The assessment of acute kidney injury in critically ill patients

Assessment of cell cycle arrest biomarkers and neutrophil gelatinase-associated lipocalin to distinguish acute kidney injury from other diseases in dogs

BACKGROUND

Cell cycle arrest biomarkers (tissue inhibitor of metalloproteinase-2 [uTIMP-2] and insulin-like growth factor binding protein 7 [uIGFBP7]), and neutrophil gelatinase-associated lipocalin (NGAL) variables are valuable biomarkers for early diagnosis of acute kidney injury (AKI) in people.

OBJECTIVES

To evaluate uTIMP-2, uIGFBP7, fractional excretion of NGAL (FeNGAL), and urinary to serum NGAL ratio (u/sNGAL) in healthy dogs, dogs with AKI, dogs with chronic kidney disease (CKD), and critically ill (CI) dogs.

ANIMALS

Forty-two client-owned dogs (healthy, n = 10; AKI, n = 11; CKD, n = 11; CI, n = 10).

METHODS

Prospective, observational study. After assessment of routine renal biomarkers, stress (uTIMP-2, uIGFBP7) and damage (NGAL) biomarkers were measured, using ELISA kits, and normalized to urinary creatinine (uCr).

RESULTS

Normalized uTIMP-2 and [uTIMP-2] × [uIGFBP7]/uCr were significantly higher in the AKI group (median 151.9 [range, 2.2-534.2] and 62.9 [1.1-266.8] pg/mL respectively), compared to healthy dogs (0.3 [0.2-74.7]; P < .001 and 0.16 [0.1-58.1] pg/mL; P < .001), dogs with CKD (0.7 [0.3-742.5]; P = .04 and 0.37 [0.2-180.1] pg/mL; P = .03) and CI dogs (1.9 [0.2-37.0]; P = .03 and 0.8 [0.1-16.1] pg/mL; P = .02). Fractional excretion of NGAL was significantly higher in dogs with AKI (54.17 [7.93-155.32] %), than in healthy (0.03 [0.01-0.21] %; P < .001) and CI dogs (3.05 [0.05-28.86] %; P = .02).

CONCLUSIONS AND CLINICAL IMPORTANCE

Normalized uTIMP-2, [uTIMP-2] × [uIGFBP7]/uCr, and FeNGAL can be valuable renal biomarkers for early diagnosis of AKI in dogs.

Serum free fatty acid elevation is related to acute kidney injury in primary nephrotic syndrome

The aim of this research was to examine the clinical characteristics of acute kidney injury (AKI) in primary nephrotic syndrome (NS) and discuss the relationship between serum lipids and AKI. A total of 1028 patients diagnosed with primary NS with renal biopsy results were enrolled in this study. The patients were divided into AKI (n = 81) and non-AKI (n = 947) groups, and their characteristics were compared using a propensity score analysis for the best matching. Serum free fatty acid (FFA) was an independent predictor for AKI in the postmatch samples (p = 0.011). No significant difference in FFA levels was observed among AKI stages or different pathological types in the AKI and non-AKI groups. The AUC (area under the ROC curve) was 0.63 for FFA levels to distinguish AKI. In primary NS, elevated FFA levels tend to be related to a high risk of AKI. FFAs have diagnostic value and may serve as biomarkers for AKI in NS.

Development and Validation of a Prediction Model for Acute Kidney Injury Among Patients With Acute Decompensated Heart Failure

Background: Acute kidney injury is an adverse event that carries significant morbidity among patients with acute decompensated heart failure (ADHF). We planned to develop a parsimonious model that is simple enough to use in clinical practice to predict the risk of acute kidney injury (AKI) occurrence. Methods: Six hundred and fifty patients with ADHF were enrolled in this study. Data for each patient were collected from medical records. We took three different approaches of variable selection to derive four multivariable logistic regression model. We selected six candidate predictors that led to a relatively stable outcome in different models to derive the final prediction model. The prediction model was verified through the use of the C-Statistics and calibration curve. Results: Acute kidney injury occurred in 42.8% of the patients. Advanced age, diabetes, previous renal dysfunction, high baseline creatinine, high B-type natriuretic peptide, and hypoalbuminemia were the strongest predictors for AKI. The prediction model showed moderate discrimination C-Statistics: 0.766 (95% CI, 0.729-0.803) and good identical calibration. Conclusion: In this study, we developed a prediction model and nomogram to estimate the risk of AKI among patients with ADHF. It may help clinical physicians detect AKI and manage it promptly.

Association of TNF-α-308 (G >A) (rs1800629) Gene Polymorphism with Adverse Outcomes of Sepsis in Critically Ill Patients

Sepsis-related mortality and morbidity are major health care problems worldwide. More effort is required to identify factors associated with adverse outcome. Evaluate the prognostic capacity of tumor necrosis factor (TNF), kidney injury molecule (KIM), and lactate and TNF-α-308 G > A gene polymorphism for prediction of 28 days-intensive care unit (ICU) mortality. TNF-α-308 G > A single nucleotide polymorphisms was detected by real-time-PCR on 112 had septic shock and 88 were septic. Serum TNF-α and urinary KIM were assessed by enzyme-linked immunosorbent assay. This study included 200 critically ill patients, 125 (62.5%) of them died within 28 days in ICU (nonsurvivors). Frequencies of TNF-308 G > A was (70.7) GG, (28) GA and (1.3) AA in survivors versus (85.6) GG, (12) GA and (2.4) AA for nonsurvivors, revealed significant association with ICU mortality but not sepsis severity (p = 0.15) or sepsis-induced acute kidney injury (AKI). In contrast, urinary KIM-1 revealed significant association with sepsis severity (p = 0.036) and AKI (p = 0.0001), but not 28-days ICU mortality. The relative risk of death in patients with GG genotype was 2.5 mainly in ICU younger male patients (odds ratios 24 and 4.9, p = 0.001). The genotype GG and GA were significantly associated with [increased urinary KIM-1 (0.29 ± 0.1) (p = 0.0001), terminal creatinine (1.67 ± 0.8) (p = 0.0001)] and [increased terminal urea (109 ± 0.001) (p = 0.001) and basal serum TNF (60 ± 0.001) (p = 0.0001)], respectively. In linear regression analysis, AKI 0.0001 (0.4-0.67), basal serum TNF 0.04 (0.0001-0.04), and TNF-308 GG 0.007 (0.05-0.33) were associated with 28 days ICU mortality [p value (95% confidence interval)]. The same results were observed for initial urea 0.024 (0.0001-0.003) and lack of diuretic usage 0.0001 (0.35-0.7) mainly in septic patients. Major frequency of TNF-308 G > A polymorphism (mainly in young age male patients), AKI and serum TNF were associated with increased risk for 28 days-ICU mortality. Furthermore, sepsis severity was influenced by TNF and urinary KIM-1, which reflects in AKI.

Validation of acute kidney injury prediction scores in critically ill patients

Prediction of acute kidney injury (AKI) in critically ill patients allows prompt intervention that improves outcome. We aimed for external validation of two AKI prediction scores that can be bedside calculated. A prospective observational study included patients admitted to medical and surgical critical care units. Performance of two AKI prediction scores, Malhotra score and acute kidney injury prediction score (APS), was assessed for their ability to predict AKI. The best cutoff point for each score was determined by Youden index. Area under the receiving operation characteristic curve, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were used to assess performance of each score. Univariate and multivariate regression analyses were done to detect the predictability of AKI. Goodness-of-fit and kappa Cohen agreement tests were done to show whether the expected score results fit well and agree with the observed results. AKI prevalence was 37.6%. The best cutoff values were 5 and 4 for Malhotra score and APS, respectively. Area under the curve for Malhotra 5 was 0.712 and for APS 4 was 0.652 with nearly similar sensitivity and specificity. Regression analysis demonstrated that Malhotra 5 was the independent predictor of AKI. Goodness-of-fit test showed significant results denoting lack of fit between the scores and the actual results. Kappa test showed moderate agreement for Malhotra 5 and fair agreement for APS 4. Both scores showed moderate performance for AKI prediction. Malhotra 5 showed better performance compared to APS 4. Multicenter international study is warranted to develop a universal model that can predict AKI in critically ill patients.

Ferritin in Kidney and Vascular Related Diseases: Novel Roles for an Old Player

Iron is at the forefront of a number of pivotal biological processes due to its ability to readily accept and donate electrons. However, this property may also catalyze the generation of free radicals with ensuing cellular and tissue toxicity. Accordingly, throughout evolution numerous pathways and proteins have evolved to minimize the potential hazardous effects of iron cations and yet allow for readily available iron cations in a wide variety of fundamental metabolic processes. One of the extensively studied proteins in the context of systemic and cellular iron metabolisms is ferritin. While clinicians utilize serum ferritin to monitor body iron stores and inflammation, it is important to note that the vast majority of ferritin is located intracellularly. Intracellular ferritin is made of two different subunits (heavy and light chain) and plays an imperative role as a safe iron depot. In the past couple of decades our understanding of ferritin biology has remarkably improved. Additionally, a significant body of evidence has emerged describing the significance of the kidney in iron trafficking and homeostasis. Here, we briefly discuss some of the most important findings that relate to the role of iron and ferritin heavy chain in the context of kidney-related diseases and, in particular, vascular calcification, which is a frequent complication of chronic kidney disease.