ArticleJournal of pediatric gastroenterology and nutrition2026
Acute kidney injury markers in pediatric pancreatitis: Differentiating disease states and assessing severity.
Article in Journal of pediatric gastroenterology and nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectivesAcute kidney injury (AKI) is a complication commonly observed in adults with acute pancreatitis (AP) but remains poorly studied in pediatric patients. We investigated the utility of AKI biomarkers-kidney injury molecule-1 (KIM-1), lipocalin 2 (NGAL), cystatin-C (CYS-C), and renalase (RNLS) in acute and chronic pancreatitis (CP), and to assess AP severity, and evaluate kidney function.
methodsPlasma and urine samples were collected from children with AP (n = 49), CP (n = 50), and healthy controls (HC; n = 20). AKI biomarkers levels were measured using enzyme-linked immunosorbent assays (ELISA). AP patients were categorized into two groups: mild AP (MAP) and moderate/severe AP (SAP). Kidney function was evaluated using plasma creatinine (pCre) and CYS-C-based enhanced glomerular filtration rate (eGFR) formulas.
resultsPlasma KIM-1 and pCYS-C were elevated in AP versus CP and HCs (p < 0.0001). Urinary NGAL (uNGAL) was elevated in AP subjects, with 14% of patients exceeding the value of 125 ng/mL. Plasma A-RNLS remained same between AP and HCs (p = 0.78) but was elevated in CP cohort (p < 0.0001). However, pF-RNLS levels declined in AP compared to HCs and CP (p < 0.0001). SAP subjects (20% of AP cohort) had elevated pKIM-1 and pCYS-C compared to MAP (p = 0.002, p = 0.003). eGFR declined in AP subjects with 84% of AP patients showing CYS-C eGFR <90 mL/min/1.73 m². Plasma CYS-C, pA-RNLS, and pF-RNLS predicted AP from CP with area under the receiving operating curve of 0.86 (95% CL).
conclusionElevated pKIM-1, pCYS-C, and uNGAL, along with declining pF-RNLS, are helpful in distinguishing pediatric AP from CP. Quantifying the Levels of pKIM-1 and pCYS-C within the first 48 h can help predict development of SAP.
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