| Autor: |
Sarah Gisewhite, Ian J. Stewart, Greg Beilman, Elizabeth Lusczek |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
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| Zdroj: |
Critical Care, Vol 25, Iss 1, Pp 1-14 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
1364-8535 |
| DOI: |
10.1186/s13054-021-03544-2 |
| Popis: |
Abstract Background Traditionally, patient risk scoring is done by evaluating vital signs and clinical severity scores with clinical intuition. Urinary biomarkers can add objectivity to these models to make risk prediction more accurate. We used metabolomics to identify prognostic urinary biomarkers of mortality or need for renal replacement therapy (RRT). Additionally, we assessed acute kidney injury (AKI) diagnosis, injury severity score (ISS), and AKI stage. Methods Urine samples (n = 82) from a previous study of combat casualties were evaluated using proton nuclear magnetic resonance (1H-NMR) spectroscopy. Chenomx software was used to identify and quantify urinary metabolites. Metabolite concentrations were normalized by urine output, autoscaled, and log-transformed. Partial least squares discriminant analysis (PLS-DA) and statistical analysis were performed. Receiver operating characteristic (ROC) curves were used to assess prognostic utility of biomarkers for mortality and RRT. Results Eighty-four (84) metabolites were identified and quantified in each urine sample. Of these, 11 were identified as drugs or drug metabolites and excluded. The PLS-DA models for ISS and AKI diagnosis did not have acceptable model statistics. Therefore, only mortality/RRT and AKI stage were analyzed further. Of 73 analyzed metabolites, 9 were significantly associated with mortality/RRT (p |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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