An integrative model using flow cytometry identifies nosocomial infection after trauma.
Adolescent
Adult
Aged
Aged, 80 and over
Cross Infection
/ blood
Feasibility Studies
Female
Flow Cytometry
Humans
Immunity, Innate
Injury Severity Score
Killer Cells, Natural
/ immunology
Length of Stay
/ statistics & numerical data
Lymphocyte Count
Male
Middle Aged
Models, Biological
Prospective Studies
Sensitivity and Specificity
Wounds and Injuries
/ blood
Young Adult
Journal
The journal of trauma and acute care surgery
ISSN: 2163-0763
Titre abrégé: J Trauma Acute Care Surg
Pays: United States
ID NLM: 101570622
Informations de publication
Date de publication:
01 07 2021
01 07 2021
Historique:
pubmed:
5
3
2021
medline:
24
9
2021
entrez:
4
3
2021
Statut:
ppublish
Résumé
Flow cytometry (FCM) is a rapid diagnostic tool for monitoring immune cell function. We sought to determine if assessment of cell phenotypes using standardized FCM could be used to identify nosocomial infection after trauma. Prospective study of trauma patients at a Level I center from 2014 to 2018. Clinical and FCM data were collected within 24 hours of admission. Random forest (RF) models were developed to estimate the risk of severe sepsis (SS), organ space infection (OSI), and ventilator-associated pneumonia (VAP). Variables were selected using backward elimination and models were validated with leave-one-out. One hundred and thirty-eight patients were included (median age, 30 years [23-44 years]; median Injury Severity Score, 20 (14-29); 76% (105/138) Black; 60% (83/138) gunshots). The incidence of SS was 8.7% (12/138), OSI 16.7% (23/138), and VAP 18% (25/138). The final RF SS model resulted in five variables (RBCs transfused in first 24 hours; absolute counts of CD56- CD16+ lymphocytes, CD4+ T cells, and CD56 bright natural killer [NK] cells; percentage of CD16+ CD56+ NK cells) that identified SS with an AUC of 0.89, sensitivity of 0.98, and specificity of 0.78. The final RF OSI model resulted in four variables (RBC in first 24 hours, shock index, absolute CD16+ CD56+ NK cell counts, percentage of CD56 bright NK cells) that identified OSI with an AUC of 0.76, sensitivity of 0.68, and specificity of 0.82. The RF VAP model resulted in six variables (Sequential [Sepsis-related] Organ Failure Assessment score: Injury Severity Score; CD4- CD8- T cell counts; percentages of CD16- CD56- NK cells, CD16- CD56+ NK cells, and CD19+ B lymphocytes) that identified VAP with AUC of 0.86, sensitivity of 0.86, and specificity of 0.83. Combined clinical and FCM data can assist with early identification of posttraumatic infections. The presence of NK cells supports the innate immune response that occurs during acute inflammation. Further research is needed to determine the functional role of these innate cell phenotypes and their value in predictive models immediately after injury. Prognostic, level III.
Sections du résumé
BACKGROUND
Flow cytometry (FCM) is a rapid diagnostic tool for monitoring immune cell function. We sought to determine if assessment of cell phenotypes using standardized FCM could be used to identify nosocomial infection after trauma.
METHODS
Prospective study of trauma patients at a Level I center from 2014 to 2018. Clinical and FCM data were collected within 24 hours of admission. Random forest (RF) models were developed to estimate the risk of severe sepsis (SS), organ space infection (OSI), and ventilator-associated pneumonia (VAP). Variables were selected using backward elimination and models were validated with leave-one-out.
RESULTS
One hundred and thirty-eight patients were included (median age, 30 years [23-44 years]; median Injury Severity Score, 20 (14-29); 76% (105/138) Black; 60% (83/138) gunshots). The incidence of SS was 8.7% (12/138), OSI 16.7% (23/138), and VAP 18% (25/138). The final RF SS model resulted in five variables (RBCs transfused in first 24 hours; absolute counts of CD56- CD16+ lymphocytes, CD4+ T cells, and CD56 bright natural killer [NK] cells; percentage of CD16+ CD56+ NK cells) that identified SS with an AUC of 0.89, sensitivity of 0.98, and specificity of 0.78. The final RF OSI model resulted in four variables (RBC in first 24 hours, shock index, absolute CD16+ CD56+ NK cell counts, percentage of CD56 bright NK cells) that identified OSI with an AUC of 0.76, sensitivity of 0.68, and specificity of 0.82. The RF VAP model resulted in six variables (Sequential [Sepsis-related] Organ Failure Assessment score: Injury Severity Score; CD4- CD8- T cell counts; percentages of CD16- CD56- NK cells, CD16- CD56+ NK cells, and CD19+ B lymphocytes) that identified VAP with AUC of 0.86, sensitivity of 0.86, and specificity of 0.83.
CONCLUSIONS
Combined clinical and FCM data can assist with early identification of posttraumatic infections. The presence of NK cells supports the innate immune response that occurs during acute inflammation. Further research is needed to determine the functional role of these innate cell phenotypes and their value in predictive models immediately after injury.
LEVEL OF EVIDENCE
Prognostic, level III.
Identifiants
pubmed: 33660689
doi: 10.1097/TA.0000000000003148
pii: 01586154-202107000-00009
doi:
Types de publication
Journal Article
Multicenter Study
Observational Study
Research Support, U.S. Gov't, Non-P.H.S.
Langues
eng
Sous-ensembles de citation
IM
Pagination
47-53Informations de copyright
Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.
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