION

Intensive care is characterized by its complexity that combines unstable patients, severe diseases, high density of medical interventions, and drug use. We found that typical risk factors for AKI showed statistical association on bivariate analysis. The contribution of drug therapy in the occurrence of AKI in medical ICUs reinforces the need for prevention strategies focused on early recognition of renal dysfunction and interventions in drug therapy. These actions would help improve the quality of patient care and ensure progress towards medication safety.

Renal Angina Is a Sensitive, but Nonspecific Identifier of Postcardiac Surgery Acute Kidney Injury

OBJECTIVES

Acute kidney injury (AKI) is a common complication of cardiac surgery, and early detection is difficult. This study was performed to determine the sensitivity, specificity, positive predictive value, negative predictive value, and statistical performance of renal angina (RA) as an early predictor of AKI in an adult cardiac surgical patient population.

DESIGN

Retrospective, nonrandomized, observational study.

SETTING

A single, university-affiliated, quaternary medical center.

PARTICIPANTS

The study comprised 324 consecutive patients undergoing coronary artery bypass grafting or cardiac valvular surgery from February 1 through July 30, 2014.

INTERVENTIONS

None.

MEASUREMENTS AND MAIN RESULTS

One hundred-seven patients at moderate or high risk of developing postoperative renal injury were identified, 82 of whom met criteria for RA. The occurrence of RA was found to have an 80.9% sensitivity and 30.8% specificity for the prediction of AKI using Acute Kidney Injury Network criteria and 89.3% sensitivity and 27.8% specificity when paired with the Risk, Injury, Failure, Loss, End Stage Renal Disease criteria. A receiver operating characteristic area under the curve analysis revealed a nonsignificant predictive ability of 55.8% (95% confidence interval 0.47-0.65) when RA was paired with Acute Kidney Injury Network criteria; however, the receiver operating characteristic area under the curve was significant when paired with Risk, Injury, Failure, Loss, End Stage Renal Disease criteria, with a predictive ability of 0.586 (0.509-0.662).

CONCLUSIONS

RA is a sensitive, but nonspecific, predictor of postcardiac surgery AKI, with clinical utility most suited as a screening tool.

Novel acute kidney injury biomarkers: their characteristics, utility and concerns

Acute kidney injury (AKI) consists of a rapid renal function decline which usually increases serum urea and creatinine levels. Since kidney injury begins by inducing biological and molecular changes which evolve to cellular damage, biomarkers could be used as tools for monitoring early AKI appearance, and predicting its recovery. Among the main AKI biomarkers the neutrophil gelatinase-associated lipocalin, cystatin C, kidney injury molecule-1, monocyte chemotactic peptide-1, N-acetyl-β-D-glucosaminidase, interleukin-18, liver-type fatty acid-binding protein, netrin-1, cycle arrest markers, endogenous ouabain, selenium-binding protein 1, and BPIFA2 marker, have been described. Even though novel biomarkers seem to be more helpful to early detect AKI and/or predict the need for renal replacement, and mortality compared to serum creatinine, more comprehensive studies are still required to determine their clinical utility.

Stem cell extracellular vesicles and kidney injury

Extracellular vesicles (EVs) appear as a new promising cell-free therapy for acute and chronic renal diseases. EVs retain characteristics of the cell of origin and those derived from stem cells may mimic their regenerative properties per se. In fact, EVs contain many active molecules such as proteins and RNA species that act on target cells through different mechanisms, stimulating proliferation and angiogenesis and reducing apoptosis and inflammation. There are several reports that demonstrate a general regenerative potential of EVs derived from mesenchymal stromal cells (MSCs) of different sources in kidney injury models. In addition, a promising new approach is the use of EVs in the graft perfusion solution for kidney conditioning before transplant. Here we summarize the application of EVs released by stem cells in preclinical models of acute and chronic renal damage, comparing animal models, use of EVs of different cell origin and of their sub-fractions, doses, route of administration and efficacy of treatment.