Lung Transplant Rejection Clinical Trial
Official title:
Analysis of Volatile Organic Compounds in the Breath of Lung Transplant Rejection
This study will sample and analyze volatile organic compounds (VOCs) from participants considered to be at risk for developing rejection following lung transplant by using infrared spectroscopy.
The aim of this study is to sample and analyze volatile organic compounds (VOCs) from participants considered to be at risk for developing rejection following lung transplant. By using infrared spectroscopy, the breath sample analysis will help investigators describe and identify patterns of VOCs that are over- or under-represented in patients with post-lung transplant rejection when compared to the breath profiles of those without rejection. It is hypothesized that the profile of volatile chemicals in the breath of patients in the early stages of rejection will differ significantly from those individuals without rejection. Primary objective • To analyze the breath-born VOCs in breath profiles of lung transplant patients with rejection in comparison to lung transplant patients without rejection using infrared spectroscopy to determine the presence of lung rejection and to develop mathematical/statistical models of infrared absorption spectrum for identification of rejection. Secondary objective - To determine the best method to classify health status based on VOC data of breath samples - To validate early test results on an additional infrared spectroscopic analyzer in post-lung transplant patients The study is an unblinded, prospective case-control study. The study cohorts will include: 1) patients with confirmed post-lung transplant rejection via biopsy, and 2) control patients who have undergone lung transplant but are free from rejection as confirmed via biopsy. Breath samples collected from participants will be analyzed to characterize and further identify differences in infrared absorption profiles from each cohort using infrared spectroscopy. The data will be used to validate a previously developed machine learning algorithm. ;
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