Serum and urinary biomarkers to predict acute kidney injury in premature infants: a systematic review and meta-analysis of diagnostic accuracy

Gut Microbiota and Neonatal Acute Kidney Injury

OBJECTIVE

 To characterize the relationship between gut microbiota and neonatal acute kidney injury biomarkers based on the gut-kidney axis.

STUDY DESIGN

 The Pubmed database was primarily searched to include relevant literature on gut microbiota and neonatal acute kidney injury biomarkers, which was subsequently organized and analyzed and a manuscript was written.

RESULTS

 Gut microbiota was associated with neonatal acute kidney injury biomarkers. These biomarkers included TIMP-2, IGFBP-7, VEGF, calbindin, GST, B2MG, ghrelin, and clusterin.

CONCLUSION

 The gut microbiota is strongly associated with neonatal acute kidney injury biomarkers, and controlling the gut microbiota may be a potential target for ameliorating neonatal acute kidney injury.

KEY POINTS

· There is a bidirectional association between gut microbiota and AKI.. · Gut microbiota is closely associated with biomarkers of nAKI.. · Manipulation of gut microbiota may improve nAKI..

Risk factors for acute kidney injury in very-low birth weight newborns: a systematic review with meta-analysis

This study aims to analyze the main risk factors for acute kidney injury in the subgroup of very-low birth weight newborns, using the diagnosing criteria of the Kidney Disease Improving Global Outcomes (KDIGO) or the Acute Kidney Injury Network (AKIN). A systematic review of the literature was performed on the EMBASE® and PubMed® platforms. Studies that evaluated the risk factors for developing AKI in VLBW newborns were included. For the meta-analysis, we only included the risk factors that were associated with AKI in the univariate analysis of at least two studies. After an initial screening, abstract readings, and full-text readings, 10 articles were included in the systematic review and 9 in the meta-analysis. The incidence of AKI varied from 11.6 to 55.8%. All the studies have performed multivariate analysis, and the risk factors that appeared most were PDA and hemodynamic instability (use of inotropes or hypotension), sepsis, and invasive mechanical ventilation. After the meta-analysis, only cesarian delivery did not show an increased risk of AKI, all the other variables remained as important risk factors. Moreover, in our meta-analysis, we found a pooled increased risk of death in newborns with AKI almost 7 times.  Conclusion: AKI in VLBW has several risk factors and must be seen as a multifactorial disease. The most common risk factors were PDA, hemodynamic instability, sepsis, and invasive mechanical ventilation. What is known: • Acute kidney injury is associated with worst outcomes in all ages. It´s prevention can help diminish mortality. What is new: • A synthesis of the main risk factors associated with AKI in very low birth weight newborns.

Artificial intelligence in early detection and prediction of pediatric/neonatal acute kidney injury: current status and future directions

Acute kidney injury (AKI) has a significant impact on the short-term and long-term clinical outcomes of pediatric and neonatal patients, and it is imperative in these populations to mitigate the pathways leading to AKI and be prepared for early diagnosis and treatment intervention of established AKI. Recently, artificial intelligence (AI) has provided more advent predictive models for early detection/prediction of AKI utilizing machine learning (ML). By providing strong detail and evidence from risk scores and electronic alerts, this review outlines a comprehensive and holistic insight into the current state of AI in AKI in pediatric/neonatal patients. In the pediatric population, AI models including XGBoost, logistic regression, support vector machines, decision trees, naïve Bayes, and risk stratification scores (Renal Angina Index (RAI), Nephrotoxic Injury Negated by Just-in-time Action (NINJA)) have shown success in predicting AKI using variables like serum creatinine, urine output, and electronic health record (EHR) alerts. Similarly, in the neonatal population, using the "Baby NINJA" model showed a decrease in nephrotoxic medication exposure by 42%, the rate of AKI by 78%, and the number of days with AKI by 68%. Furthermore, the "STARZ" risk stratification AI model showed a predictive ability of AKI within 7 days of NICU admission of AUC 0.93 and AUC of 0.96 in the validation and derivation cohorts, respectively. Many studies have reported the superiority of using biomarkers to predict AKI in pediatric patients and neonates as well. Future directions include the application of AI along with biomarkers (NGAL, CysC, OPN, IL-18, B2M, etc.) in a Labelbox configuration to create a more robust and accurate model for predicting and detecting pediatric/neonatal AKI.

Urinary Concentration of Renal Biomarkers in Healthy Term Neonates: Gender Differences in GST-pi Excretion

BACKGROUND Serum creatinine, the criterion standard in assessment of renal function, is not reliable for the neonatal period because of its dependence on renal immaturity and maternal creatinine levels. Thus, it is important to study other biomarkers of renal function in neonates. The present study aimed to measure the urinary concentration of renal biomarkers: calbindin, clusterin, GST-pi (glutathione-S-transferase-alpha), KIM-1 (kidney injury molecule 1), MCP-1 (monocyte chemoattractant protein-1), and B2M (beta 2-microglobulin) in healthy term neonates. MATERIAL AND METHODS In the study, we included 80 healthy term neonates - 40 females and 40 males. We collected the neonates' urine on their first day of life. Urinary concentrations of calbindin, clusterin, KIM-1, MCP-1, and B2M were assessed using an immunoassay for kidney toxicology research. Because dilution of the urine affects the concentrations of urinary biomarkers, we normalized them to the concentration of urinary creatinine (Cr) and present them as biomarker/Cr ratios. RESULTS We obtained the following values of the assessed biomarker/Cr ratios (median [Q1-Q3]): calbindin/Cr.: 197.04 (56.25-595.17), KIM-1/Cr: 0.09 (0.04-0.18), MCP-1/Cr: 0.05 (0.02-0.14), B2M/Cr: 126.12 (19.03-342.48), GST-pi/Cr in boys: 1.28 (0.46-3.77), GST-pi/Cr in girls: 8.66 (2.51-27.82), clusterin/Cr: 4.55 (1.79-12.97) ng/mg Cr. CONCLUSIONS We showed the urinary levels of calbindin, clusterin, GST-pi, KIM-1, MCP-1, B2M in white, West Slavic, healthy term neonates. We found that in there is an association between female sex and a higher urinary GST-pi excretion, but urinary excretion of calbindin, clusterin, KIM-1, MCP-1, and B2M is sex-independent. The urinary levels of the assessed biomarkers do not depend on the method of delivery.

Gut microbiota and neonatal acute kidney injury biomarkers

One of the most frequent issues in newborns is acute kidney injury (AKI), which can lengthen their hospital stay or potentially raise their chance of dying. The gut-kidney axis establishes a bidirectional interplay between gut microbiota and kidney illness, particularly AKI, and demonstrates the importance of gut microbiota to host health. Since the ability to predict neonatal AKI using blood creatinine and urine output as evaluation parameters is somewhat constrained, a number of interesting biomarkers have been developed. There are few in-depth studies on the relationships between these neonatal AKI indicators and gut microbiota. In order to gain fresh insights into the gut-kidney axis of neonatal AKI, this review is based on the gut-kidney axis and describes relationships between gut microbiota and neonatal AKI biomarkers.

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

BACKGROUND

Severity of acute kidney injury (AKI) confers higher odds of mortality. Timely recognition and early initiation of preventive measures may help mitigate the injury further. Novel biomarkers may aid in the early detection of AKI. The utility of these biomarkers across various clinical settings in children has not been evaluated systematically.

OBJECTIVE

To synthesize the currently available evidence on different novel biomarkers for the early diagnosis of AKI in pediatric patients.

DATA SOURCES

We searched four electronic databases (PubMed, Web of Science, Embase, and Cochrane Library) for studies published between 2004 and May 2022.

STUDY ELIGIBILITY CRITERIA

Cohort and cross-sectional studies evaluating the diagnostic performance of biomarkers in predicting AKI in children were included.

PARTICIPANTS AND INTERVENTIONS

Participants in the study included children (aged less than 18 years) at risk of AKI.

STUDY APPRAISAL AND SYNTHESIS METHODS

We used the QUADAS-2 tool for the quality assessment of the included studies. The area under the receiver operating characteristics (AUROC) was meta-analyzed using the random-effect inverse-variance method. Pooled sensitivity and specificity were generated using the hierarchical summary receiver operating characteristic (HSROC) model.

RESULTS

We included 92 studies evaluating 13,097 participants. Urinary NGAL and serum cystatin C were the two most studied biomarkers, with summary AUROC of 0.82 (0.77-0.86) and 0.80 (0.76-0.85), respectively. Among others, urine TIMP-2*IGFBP7, L-FABP, and IL-18 showed fair to good predicting ability for AKI. We observed good diagnostic performance for predicting severe AKI by urine L-FABP, NGAL, and serum cystatin C.

LIMITATIONS

Limitations were significant heterogeneity and lack of well-defined cutoff value for various biomarkers.

CONCLUSIONS AND IMPLICATIONS OF KEY FINDINGS

Urine NGAL, L-FABP, TIMP-2*IGFBP7, and cystatin C showed satisfactory diagnostic accuracy in the early prediction of AKI. To further improve the performance of biomarkers, they need to be integrated with other risk stratification models.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO (CRD42021222698). A higher resolution version of the Graphical abstract is available as "Supplementary information".

The Urinary Concentration of Trefoil Factor 3 (TFF3) in the Term and Preterm Neonates

BACKGROUND

Distinguishing between a pathologic state and renal development is important in neonatology. Because the assessment of serum creatinine in neonates is not reliable, better biomarkers are needed. Trefoil factor 3 (TFF3) is proposed as a biomarker of kidney injury. The study aimed to assess its urinary concentration in healthy term and stable preterm neonates.

MATERIAL AND METHODS

The study included 80 term and 20 preterm neonates born in the Department of Perinatology of the University Clinical Hospital in Bialystok. Urine was obtained from the term neonates on the 1st day of life and from the preterm neonates on the 1st, 8th, 15th and 22nd day of life. The urinary concentration of TFF3 was determined using a commercially available immunoassay and was normalized for the urinary creatinine concentration (cr.).

RESULTS

The values of TFF3/cr. were higher in the preterm than in the term neonates (p < 0.05) (median (Q1-Q3): 1486.85 (614.92-3559.18) and 317.29 (68.07-671.40) ng/mg cr.). They did not differ in the subsequent days of the preterm neonates' lives. The ROC curve for TFF3/cr. in the preterm and term neonates showed AUC = 0.751 (cut-off value = 1684.25 ng/mg cr.).

CONCLUSIONS

Prematurity is associated with higher urinary excretion of TFF3. Male gender is associated with an increased urinary TFF3 excretion in term neonates.

Biomarkers for acute kidney injury in children - where are we now?

PURPOSE OF REVIEW

Review the literature over the last 2 years on commonly evaluated biomarkers of acute kidney injury (AKI) and highlight the findings of these biomarkers.

RECENT FINDINGS

Among several studied AKI biomarkers, urine neutrophil gelatinase-associated lipocalin (NGAL) and the combination of urine tissue inhibitor of metalloproteinases-2 (TIMP-2) and insulin-like growth factor binding protein 7 (IGFBP7) have been recently studied most frequently as diagnostic biomarkers of AKI and for AKI risk stratification. Urine NGAL has continued to show good discriminative value to predict and diagnose AKI in childhood. Urine TIMP-2∗IGFBP7 can provide modest improvement to clinical models of AKI.

SUMMARY

Prior research supports that AKI biomarkers may identify AKI at an earlier time point and indicate clinically meaningful tubular injury. More effort should be made to understand if AKI biomarkers can guide treatments and improve outcomes.

Neonatal AKI: An update

Neonatal acute kidney injury (AKI) is a common complication, especially in the neonatal intensive care unit, that is associated with long term consequences and poor outcomes. Early detection and treatment is critical. Currently, neonatal AKI is defined with urinary markers and serum creatinine, with limitations on early detection and individual treatment. There have been numerous biomarkers and risk factor scores that have been studied for their ability to predict neonatal AKI. To move towards personalized medicine, neonatal AKI must be categorized into phenotypes and subphenotypes that fully encapsulate the diverse causes and specific treatments. This review aims to advance our understanding of neonatal AKI detection through the use of biomarkers, subphenotypes, and phenotypes to move towards personalized treatment strategies.

Lipid metabolism and renal function markers in obese adolescents

AIM OF THE STUDY

To investigate the relationship of renal function markers and lipid metabolism parameters in obese adolescents.

MATERIAL AND METHODS

The study comprised 76 children aged 11-17 years, hospitalised due to: obesity (group I - 19 children) or obesity accompanied by obesity-induced hypertension (group II - 30 children) or normosthenic children with a diagnosed tension headaches (control group - 27 children). A subgroup with metabolic syndrome (MS - 16 children) was also separated. Renal function was assessed on the basis of: serum creatinine concentration, glomerular filtration rate estimated using Schwartz eqation (eGFR), determination of plasma and urinary neutrophil gelatinase-associated lipocalin and cystatin C. On the basis of statistical analysis, it was checked whether renal function markers depend on lipid metabolism parameters.

RESULTS

In the study groups mean creatinine concentrations were significantly higher and eGFR values significantly lower than in the control group, but they remained within norm. Differences in plasma and urinary neutrophil gelatinase-associated lipocalin concentrations were not significant. Mean cystatin C concentrations were significantly higher in the group of obese children. Multiple linear regression analysis showed that the most important predictor was: LDL-C for urinary neutrophil gelatinase-associated lipocalin (R2 = 0.42) and TG for eGFR (R2 = 0.44) concentrations in group I; cholesterol for creatinine concentrations in MS group (R2 = 0.44).

CONCLUSIONS

Renal function of the obese adolescents included in the study was normal and the associations with lipid metabolism were poorly expressed.

Serum neutrophil gelatinase-associated lipocalin (NGAL) as a diagnostic tool in pediatric acute appendicitis: a prospective validation study

INTRODUCTION

NGAL has recently been studied as a biomarker in the diagnostic context of pediatric acute appendicitis (PAA), although existing series are scarce and have limited sample sizes.

MATERIALS AND METHODS

A prospective observational study was designed to validate serum NGAL as a diagnostic tool in PAA. This study included 215 patients, divided into 3 groups: (1) patients undergoing major outpatient surgery (n = 63), (2) patients with non-surgical abdominal pain in whom a diagnosis of PAA was excluded (n = 53) and (3) patients with a confirmed diagnosis of PAA (n = 99). Patients in group 3 were divided into complicated or uncomplicated appendicitis. In 201 patients, a serum sample was obtained at the time of diagnosis and NGAL concentration was determined by ELISA. The Kolmogorov-Smirnov test was used to assess normality. Comparative statistical analyses were performed using the Mann-Whitney U test, the Kruskal-Wallis test and the Fisher's exact test. To calculate the discriminative ability of the molecule, the area under the receiver-operating characteristic curves (AUC) was calculated. A p value < 0.05 established statistical significance.

RESULTS

Median (interquartile range) of serum NGAL values were 38.88 (27.15-48.04) ng/mL (group 1), 51.84 (37.33-69.80) ng/mL (group 2) and 65.06 (50.50-86.60) ng/mL (group 3). The AUC (group 2 vs 3) was 0.642 (95% CI 0.542-0.741) (p < 0.001) and the best cutoff point was found to be at 40.97 ng/mL, with a sensitivity of 89% and a specificity of 34.6%. No statistically significant differences in serum NGAL values were found between patients with uncomplicated PAA and those with complicated PAA.

CONCLUSIONS

This prospective validation study with a large sample size confirms that the diagnostic yield of NGAL in the context of PAA is only moderate, and therefore, it should not be used as a unique diagnostic tool. Furthermore, NGAL is not a valid biomarker to discern between uncomplicated and complicated PAA.