Measuring XXXX for Infection Prediction in @entity510 .

@entity1 @entity55 @entity510 @entity281 @entity580 @entity5475 @entity204 @entity293
UNASSIGNED: @entity510 ( @entity510 ) is associated with high rates of mortality and morbidity. @entity580 , such as @entity55 or @entity293 , are among the main causes of worsening outcomes and @entity204 . The aim of this study was to discover a biomarker to predict @entity281 in @entity510 @entity1 . For this purpose, the plasma of infected and noninfected @entity1 was compared using quantitative mass spectrometry. The most interesting differentially expressed proteins were selected for validation by immunoassays on plasma samples taken from @entity1 (n = 81) over 10 days of hospitalization. Predictive performances were established using Mann-Whitney U tests and receiver operating characteristic curves. Quantitative proteomics identified 17 significantly regulated proteins. Of these, levels of @entity5475 ( @entity5475 ) were significantly higher in infected @entity1 (p < 0.007). ELISA confirmed that the concentrations were significantly higher (p < 0.002) already at hospital admission in @entity1 who subsequently developed an @entity281 during their hospitalization, (AUC of 76%) for a cutoff value of 90.9  g/mL. Our data suggested that measuring @entity5475 could be an efficient means of detecting @entity1 susceptible of developing an @entity281 during hospitalization after an @entity510 . Its predictive capacity could lead to earlier antibiotherapy, improved @entity1 management, and potentially better long-term outcomes.
