In: PLOS One
13(5), e0197637
[PDF, 1MB]
Abstract
Background: Sepsis is now operationally defined as life-threatening organ dysfunction caused by an infection, identified by an acute change in SOFA-Score of at least two points, including clinical chemistry such as creatinine or bilirubin concentrations. However, little knowledge exists about organ-specific microRNAs as potentially new biomarkers. Accordingly, we tested the hypotheses that micro-RNA-122, the foremost liver-related micro-RNA (miR), 1) discriminates between sepsis and infection, 2) is an early predictor for mortality, and 3) improves the prognostic value of the SOFA-score. Methods: We analyzed 108 patients with sepsis (infection + increase SOFA-Score >= 2) within the first 24h of ICU admission and as controls 20 patients with infections without sepsis (infection + SOFA-Score <= 1). Total circulating miR was isolated from serum and relative miR-122 expression was measured (using spiked-in cel-miR-54) and associated with 30-day survival. Results: 30-day survival of the sepsis patients was 63%. miR-122 expression was 40-fold higher in non-survivors (p = 0.001) and increased almost 6-fold in survivors (p = 0.013) compared to controls. miR-122 serum-expression discriminated both between sepsis vs. infection (AUC 0.760, sensitivity 58.3%, specificity 95%) and survivors vs. non-survivors (AUC 0.728, sensitivity 42.5%, specificity 94%). Multivariate Cox-regression analysis revealed miR-122 (HR 4.3;95%-CI 2.0-8.9, p<0.001) as independent prognostic factor for 30-day mortality. Furthermore, the predictive value for 30-day mortality of the SOFA-Score (AUC 0.668) was improved by adding miR-122 (AUC 0.743;net reclassification improvement 0.37, p<0.001;integrated discrimination improvement 0.07, p = 0.007). Conclusions: Increased miR-122 serum concentration supports the discrimination between infection and sepsis, is an early and independent risk factor for 30-day mortality, and improves the prognostic value of the SOFA-Score, suggesting a potential role for miR-122 in sepsis-related prediction models.
Dokumententyp: | Zeitschriftenartikel |
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Fakultät: | Medizin |
Themengebiete: | 600 Technik, Medizin, angewandte Wissenschaften > 610 Medizin und Gesundheit |
URN: | urn:nbn:de:bvb:19-epub-63308-6 |
ISSN: | 1932-6203 |
Sprache: | Englisch |
Dokumenten ID: | 63308 |
Datum der Veröffentlichung auf Open Access LMU: | 19. Jul. 2019, 12:13 |
Letzte Änderungen: | 04. Nov. 2020, 13:41 |