Dataset Information

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

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.

SUBMITTER: Yan S

PROVIDER: S-EPMC4284150 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Publications

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

Yan Shuangchun S Tsurumi Amy A Que Yok-Ai YA Ryan Colleen M CM Bandyopadhaya Arunava A Morgan Alexander A AA Flaherty Patrick J PJ Tompkins Ronald G RG Rahme Laurence G LG

Annals of surgery 20150401 4

<h4>Objective</h4>To develop predictive models for early triage of burn patients based on hypersusceptibility to repeated infections.<h4>Background</h4>Infection remains a major cause of mortality and morbidity after severe trauma, demanding new strategies to combat infections. Models for infection prediction are lacking.<h4>Methods</h4>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 transc ...[more]

PMID: 24950278

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Dataset Information

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

Objective

Background

Methods

Results

Conclusions

Publications

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

Similar Datasets

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