Abstract
Early diagnosis of sepsis and its severity stratification at admission is critical to improve patient outcomes and to ensure the optimal use of health care resources. In order to assess the diagnostic potential of mid-regional pro-adrenomedullin (MR-proADM) in septic paediatric patients in comparison with procalcitonin (PCT), and to evaluate the usefulness of a single early determination of MR-proADM as a stratification and severity prediction tool, a prospective observational study was conducted. Seventy-three paediatric patients with a suspicion of sepsis were included. A single blood test was carried out at initial time to analyse infection biomarkers. PCT values were significantly higher in septic patients in comparison with non-septic patients (p = 0.03) with an AUC of 0.748 (p = 0.003). Levels of MR-proADM significantly increased in patients with severe sepsis (p = 0.048), with an AUC of 0.729 (p = 0.013). MR-proADM showed a positive correlation with pSOFA, PRISM III, and PELOD-2 severity scores. Levels of MR-proADM were significantly higher in patients who required vasoactive drugs (p = 0.02) or presented renal dysfunction (p = 0.004).Conclusion: PCT appeared to be superior to MR-proADM in diagnosing sepsis. Determining MR-proADM plasma levels at the initial phase of sepsis could be a useful tool for sepsis stratification and morbidity prediction before organ failure occurs. The present results need to be assessed with larger sample size studies.What is Known:•CRP and PCT are already included in clinical practice to assess sepsis and estimate disease severity, although their sensitivity and specificity are lower than desired.•ADM is a protein that has immune and vascular modulation actions, and its blood levels are increased in adult and paediatric sepsis.•ADM is a promising tool for early diagnosis and prognostic assessment in adult sepsis.What is New:•PCT appeared to be superior to MR-proADM in diagnosing paediatric sepsis.•MR-proADM plasma levels could be a useful tool for paediatric sepsis stratification and morbidity prediction.
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