Biomarkers for prediction of acute kidney injury in pediatric patients: a systematic review and meta-analysis of diagnostic test accuracy studies

Diagnostic Accuracy of Furosemide Stress Test and Cystatin-C for Predicting Acute Kidney Injury Progression in Children: A Prospective Cohort Study

OBJECTIVES

To evaluate the predictive ability of furosemide stress test (FST), serum and urine cystatin-C in identifying progressive acute kidney injury (AKI) and the need for kidney replacement therapy (KRT).

METHODS

Children aged one month to 18 y admitted in the pediatric intensive care unit (PICU) with Kidney Diseases Improving Global Outcomes (KDIGO) stage-1/2 AKI were enrolled. FST and serum and urine cystatin-C levels were performed and analyzed. The primary outcome was progression to stage-3 AKI. Secondary outcomes included comparing predictive ability of FST vs. cystatin-C for stage-3 AKI and need for KRT, adverse effects, length of hospital stay and mortality.

RESULTS

Of the 41 children enrolled, seven (17.07%) progressed to KDIGO stage-3 AKI. Four children were furosemide non-responders at 2 h and five at 6 h post-FST. The sensitivity, specificity and area under the receiver operating characteristic curve (AUROC) of FST at 2 h were 57.14%, 100% and 0.84 (p = 0.01), and at 6 h were 71.43%, 100% and 0.87 (p < 0.001), respectively. Urine cystatin-C was positive in 20 (48.78%) children, of which seven progressed to stage-3 AKI [sensitivity- 100%, specificity- 61.76%, AUROC- 0.91 (p = 0.003)]. Five of nine children with positive serum cystatin-C progressed to stage-3 AKI [sensitivity- 71.43%, specificity- 88.24%, AUROC- 0.75 (p = 0.08)]. All FST non-responders progressed to undergo KRT showing sensitivity and specificity of 66.67% and 100% at 2 h (AUROC- 0.87) and 85% and 100% at 6 h (AUROC- 0.89) respectively.

CONCLUSIONS

FST is a simple bedside tool with robust predictive value in detecting kidney impairment progression in children and can be utilized in PICU for assessing tubular dysfunction. The diagnostic accuracy of FST was comparable to that of urine and serum cystatin-C. Further studies can be done on a larger cohort for better generalizability.

Determination of Urinary Neutrophil Gelatinase-Associated Lipocalin (uNGAL) Reference Intervals in Healthy Adult and Pediatric Individuals Using a Particle-Enhanced Turbidimetric Immunoassay

Background: The current gold standards for diagnosing acute kidney injury (AKI) are an increase in serum creatinine and a decrease in urine output, which are inadequate for rapid diagnosis. Neutrophil gelatinase-associated lipocalin (NGAL) is a 25-kDa protein produced and secreted by injured kidney tubule epithelial cells, and can serve as an early urinary biomarker for AKI. ProNephro AKI (NGAL) is an immunoassay for the quantitative determination of NGAL in urine (uNGAL) that recently received FDA clearance. A multisite, cross-sectional study was conducted to establish reference intervals for uNGAL in apparently healthy individuals. Methods: Urine samples were collected from apparently healthy individuals aged ≥3 months who met all inclusion criteria and no exclusion criteria. Specimens were temporarily stored at room temperature or 2-8 °C, then transferred into urinalysis tubes before being frozen and shipped for testing. uNGAL testing was performed using the ProNephro AKI (NGAL) immunoassay on a Roche cobas c501 analyzer. Results: Of the 688 individuals screened, 677 were eligible, and 629 (91.4%) of those were deemed evaluable. The 95th and 97.5th percentile uNGAL values for all pediatric participants were below the clinical cutoff of 125 ng/mL. uNGAL values were statistically significantly higher for female vs. male participants in both adult (p = 0.003) and pediatric groups (p < 0.001), while differences were not statistically significant for age, site location, race, or ethnicity. Conclusions: This study provides normal reference intervals for uNGAL with the ProNephro AKI (NGAL) clinical chemistry immunoassay that may be useful for interpreting patient results.

Utility of plasma suPAR to identify AKI and sepsis associated AKI in critically ill children

Current biomarkers for sepsis-associated acute kidney injury (SA-AKI) lack specificity. The role of soluble urokinase plasminogen activator receptor (suPAR) in discriminating AKI and SA-AKI in children remains elusive. This prospective multicenter study was conducted in critically ill children cohorts using a derivation-validation design, and plasma samples were collected within first 24 h after admission. Plasma suPAR was independently associated with AKI, SA-AKI, and PICU mortality, even after adjustment for confounding variables. This multiclass classification model had the micro-average AUC of 0.89 with specificity of 97.6% for discriminating non-septic AKI, and specificity of 99.0% for discriminating SA-AKI, based on the cut-off values of 1.5 and 2.3-fold baseline in serum creatinine (SCr) and 4.5 and 11.2 ng/mL in plasma suPAR. The multiclass classification model provides the cutoffs for plasma suPAR and SCr and specifically discriminates critically ill children at high risk of non-septic AKI and SA-AKI, which can facilitate clinical utility.

Artificial intelligence and predictive models for early detection of acute kidney injury: transforming clinical practice

Acute kidney injury (AKI) presents a significant clinical challenge due to its rapid progression to kidney failure, resulting in serious complications such as electrolyte imbalances, fluid overload, and the potential need for renal replacement therapy. Early detection and prediction of AKI can improve patient outcomes through timely interventions. This review was conducted as a narrative literature review, aiming to explore state-of-the-art models for early detection and prediction of AKI. We conducted a comprehensive review of findings from various studies, highlighting their strengths, limitations, and practical considerations for implementation in healthcare settings. We highlight the potential benefits and challenges of their integration into routine clinical care and emphasize the importance of establishing robust early-detection systems before the introduction of artificial intelligence (AI)-assisted prediction models. Advances in AI for AKI detection and prediction are examined, addressing their clinical applicability, challenges, and opportunities for routine implementation.

Derivation and Validation of an Optimal Neutrophil Gelatinase-Associated Lipocalin Cutoff to Predict Stage 2/3 Acute Kidney Injury (AKI) in Critically Ill Children

Introduction

Acute kidney injury (AKI) defined by changes in serum creatinine (SCr), or oliguria is associated with increased morbidity and mortality in children who are critically ill. We derived and validated a clinical cutoff value for urine neutrophil gelatinase-associated lipocalin (NGAL), in a prospective multicenter study of children who were critically ill. We report the clinical performance of urine NGAL (uNGAL) to aid in pediatric AKI risk assessment.

Methods

Eligible subjects were aged ≥ 90 days to < 22 years, admitted to an intensive care unit (ICU), and had 1 or more of the following: mechanical ventilation, vasoactive medication administration, solid organ or bone marrow transplantation, or hypotension within 24-hours of admission. uNGAL was assessed within 24-hours of admission. The primary outcome was SCr-based stage 2/3 AKI presence at 48- to 72-hours.

Results

Twenty-five (12.3%) derivation study patients had stage 2/3 AKI at 48- to 72-hours. uNGAL concentration of 125 ng/ml was the optimal cutoff. Forty-seven (9.1%) validation study patients had stage 2/3 AKI at 48- to 72-hours. The area under the curve of a receiver operator characteristics curve (AUC-ROC) for uNGAL performance was 0.83 (95% confidence interval [CI]: 0.77-0.90). Performance characteristics were sensitivity 72.3% (95% CI: 57.4%-84.4%), specificity 86.3% (95% CI: 82.8%-89.3%), positive predictive value 34.7% (95% CI: 28.5%-41.5%), and negative predictive value 96.9% (95% CI: 95.1%-98.0%).

Conclusion

These prospective, pediatric, multicenter studies demonstrate that uNGAL in the first 24-hours performs very well to predict Kidney Disease Improving Global Outcomes (KDIGO) stage 2/3 AKI at 48- to 72-hours into an ICU course. We suggest that a uNGAL cut point of 125 ng/ml can aid in the risk assessment for stage 2/3 AKI persistence or development.

The multifaceted role of insulin-like growth factor binding protein 7

Insulin-like growth factor binding protein 7 (IGFBP7) serves as a crucial extracellular matrix protein, exerting pivotal roles in both physiological and pathological processes. This comprehensive review meticulously delineates the structural attributes of IGFBP7, juxtaposing them with other members within the IGFBP families, and delves into the expression patterns across various tissues. Furthermore, the review thoroughly examines the multifaceted functions of IGFBP7, encompassing its regulatory effects on cell proliferation, apoptosis, and migration, elucidating the underlying mechanistic pathways. Moreover, it underscores the compelling roles in tumor progression, acute kidney injury, and reproductive processes. By rigorously elucidating the diverse functionalities and regulatory networks of IGFBP7 across various physiological and pathological contexts, this review aims to furnish a robust theoretical framework and delineate future research trajectories for leveraging IGFBP7 in disease diagnosis, therapeutic interventions, and pharmaceutical innovations.

Metal concentrations and KIM-1 levels in school-aged children: a cross-sectional study

Environmental exposure to heavy metals and metalloids, originating from sources such as mining and manufacturing activities, has been linked to adverse renal effects. This cross-sectional study assessed children's exposure to these elements and its association with urinary kidney injury molecule-1 (KIM-1). We analyzed data from 99 school-aged children residing in nine localities within the state of Colima, Mexico, during the latter half of 2023. Levels of 23 metals/metalloids and urinary KIM-1 were measured using inductively coupled plasma mass spectrometry (ICP-MS) and enzyme-linked immunosorbent assay, respectively. Detectable levels of these contaminants were found in over 91% of participants, with varied exposure profiles observed across locations ( p = 0.019). After adjusting for confounding factors like gender, age, and locality, higher levels of six metals/metalloids (boron, cadmium, cesium, lithium, selenium, zinc) were significantly associated with increased KIM-1 levels. Tailored mitigation efforts are crucial to protect children from regional pollutant burdens. However, limitations exist, as our study did not capture all potential factors influencing heavy metal/metalloid and KIM-1 levels.

Biomarkers vs Machines: The Race to Predict Acute Kidney Injury

BACKGROUND

Acute kidney injury (AKI) is a serious complication affecting up to 15% of hospitalized patients. Early diagnosis is critical to prevent irreversible kidney damage that could otherwise lead to significant morbidity and mortality. However, AKI is a clinically silent syndrome, and current detection primarily relies on measuring a rise in serum creatinine, an imperfect marker that can be slow to react to developing AKI. Over the past decade, new innovations have emerged in the form of biomarkers and artificial intelligence tools to aid in the early diagnosis and prediction of imminent AKI.

CONTENT

This review summarizes and critically evaluates the latest developments in AKI detection and prediction by emerging biomarkers and artificial intelligence. Main guidelines and studies discussed herein include those evaluating clinical utilitiy of alternate filtration markers such as cystatin C and structural injury markers such as neutrophil gelatinase-associated lipocalin and tissue inhibitor of metalloprotease 2 with insulin-like growth factor binding protein 7 and machine learning algorithms for the detection and prediction of AKI in adult and pediatric populations. Recommendations for clinical practices considering the adoption of these new tools are also provided.

SUMMARY

The race to detect AKI is heating up. Regulatory approval of select biomarkers for clinical use and the emergence of machine learning algorithms that can predict imminent AKI with high accuracy are all promising developments. But the race is far from being won. Future research focusing on clinical outcome studies that demonstrate the utility and validity of implementing these new tools into clinical practice is needed.

Mechanism and clinical role of TIMP-2 and IGFBP-7 in cardiac surgery-associated acute kidney injury: A review

Acute kidney injury (AKI) is a common postoperative complication, but there is still a lack of accurate biomarkers. Cardiac surgery-associated AKI is the most common cause of major-surgery-related AKI, and patients requiring renal replacement therapy have high mortality rates. Early diagnosis, intervention, and management are crucial for improving patient prognosis. However, diagnosing AKI based solely on changes in serum creatinine level and urine output is insufficient, as these changes often lag behind actual kidney damage, making early detection challenging. Biomarkers such as tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor-binding protein-7 (IGFBP-7) have been found to be significant predictors of moderate-to-severe AKI when combined with urine content analysis. This article reviews the mechanism of biomarkers TIMP-2 and IGFBP-7 in AKI and provides a comprehensive overview of the clinical effects of TIMP-2 and IGFBP-7 in cardiac surgery-associated AKI, including prediction, diagnosis, and progression.

Comparative quantitation of liver-type fatty acid-binding protein localizations in liver injury and non-pathological liver tissue in dogs

Background and Aim

Liver injury results in the production of free radicals that can lead to hepatocytic degeneration, cirrhosis, and hepatocellular carcinoma (HCC). Liver-fatty acid-binding protein (L-FABP) is highly expressed in hepatocytes and is a key regulator of hepatic lipid metabolism and antioxidant characteristics. Interestingly, the increase in L-FABP expression could be used as a novel marker of liver injury. Therefore, this study aimed to use immunohistochemical techniques to investigate the expression of L-FABP in dogs with liver injury compared with dogs with non-pathological liver.

Materials and Methods

Liver tissue samples were collected from dog biopsy specimens at the Veterinary Diagnostic Laboratory at the Faculty of Veterinary Medicine, Chiang Mai University. The tissues were prepared for immunohistochemistry and the expression and localization of L-FABP were investigated using one-way analysis of variance.

Results

Immunohistochemical analysis showed that L-FABP was strongly expressed in the hepatocytes of dogs with lipidosis and HCC when compared with that in normal liver. Semi-quantitative immunohistochemistry evaluation showed the percentage of protein expression of L-FABP 0.023 ± 0.027 in the non-pathological liver. The percentage of L-FABP protein expression in lipidosis and HCC was found to be 8.517 ± 1.059 and 17.371 ± 4.026, respectively.

Conclusion

L-FABP expression in dogs with liver injuries was significantly higher than that in dogs with non-pathological liver injury (p = 0.05). These results suggest that L-FABP has the potential as a novel marker for specific diagnosis and prognosis of dogs with liver injury.

KIM-1, IL-18, and NGAL, in the Machine Learning Prediction of Kidney Injury among Children Undergoing Hematopoietic Stem Cell Transplantation-A Pilot Study

Children undergoing allogeneic hematopoietic stem cell transplantation (HSCT) are prone to developing acute kidney injury (AKI). Markers of kidney damage: kidney injury molecule (KIM)-1, interleukin (IL)-18, and neutrophil gelatinase-associated lipocalin (NGAL) may ease early diagnosis of AKI. The aim of this study was to assess serum concentrations of KIM-1, IL-18, and NGAL in children undergoing HSCT in relation to classical markers of kidney function (creatinine, cystatin C, estimated glomerular filtration rate (eGFR)) and to analyze their usefulness as predictors of kidney damage with the use of artificial intelligence tools. Serum concentrations of KIM-1, IL-18, NGAL, and cystatin C were assessed by ELISA in 27 children undergoing HSCT before transplantation and up to 4 weeks after the procedure. The data was used to build a Random Forest Classifier (RFC) model of renal injury prediction. The RFC model established on the basis of 3 input variables, KIM-1, IL-18, and NGAL concentrations in the serum of children before HSCT, was able to effectively assess the rate of patients with hyperfiltration, a surrogate marker of kidney injury 4 weeks after the procedure. With the use of the RFC model, serum KIM-1, IL-18, and NGAL may serve as markers of incipient renal dysfunction in children after HSCT.

Kidney fibrosis: Emerging diagnostic and therapeutic strategies

An increasing number of patients worldwide suffers from chronic kidney disease (CKD). CKD is accompanied by kidney fibrosis, which affects all compartments of the kidney, i.e., the glomeruli, tubulointerstitium, and vasculature. Fibrosis is the best predictor of progression of kidney diseases. Currently, there is no specific anti-fibrotic therapy for kidney patients and invasive renal biopsy remains the only option for specific detection and quantification of kidney fibrosis. Here we review emerging diagnostic approaches and potential therapeutic options for fibrosis. We discuss how translational research could help to establish fibrosis-specific endpoints for clinical trials, leading to improved patient stratification and potentially companion diagnostics, and facilitating and optimizing development of novel anti-fibrotic therapies for kidney patients.