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  • Title: Plasma Neutrophil Elastase and Elafin as Prognostic Biomarker for Acute Respiratory Distress Syndrome: A Multicenter Survival and Longitudinal Prospective Observation Study.
    Author: Wang T, Zhu Z, Liu Z, Yi L, Yang Z, Bian W, Chen W, Wang S, Li G, Li A, Martin GS, Zhu X.
    Journal: Shock; 2017 Aug; 48(2):168-174. PubMed ID: 28187039.
    Abstract:
    BACKGROUND: Neutrophil elastase (HNE) is a destructive enzyme and plays crucial roles in the pathophysiology of acute respiratory distress syndrome (ARDS). Endogenous proteinase inhibitors elafin (PI3) is important to protect against lung tissue destruction. We proposed to examine whether HNE and PI3 serve as prognostic biomarkers for ARDS. METHODS: This study is a survival and longitudinal analysis of plasma profiles of HNE and PI3 in ARDS patients from a multicenter prospective observational cohort in Beijing, China. Plasma samples were collected on day-1, day-3, and day-7 of study enrollment. RESULTS: HNE levels were higher in ARDS non-survivors than survivors, whereas PI3 showed opposite direction for all three measurements (P < 0.01 for all). Patients with HNE level above median and PI3 level below median values had the lowest survival probability and died the fastest. There was a significant longitudinal effect of HNE levels and PI3 level on mortality. Receiver-operating characteristic analysis demonstrated combination of HNE and PI3 had the discrimination ability for 28-day mortality (area under the receiver-operating characteristic curve [AUC]: 0.76), better than the combination of Berlin categories and APACHE II (AUC: 0.63). The addition of HNE and PI3 to Berlin categories and APACHE II has significantly improved the prognostic discrimination ability (AUC: 0.81, P < 0.0001). CONCLUSIONS: Imbalance between HNE and PI3 levels in ARDS patients was associated with ARDS mortality. By combining these biomarkers with Berlin categories and APACHE II, prognostic power of ARDS was greatly improved. Circulation levels of HNE and PI3 may have the potential to predict ARDS mortality and better inform clinicians about ARDS mortality risk.
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