RESUMEN
Objectives: The number of geriatric hip fracture patients is high and expected to rise in the coming years, and many are frail and at risk for adverse outcomes. Early identification of high-risk patients is crucial to balance treatment and optimize outcome, but remains challenging. Previous research in patients with multitrauma suggested that neutrophil phenotype analysis could aid in early identification of high-risk patients. This pilot study investigated the feasibility and clinical value of neutrophil phenotype analysis in geriatric patients with a hip fracture. Methods: A prospective study was conducted in a regional teaching hospital in the Netherlands. At the emergency department, blood samples were collected from geriatric patients with a hip fracture and analyzed using automated flow cytometry. Flow cytometry data were processed using an automated clustering algorithm. Neutrophil activation data were compared with a healthy control cohort. Neutrophil phenotype categories were assessed based on two-dimensional visual assessment of CD16/CD62L expression. Results: Blood samples from 45 geriatric patients with a hip fracture were included. Neutrophils showed an increased activation profile and decreased responsiveness to formyl peptides when compared to healthy controls. The neutrophil phenotype of all patients was categorized. The incidence of severe adverse outcome was significantly different between the different categories (P = 0.0331). Moreover, patients with neutrophil phenotype category 0 developed no severe adverse outcomes. Conclusions: Using point-of-care fully automated flow cytometry to analyze the neutrophil compartment in geriatric hip fracture patients is feasible and holds clinical value in determining patients at risk for adverse outcome. This study is a first step toward immuno-based precision medicine for identifying geriatric hip fracture patients that are deemed fit for surgery.
RESUMEN
PURPOSE: The risk of infectious complications after trauma is determined by the amount of injury-related tissue damage and the resulting inflammatory response. Recently, it became possible to measure the neutrophil phenotype in a point-of-care setting. The primary goal of this study was to investigate if immunophenotype categories based on visual recognition of neutrophil subsets are applicable to interpret the inflammatory response to trauma. The secondary goal was to correlate these immunophenotype categories with patient characteristics, injury severity and risk of complications. METHODS: A cohort study was conducted with patients presented at a level 1 trauma center with injuries of any severity, who routinely underwent neutrophil phenotyping. Data generated by automated point-of-care flow cytometry were prospectively gathered. Neutrophil phenotypes categories were defined by visual assessment of two-dimensional CD16/CD62L dot plots. All patients were categorized in one of the immunophenotype categories. Thereafter, the categories were validated by multidimensional analysis of neutrophil populations, using FlowSOM. All clinical parameters and endpoints were extracted from the trauma registry. RESULTS: The study population consisted of 380 patients. Seven distinct immunophenotype Categories (0-6) were defined, that consisted of different neutrophil populations as validated by FlowSOM. Injury severity scores and risk of infectious complications increased with ascending immunophenotype Categories 3-6. Injury severity was similarly low in Categories 0-2. CONCLUSION: The distribution of neutrophil subsets that were described in phenotype categories is easily recognizable for clinicians at the bedside. Even more, multidimensional analysis demonstrated these categories to be distinct subsets of neutrophils. Identification of trauma patients at risk for infectious complications by monitoring the immunophenotype category is a further improvement of personalized and point-of-care decision-making in trauma care.