An integrative model using flow cytometry identifies nosocomial infection after trauma. Issue 1 (July 2021)

• Record Type: Journal Article
• Authors: Gelbard, Rondi B.; Hensman, Hannah; Schobel, Seth; Stempora, Linda L.; Moris, Dimitrios; Dente, Christopher J.; Buchman, Timothy G.; Kirk, Allan D.; Elster, Eric
• Is Part Of: Journal of trauma and acute care surgery. Volume 91:Issue 1(2021)
• Publication Date: 2021-07
• Subjects: Precision medicine -- clinical decision support -- flow cytometry -- nosocomial infection -- trauma; Surgical intensive care -- Periodicals; Surgical emergencies -- Periodicals; Wounds and injuries -- Surgery -- Periodicals; 617.026
• DOI: 10.1097/TA.0000000000003148
• Languages: English
• ISSNs: 2163-0755

Abstract

Abstract : 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. Abstract : Supplemental digital content is available in the text.