Prediction of multiple infections after severe burn trauma: a prospective cohort study.

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Version: author
Serval ID
serval:BIB_05B445EAC18B
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Prediction of multiple infections after severe burn trauma: a prospective cohort study.
Journal
Annals of Surgery
Author(s)
Yan S., Tsurumi A., Que Y.A., Ryan C.M., Bandyopadhaya A., Morgan A.A., Flaherty P.J., Tompkins R.G., Rahme L.G.
ISSN
1528-1140 (Electronic)
ISSN-L
0003-4932
Publication state
Published
Issued date
2015
Peer-reviewed
Oui
Volume
261
Number
4
Pages
781-792
Language
english
Notes
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, U.S. Gov't, Non-P.H.S.Publication Status: ppublish
Abstract
OBJECTIVE: To develop predictive models for early triage of burn patients based on hypersusceptibility to repeated infections.
BACKGROUND: Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking.
METHODS: Secondary analysis of 459 burn patients (≥16 years old) with 20% or more total body surface area burns recruited from 6 US burn centers. We compared blood transcriptomes with a 180-hour cutoff on the injury-to-transcriptome interval of 47 patients (≤1 infection episode) to those of 66 hypersusceptible patients [multiple (≥2) infection episodes (MIE)]. We used LASSO regression to select biomarkers and multivariate logistic regression to built models, accuracy of which were assessed by area under receiver operating characteristic curve (AUROC) and cross-validation.
RESULTS: Three predictive models were developed using covariates of (1) clinical characteristics; (2) expression profiles of 14 genomic probes; (3) combining (1) and (2). The genomic and clinical models were highly predictive of MIE status [AUROCGenomic = 0.946 (95% CI: 0.906-0.986); AUROCClinical = 0.864 (CI: 0.794-0.933); AUROCGenomic/AUROCClinical P = 0.044]. Combined model has an increased AUROCCombined of 0.967 (CI: 0.940-0.993) compared with the individual models (AUROCCombined/AUROCClinical P = 0.0069). Hypersusceptible patients show early alterations in immune-related signaling pathways, epigenetic modulation, and chromatin remodeling.
CONCLUSIONS: Early triage of burn patients more susceptible to infections can be made using clinical characteristics and/or genomic signatures. Genomic signature suggests new insights into the pathophysiology of hypersusceptibility to infection may lead to novel potential therapeutic or prophylactic targets.
Keywords
burn, genomics, infection, predictive models, prognosis, sepsis, trauma
Pubmed
Web of science
Create date
28/10/2014 9:12
Last modification date
20/08/2019 12:27
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