title: 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.
authors.affiliation: *Department of Surgery, Massachusetts General Hospital, Harvard Medical School, Boston, MA †Department of Microbiology and Immunobiology, Harvard Medical School, Boston, MA ‡Shriners Hospitals for Children Boston, Boston, MA §Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland ¶Department of Biochemistry and Stanford Genome Technology Center, Stanford University School of Medicine, Palo Alto, CA ‖Department of Biomedical Engineering, Worcester Polytechnic Institute, Worchester, MA **Program in Bioinformatics and Computational Biology, Worcester Polytechnic Institute, Worchester, MA.
authors.forename: Shuangchun
authors.initials: S
authors.lastname: Yan
authors.forename: Amy
authors.initials: A
authors.lastname: Tsurumi
authors.forename: Yok-Ai
authors.initials: YA
authors.lastname: Que
authors.forename: Colleen M
authors.initials: CM
authors.lastname: Ryan
authors.forename: Arunava
authors.initials: A
authors.lastname: Bandyopadhaya
authors.forename: Alexander A
authors.initials: AA
authors.lastname: Morgan
authors.forename: Patrick J
authors.initials: PJ
authors.lastname: Flaherty
authors.forename: Ronald G
authors.initials: RG
authors.lastname: Tompkins
authors.forename: Laurence G
authors.initials: LG
authors.lastname: Rahme
mesh_terms: D018806:APACHE; D000328:Adult; D019540:Area Under Curve; D001424:Bacterial Infections / Q000453:epidemiology* / Q000235:genetics*; D002056:Burns / Q000453:epidemiology* / Q000235:genetics / Q000276:immunology; D002059:Burns, Inhalation / Q000453:epidemiology; D016022:Case-Control Studies; D042002:Chromatin Assembly and Disassembly / Q000235:genetics; D015331:Cohort Studies; D015897:Comorbidity; D003428:Cross Infection / Q000453:epidemiology* / Q000235:genetics* / Q000276:immunology; D005260:Female; D020869:Gene Expression Profiling; D020022:Genetic Predisposition to Disease / Q000453:epidemiology*; D006657:Histones / Q000235:genetics; D006801:Humans; D015601:Injury Severity Score; D016015:Logistic Models; D008297:Male; D015233:Models, Statistical; D009765:Obesity / Q000453:epidemiology; D050177:Overweight / Q000453:epidemiology; D011014:Pneumonia / Q000453:epidemiology; D011237:Predictive Value of Tests; D011446:Prospective Studies; D012372:ROC Curve; D012008:Recurrence; D018570:Risk Assessment; D013601:T-Lymphocytes / Q000276:immunology; D013851:Thinness / Q000453:epidemiology; D059467:Transcriptome / Q000235:genetics; D060449:Wnt Signaling Pathway / Q000235:genetics
chemical_list: D006657:Histones