PMID- 36597771
OWN - NLM
STAT- MEDLINE
DCOM- 20230307
LR  - 20240302
IS  - 1540-0514 (Electronic)
IS  - 1073-2322 (Print)
IS  - 1073-2322 (Linking)
VI  - 59
IP  - 3
DP  - 2023 Mar 1
TI  - A PREVENTIVE TOOL FOR PREDICTING BLOODSTREAM INFECTIONS IN CHILDREN WITH BURNS.
PG  - 393-399
LID - 10.1097/SHK.0000000000002075 [doi]
AB  - Introduction: Despite significant advances in pediatric burn care, bloodstream 
      infections (BSIs) remain a compelling challenge during recovery. A personalized 
      medicine approach for accurate prediction of BSIs before they occur would 
      contribute to prevention efforts and improve patient outcomes. Methods: We 
      analyzed the blood transcriptome of severely burned (total burn surface area 
      [TBSA] >/=20%) patients in the multicenter Inflammation and Host Response to Injury 
      ("Glue Grant") cohort. Our study included 82 pediatric (aged <16 years) patients, 
      with blood samples at least 3 days before the observed BSI episode. We applied 
      the least absolute shrinkage and selection operator (LASSO) machine-learning 
      algorithm to select a panel of biomarkers predictive of BSI outcome. Results: We 
      developed a panel of 10 probe sets corresponding to six annotated genes ( ARG2 [ 
      arginase 2 ], CPT1A [ carnitine palmitoyltransferase 1A ], FYB [ FYN binding 
      protein ], ITCH [ itchy E3 ubiquitin protein ligase ], MACF1 [ microtubule actin 
      crosslinking factor 1 ], and SSH2 [ slingshot protein phosphatase 2 ]), two 
      uncharacterized ( LOC101928635 , LOC101929599 ), and two unannotated regions. Our 
      multibiomarker panel model yielded highly accurate prediction (area under the 
      receiver operating characteristic curve, 0.938; 95% confidence interval [CI], 
      0.881-0.981) compared with models with TBSA (0.708; 95% CI, 0.588-0.824) or TBSA 
      and inhalation injury status (0.792; 95% CI, 0.676-0.892). A model combining the 
      multibiomarker panel with TBSA and inhalation injury status further improved 
      prediction (0.978; 95% CI, 0.941-1.000). Conclusions: The multibiomarker panel 
      model yielded a highly accurate prediction of BSIs before their onset. Knowing 
      patients' risk profile early will guide clinicians to take rapid preventive 
      measures for limiting infections, promote antibiotic stewardship that may aid in 
      alleviating the current antibiotic resistance crisis, shorten hospital length of 
      stay and burden on health care resources, reduce health care costs, and 
      significantly improve patients' outcomes. In addition, the biomarkers' identity 
      and molecular functions may contribute to developing novel preventive 
      interventions.
CI  - Copyright (c) 2023 by the Shock Society.
FAU - Tsurumi, Amy
AU  - Tsurumi A
FAU - Flaherty, Patrick J
AU  - Flaherty PJ
AD  - Department of Mathematics and Statistics, University of Massachusetts at Amherst, 
      Amherst, Massachusetts.
FAU - Que, Yok-Ai
AU  - Que YA
AD  - Department of Intensive Care Medicine, Inselspital, Bern University Hospital, 
      University of Bern, Bern, Switzerland.
FAU - Ryan, Colleen M
AU  - Ryan CM
FAU - Banerjee, Ankita
AU  - Banerjee A
AD  - Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts.
FAU - Chakraborty, Arijit
AU  - Chakraborty A
FAU - Almpani, Marianna
AU  - Almpani M
FAU - Shankar, Malavika
AU  - Shankar M
AD  - Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts.
FAU - Goverman, Jeremy
AU  - Goverman J
FAU - Schulz, John T 3rd
AU  - Schulz JT 3rd
FAU - Sheridan, Robert L
AU  - Sheridan RL
FAU - Friedstat, Jonathan
AU  - Friedstat J
FAU - Hickey, Sean A
AU  - Hickey SA
FAU - Tompkins, Ronald G
AU  - Tompkins RG
AD  - Department of Surgery, Massachusetts General Hospital, Boston, Massachusetts.
FAU - Rahme, Laurence G
AU  - Rahme LG
LA  - eng
GR  - R03 AI151499/AI/NIAID NIH HHS/United States
GR  - R56 AI155505/AI/NIAID NIH HHS/United States
GR  - U54 GM062119/GM/NIGMS NIH HHS/United States
PT  - Journal Article
PT  - Multicenter Study
PT  - Research Support, N.I.H., Extramural
PT  - Research Support, Non-U.S. Gov't
DEP - 20230104
PL  - United States
TA  - Shock
JT  - Shock (Augusta, Ga.)
JID - 9421564
SB  - IM
MH  - Humans
MH  - Child
MH  - Retrospective Studies
MH  - Length of Stay
MH  - *Burns
MH  - *Sepsis
MH  - Inflammation
PMC - PMC9991965
MID - NIHMS1858399
COIS- L.G.R. has a financial interest in Spero Therapeutics, a company developing 
      therapies to treat bacterial infections. L.G.R.'s financial interests are 
      reviewed and managed by Massachusetts General Hospital and Partners HealthCare in 
      accordance with their conflict of interest policies. The other authors report no 
      conflicts of interest.
EDAT- 2023/01/05 06:00
MHDA- 2023/03/08 06:00
PMCR- 2024/03/01
CRDT- 2023/01/04 03:53
PHST- 2023/01/05 06:00 [pubmed]
PHST- 2023/03/08 06:00 [medline]
PHST- 2023/01/04 03:53 [entrez]
PHST- 2024/03/01 00:00 [pmc-release]
AID - 00024382-202303000-00010 [pii]
AID - 10.1097/SHK.0000000000002075 [doi]
PST - ppublish
SO  - Shock. 2023 Mar 1;59(3):393-399. doi: 10.1097/SHK.0000000000002075. Epub 2023 Jan 
      4.