Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administration of broad-spectrum antibiotics is associated with improved outcomes, but early recognition of sepsis remains a major challenge. In a two-center cohort study with prospective sample collection from 1400 adult patients in emergency departments suspected of sepsis, we sought to determine the diagnostic and prognostic capabilities of a machine-learning algorithm based on clinical data and a set of uncommonly measured biomarkers. Specifically, we demonstrate that a machine-learning model developed using this dataset outputs a score with not only diagnostic capability but also prognostic power with respect to hospital length of stay (LOS), 30-day mortality, and 3-day inpatient re-admission both in our entire testing cohort and various subpopulations. The area under the receiver operating curve (AUROC) for diagnosis of sepsis was 0.83. Predicted risk scores for patients with septic shock were higher compared with patients with sepsis but without shock (p < 0.0001). Scores for patients with infection and organ dysfunction were higher compared with those without either condition (p < 0.0001). Stratification based on predicted scores of the patients into low, medium, and high-risk groups showed significant differences in LOS (p < 0.0001), 30-day mortality (p < 0.0001), and 30-day inpatient readmission (p < 0.0001). In conclusion, a machine-learning algorithm based on electronic medical record (EMR) data and three nonroutinely measured biomarkers demonstrated good diagnostic and prognostic capability at the time of initial blood culture.

Proteomics analysis of rat brain protein modulations by grape seed extract.

Dietary supplements such as grape seed extract (GSE) enriched in proanthocyanidins (PA) (oligomeric polyphenols) have been suggested to have multiple health benefits, due to antioxidant and other beneficial activities of the PA. However, a systematic analysis of the molecular basis of these benefits has not been demonstrated. Because the brain is vulnerable to age-related oxidative damage and other insults including inflammation, it was hypothesized that rats ingesting GSE would experience changes in expression or modifications of specific brain proteins that might protect against pathologic events. Normal adult female rats were fed diets supplemented with 5% GSE for 6 weeks. Proteomics analysis (2D electrophoresis and mass spectrometry) of brain homogenates from these animals identified 13 proteins that were altered in amount and/or charge. Because many of these changes were quantitatively in the opposite direction from previous findings for the same proteins in either Alzheimer disease or mouse models of neurodegeneration, the data suggest that these identified proteins may mediate the neuroprotective actions of GSE. This is the first identification and quantitation of specific proteins in mammalian tissues modulated by a dietary supplement, as well as the first to demonstrate links of such proteins with any disease.