The diagnosis and treatment of Chronic Fatigue Syndrome (CFS) has been a challenge for doctors. Characterised by profound fatigue, CFS is an extremely complicated disorder. Till now there has been no cure or approved treatment for this disorder.
A newly developed diagnostic test might become a game-changer in dealing with this condition.
A team of scientists led by the University of Oxford has published their preliminary findings of a blood cell-based test. According to reports, this test can distinguish between unaffected individuals and those with CFS with 91 percent accuracy.
“The development of a simple test with the potential for early diagnosis [of ME/CFS is] a critical goal. Early diagnosis would enable patients to manage their conditions more effectively, potentially leading to new discoveries in disease pathways and treatment development,” Jiabao Xu and colleagues write in their open-access, peer-reviewed paper.
According to reports, the researchers analysed the profiles of more than 2,000 cells across 98 patient samples, analyzing the molecular vibrations of single cells. Moreover, the scientists observed clear metabolic differences between ME/CFS patients and the two control groups.
According to the scientists, when the AI Algorithm is applied to the test, it could accurately classify 91 percent of patients. Interestingly, it could even differentiate between mild, moderate, and severe ME/CFS patients with 84 percent accuracy.
The team emphasised that further studies to validate the findings in larger cohorts will take some time.
The Findings of the study were published in Advanced Science.
