학술논문
Validation of the riboleukogram to detect ventilator-associated pneumonia after severe injury.
Document Type
Academic Journal
Author
Cobb JP; Center for Critical Illness and Health Engineering, Washington University in St Louis, MO, USA. cobb@wustl.edu; Moore EE; Hayden DL; Minei JP; Cuschieri J; Yang J; Li Q; Lin N; Brownstein BH; Hennessy L; Mason PH; Schierding WS; Dixon DJ; Tompkins RG; Warren HS; Schoenfeld DA; Maier RV
Source
Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 0372354 Publication Model: Print Cited Medium: Internet ISSN: 1528-1140 (Electronic) Linking ISSN: 00034932 NLM ISO Abbreviation: Ann Surg Subsets: MEDLINE
Subject
Language
English
Abstract
Objective: We hypothesized that circulating leukocyte RNA profiles or “riboleukograms” detect ventilator-associated pneumonia after blunt trauma.
Summary Background Data: A pilot microarray study of 11 ventilator-associated pneumonia (VAP) patients suggested that 85 leukocyte genes can be used to diagnose VAP. Validation of this gene set to detect VAP was tested using data from an independent patient cohort.
Methods: A total of 158 intubated blunt trauma patients were enrolled at 5 centers, where 57 (36%) developed VAP. Patient age was 34.2 ± 11.1 years; 65% were male. Circulating leukocyte GeneChip U133 2.0 expression values were measured at time 0.5, 1, 4, 7, 14, 21, and 28 days after injury. DChip normalized leukocyte transcriptional profiles were analyzed using repeated measures logistic regression. A compound covariate model based on leukocyte gene transcriptional profiles in a training subset of patients was tested to determine predictive accuracy for VAP 4 days prior to clinical diagnosis in the test subset.
Results: Using gene expression values measured on each study day at an FDR <0.05, 27 (32%) of the 85 genes were associated with the diagnosis of VAP 1 to 4 days before diagnosis. However, the compound covariate model based on these 85-genes did not predict VAP in the test cohort better than chance (P = 0.27). In contrast, a compound covariate model based upon de novo transcriptional analysis of the 158 patients predicted VAP better than chance 4 days before diagnosis with a sensitivity of 57% and a specificity of 69%.
Conclusion: Our results validate those described in a pilot study, confirming that riboleukograms are associated with the development of VAP days prior to clinical diagnosis. Similarly, a riboleukogram predictive model tested on a larger cohort of 158 patients was better than chance at predicting VAP days prior to clinical diagnosis.
Summary Background Data: A pilot microarray study of 11 ventilator-associated pneumonia (VAP) patients suggested that 85 leukocyte genes can be used to diagnose VAP. Validation of this gene set to detect VAP was tested using data from an independent patient cohort.
Methods: A total of 158 intubated blunt trauma patients were enrolled at 5 centers, where 57 (36%) developed VAP. Patient age was 34.2 ± 11.1 years; 65% were male. Circulating leukocyte GeneChip U133 2.0 expression values were measured at time 0.5, 1, 4, 7, 14, 21, and 28 days after injury. DChip normalized leukocyte transcriptional profiles were analyzed using repeated measures logistic regression. A compound covariate model based on leukocyte gene transcriptional profiles in a training subset of patients was tested to determine predictive accuracy for VAP 4 days prior to clinical diagnosis in the test subset.
Results: Using gene expression values measured on each study day at an FDR <0.05, 27 (32%) of the 85 genes were associated with the diagnosis of VAP 1 to 4 days before diagnosis. However, the compound covariate model based on these 85-genes did not predict VAP in the test cohort better than chance (P = 0.27). In contrast, a compound covariate model based upon de novo transcriptional analysis of the 158 patients predicted VAP better than chance 4 days before diagnosis with a sensitivity of 57% and a specificity of 69%.
Conclusion: Our results validate those described in a pilot study, confirming that riboleukograms are associated with the development of VAP days prior to clinical diagnosis. Similarly, a riboleukogram predictive model tested on a larger cohort of 158 patients was better than chance at predicting VAP days prior to clinical diagnosis.