4 research outputs found

    Relation of Left Ventricular Mass and Infarct Size in Anterior Wall ST-Segment Elevation Acute Myocardial Infarction (from the EMBRACE STEMI Clinical Trial)

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    Biomarker measures of infarct size and myocardial salvage index (MSI) are important surrogate measures of clinical outcomes after a myocardial infarction. However, there is variability in infarct size unaccounted for by conventional adjustment factors. This post hoc analysis of Evaluation of Myocardial Effects of Bendavia for Reducing Reperfusion Injury in Patients With Acute Coronary Events (EMBRACE) ST-Segment Elevation Myocardial Infarction (STEMI) trial evaluates the association between left ventricular (LV) mass and infarct size as assessed by areas under the curve for creatine kinase-MB (CK-MB) and troponin I release over the first 72 hours (CK-MB area under the curve [AUC] and troponin I [TnI] AUC) and the MSI. Patients with first anterior STEMI, occluded left anterior descending artery, and available LV mass measurement in EMBRACE STEMI trial were included (n = 100) (ClinicalTrials.govNCT01572909). MSI, end-diastolic LV mass on day 4 cardiac magnetic resonance, and CK-MB and troponin I concentrations were evaluated by a core laboratory. After saturated multivariate analysis, dominance analysis was performed to estimate the contribution of each independent variable to the predicted variance of each outcome. In multivariate models that included age, gender, body surface area, lesion location, smoking, and ischemia time, LV mass remained independently associated with biomarker measures of infarct size (CK-MB AUC p = 0.02, TnI AUC p = 0.03) and MSI (p = 0.003). Dominance analysis demonstrated that LV mass accounted for 58%, 47%, and 60% of the predicted variances for CK-MB AUC, TnI AUC, and MSI, respectively. In conclusion, LV mass accounts for approximately half of the predicted variance in biomarker measures of infarct size. It should be considered as an adjustment variable in studies evaluating infarct size

    Integrated Kidney Exosome Analysis for the Detection of Kidney Transplant Rejection

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    Kidney transplant patients require life-long surveillance to detect allograft rejection. Repeated biopsy, albeit the clinical gold standard, is an invasive procedure with the risk of complications and comparatively high cost. Conversely, serum creatinine or urinary proteins are noninvasive alternatives but are late markers with low specificity. We report a urine-based platform to detect kidney transplant rejection. Termed iKEA (integrated kidney exosome analysis), the approach detects extracellular vesicles (EVs) released by immune cells into urine; we reasoned that T cells, attacking kidney allografts, would shed EVs, which in turn can be used as a surrogate marker for inflammation. We optimized iKEA to detect T-cell-derived EVs and implemented a portable sensing system. When applied to clinical urine samples, iKEA revealed high level of CD3-positive EVs in kidney rejection patients and achieved high detection accuracy (91.1%). Fast, noninvasive, and cost-effective, iKEA could offer new opportunities in managing transplant recipients, perhaps even in a home setting
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