This electronic nose detects when there is rejection of a lung transplant

A survey that has just been presented to the International Congress of the European Respiratory Society, which took place in practice and is being published, shows the development of a powerful electronic nose capable of detecting, with an accuracy of 86%. , when “a lung transplant begins at Discovery could help doctors identify refusals earlier so that treatments can be given to prevent them from getting worse. However, more research is needed before this eNose can be used in the clinic .

Approximately 50% of lung transplant patients are diagnosed with chronic allograft dysfunction (CLAD) or chronic rejection within five years of transplantation. Chronic rejection leftovers the leading cause of death after lung relocation and there is currently no treatment to reverse it, ”said Nynke Wijbenga, PhD student and medical technician at Erasmus Rotterdam University Medical Center in the Netherlands. "Once chronic rejection is confirmed, patients can survive an average of one to five years. A transplant may be a last resort for some patients with advanced chronic rejection. Therefore, it is extremely important to assess whether we can predict or diagnose lung transplant dysfunction. . at an early stage, allowing for additional effective early treatment . "

Currently, the diagnosis of CLAD container take several months. Doctors evaluate lung function at each visit and compare it to the best peak lung function obtained after a transplant. If it drops to 80% or less, continue your research to rule out causes that could respond to action, such as a lung infection that could be treated with antibiotics. Chronic rejection can only be confirmed after these investigations and if the deterioration of lung function persists for three months .

 

This is how eNose works

ENose is a small device that contains instruments for detecting chemicals called volatile organic compounds (VOCs), which are present in about 1% of our expired breath and can vary depending on metabolic processes that take place throughout the body or in parts such as the lungs. . . . . . When patients exhale in eNose, the sensors not only detect the respiratory VOC profile, but also correct the results to take into account the ambient air that has remained inhaled. The results are analyzed using machine learning algorithms and the "breath footprint" can be used to identify various lung diseases .

To validate the functioning of the microelectronic nose, the researchers recruited 91 lung transplant patients, took an eNose extent of each patient and then compared their results with the usual diagnoses they had already received. In 86% of cases, the academics found that eNose was able to distinguish between the 68 patients with stable lung transplantation and the 23 patients with CLAD .

"These results advise that eNose is a talented tool for CLAD detection," Wijbenga explained. "But, more research is needed before it can be used in the clinic. We need to assess whether repeated measurements on the same patients can provide more accurate diagnoses and even predict CLAD before it occurs. The aim is to develop this technique for widespread use throughout Europe. "

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