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J Pediatr Gastroenterol Nutr ; 71(4): 536-542, 2020 10.
Artigo em Inglês | MEDLINE | ID: mdl-32541203

RESUMO

OBJECTIVES: The aim of the study was to validate and optimize a severity prediction model for acute pancreatitis (AP) and to examine blood urea nitrogen (BUN) level changes from admission as a severity predictor. STUDY DESIGN: Patients from 2 hospitals were included for the validation model (Children's Hospital of the King's Daughters and Children's National Hospital). Children's Hospital of the King's Daughters and Cincinnati Children's Hospital Medical Center data were used for analysis of BUN at 24 to 48 hours. RESULTS: The validation cohort included 73 patients; 22 (30%) with either severe or moderately severe AP, combined into the all severe AP (SAP) group. Patients with SAP had higher BUN (P = 0.002) and lower albumin (P = 0.005). Admission BUN was confirmed as a significant predictor (P = 0.005) of SAP (area under the receiver operating characteristic [AUROC] 0.73, 95% confidence interval [CI] 0.60-0.86). Combining BUN (P = 0.005) and albumin (P = 0.004) resulted in better prediction for SAP (AUROC 0.83, 95% CI 0.72-0.94). A total of 176 AP patients were analyzed at 24-48 hours; 39 (22%) met criteria for SAP. Patients who developed SAP had a significantly higher BUN (P < 0.001) after 24 hours. Elevated BUN levels within 24 to 48 hours were independently predictive of developing SAP (AUROC: 0.76, 95% CI: 0.66-0.85). Patients who developed SAP had a significantly smaller percentage decrease in BUN from admission to 24 to 48 hours (P = 0.002). CONCLUSION: We externally validated the prior model with admission BUN levels and further optimized it by incorporating albumin. We also found that persistent elevation of BUN is associated with development of SAP. Our model can be used to risk stratify patients with AP on admission and again at 24 to 48 hours.


Assuntos
Pancreatite , Doença Aguda , Biomarcadores , Nitrogênio da Ureia Sanguínea , Criança , Humanos , Pancreatite/diagnóstico , Prognóstico , Curva ROC , Estudos Retrospectivos , Índice de Gravidade de Doença
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