Evaluation of BCL2 and TNFα as mRNA biomarkers for monitoring the immune response in critically ill children

评估 BCL2 和 TNFα 作为 mRNA 生物标志物在监测危重儿童免疫反应中的应用

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Abstract

BACKGROUND: Hospital acquired infection (HAI) and multiple organ dysfunctions (MODS) remain a leading cause of death in pediatric intensive care unit (PICU) despite the great efforts to control it. OBJECTIVE: Our objective was to assess the mRNA of TNFα and BCL2 for prediction of HAI and/or MODS in our community. PATIENTS AND METHODS: Fifty children, admitted to PICU, were included in the study after exclusion of cases of end-stage renal failure, end-stage liver failure and congenital immune deficiency. Serial Blood samples were collected for complete blood count (CBC) and other routine investigations. Gene expression of (TNFα and BCL2) was quantified using quantitative real time PCR (qRT-PCR). Centers of disease control (CDC) criteria were used to detect HAI, and organ failure index (OFI). Pediatric logistic organ dysfunction (PELOD) and pediatric risk of mortality (PRISM) scores were used for follow up. The results were compared between the group who acquired HAI and who didn't. Gene expression was tested with a ROC curve to detect its ability to predict HAI. MAIN RESULTS: The overall complication (HAI and/or MODS) rate was 52%, Complicated cases had a significantly longer duration of stay in PICU (0.002) and in overall hospital stay (p = 0.013) and a higher death rate (p = 0.000). On day1; TNFα, BCL2 and lymphocytic count were lower in patients who developed complications (p = 0.02, p = 0.000 and p = 0.04, respectively), all had the ability to predict the complications with AUC (0.7, 0.8 and 0.67 respectively). On day 4: TNFα and BCL2 returned to normal levels while the lymphocytic count still lower in complicated cases, p = 0.001 and AUC = 0.73. CONCLUSIONS: TNFα and BCL2 on admission can predict HAI and MODS (AUC = 0.7 and AUC = 0.8), but were of no use in the follow-up, however, the lymphocytic count is a rapid, easy and cheap test to assess the immune state with a good predictive and follow up values.

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