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Updated: Aug 3, 2025
Flow Cytometric Analysis for Identification of the Innate and Adaptive Immune Cells of Murine Lung
Published on: November 16, 2021
A random forest model using flow cytometry data identifies pulmonary infection after thoracic injury
Rondi B Gelbard1, Hannah Hensman, Seth Schobel
1From the Department of Surgery (R.B.G., C.J.D., T.G.B.), Emory University, Atlanta, Georgia; Uniformed Services University of the Health Sciences (S.S., E.G., E.E.), Walter Reed National Military Medical Center (E.E.), Surgical Critical Care Initiative (R.B.G., H.H., S.S., L.S., E.G., C.J.D., T.G.B., A.D.K., E.E.), Bethesda, Maryland; DecisionQ (H.H.), Arlington, Virginia; Department of Surgery (L.S., D.M., A.D.K.), Duke University, Durham, North Carolina; Department of Surgery, Trauma, Burns, and Surgical Critical Care (R.B.G.), University of Alabama at Birmingham, Birmingham, Alabama; and Henry M Jackson Foundation for the Advancement of Military Medicine (S.S., E.G.), Bethesda, Maryland.
Background:
Thoracic injury can cause impairment of lung function leading to respiratory complications such as pneumonia (PNA). There is increasing evidence that central memory T cells of the adaptive immune system play a key role in pulmonary immunity. We sought to explore whether assessment of cell phenotypes using flow cytometry (FCM) could be used to identify pulmonary infection after thoracic trauma.
Methods:
We prospectively studied trauma patients with thoracic injuries who survived >48 hours at a Level 1 trauma center from 2014 to 2020. Clinical and FCM data from serum samples collected within 24 hours of admission were considered as potential variables. Random forest and logistic regression models were developed to estimate the risk of hospital-acquired and ventilator-associated PNA. Variables were selected using backwards elimination, and models were internally validated with leave-one-out.
Results:
Seventy patients with thoracic injuries were included (median age, 35 years [interquartile range (IQR), 25.25-51 years]; 62.9% [44 of 70] male, 61.4% [42 of 70] blunt trauma). The most common injuries included rib fractures (52 of 70 [74.3%]) and pulmonary contusions (26 of 70 [37%]). The incidence of PNA was 14 of 70 (20%). Median Injury Severity Score was similar for patients with and without PNA (30.5 [IQR, 22.6-39.3] vs. 26.5 [IQR, 21.6-33.3]). The final random forest model selected three variables (Acute Physiology and Chronic Health Evaluation score, highest pulse rate in first 24 hours, and frequency of CD4 + central memory cells) that identified PNA with an area under the curve of 0.93, sensitivity of 0.91, and specificity of 0.88. A logistic regression with the same features had an area under the curve of 0.86, sensitivity of 0.76, and specificity of 0.85.
Conclusion:
Clinical and FCM data have diagnostic utility in the early identification of patients at risk of nosocomial PNA following thoracic injury. Signs of physiologic stress and lower frequency of central memory cells appear to be associated with higher rates of PNA after thoracic trauma.
Level Of Evidence:
Diagnostic Test/Criteria; Level IV.
