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.

Nitrous oxide abuse direct measurement for diagnosis and follow-up: update on kinetics and impact on metabolic pathways.

Recreational use of nitrous oxide (N2O) has become a major health issue worldwide, with a high number of clinical events, especially in neurology and cardiology. It is essential to be able to detect and monitor N2O abuse to provide effective care and follow-up to these patients. Current recommendations for detecting N2O in cases of recreational misuse and consumption markers are lacking. We aimed to update current knowledge through a review of the literature on N2O measurement and kinetics. We reviewed the outcomes of experiments, whether in preclinical models (in vitro or in vivo), or in humans, with the aim to identify biomarkers of intoxication as well as biomarkers of clinical severity, for laboratory use. Because N2O is eliminated 5 min after inhalation, measuring it in exhaled air is of no value. Many studies have found that urine and blood matrices concentrations are connected to ambient concentrations, but there is no similar data for direct exposure. There have been no studies on N2O measurement in direct consumers. Currently, patients actively abusing N2O are monitored using effect biomarkers (biomarkers related to the effects of N2O on metabolism), such as vitamin B12, homocysteine and methylmalonic acid.

Urinary Biomarkers of Tubular Health and Risk for Kidney Function Decline or Mortality in Diabetes.

INTRODUCTION: Diabetes is a leading cause of end-stage kidney disease (ESKD). Biomarkers of tubular health may prognosticate chronic kidney disease (CKD) progression beyond estimated glomerular filtration rate (eGFR) and urine albumin-to-creatinine ratio (UACR). METHODS: We examined associations of five urinary biomarkers of tubular injury and repair (NGAL, KIM-1, IL-18, MCP-1, YKL-40) with kidney function decline (first occurrence of a decrease in eGFR ≥30 mL/min/1.73 m2 if randomization eGFR ≥60 or ≥50% if randomization eGFR <60; ESKD) and all-cause mortality among 1,135 VA NEPHRON-D trial participants with baseline UACR ≥300 mg/g and available urine samples. Covariates included age, sex, race, BMI, systolic BP, HbA1c, treatment arm, eGFR, and UACR. In a subset of participants with 12-month samples (n = 712), we evaluated associations of KIM-1, MCP-1, and YKL-40 change (from baseline to 12 months) with eGFR decline (from 12 months onward). RESULTS: At baseline, mean age was 65 years, mean eGFR was 56 mL/min/1.73 m2, and median UACR was 840 mg/g. Over a median of 2.2 years, 13% experienced kidney function decline and 9% died. In fully adjusted models, the highest versus lowest quartiles of MCP-1 and YKL-40 were associated with 2.18- and 1.76-fold higher risks of kidney function decline, respectively. One-year changes in KIM-1, MCP-1, and YKL-40 were not associated with subsequent eGFR decline. Higher baseline levels of NGAL, IL-18, MCP-1, and YKL-40 levels (per 2-fold higher) were independently associated with 10-40% higher risk of mortality. CONCLUSION: Among Veterans with diabetes and CKD, urinary biomarkers of tubular health were associated with kidney function decline and mortality.