Novel Biomarkers Predict Pain Sensitivity

The study of the authenticity of the prediction showed that the signing of the new vital signs that valued the cortical activity predicted the sensitivity of individual pain.

The signature consists of standards: the frequency of alpha alpha (PAF) and the severity of the cortical (CME). In the training group, it has correctly classified the study participants with high or low pain sensitivity with an area of ​​under the curve (AUC) of 1.00.

In the test set, AUC 0.88 (95 % CI 0.78-0.99) was The nerve group.

The results were cloned through a group of parameters. PAF and CME vital indicators showed a good test to a re -test test.

“A mixture of vital signs, reproduction, reliability, and the health of the pain model indicates high capabilities of clinical translation, especially in predicting the transition from acute pain to chronic pain,” wrote Seinowicz and his colleagues.

PAF is the dominant sensory cortical oscillation in the range of 8-12 Hz (alpha). CME is the effectiveness of moving signals from the initial motor cortex to the peripheral muscles. The previous work showed that PAF is slower before the pain appears and reduces CME during the lengthy pain associated with more pain, while PAF faster and increased CME with less pain.

“Given that individuals with higher pain in the early stages of the lengthy pain ring (for example, posturicy) are more likely to develop chronic pain in the future, slow before the expected lengthy pain ring and/or CME depression during the sharp stages and the researchers pointed out The pain can be a prediction of moving to chronic pain. “

The objective vital indicators were named to track the intensity of the pain “The Holy Jassy” of neuroscience, note that Brasad Sherfal, PhD, PhD, from the University of California San Francisco, and Christopher Roselle, PhD, from the Georgia Institute of Technology in Atlanta, in The accompanying editorial.

“While pain is among the most basic experiences, everywhere, and adaptation that can affect a living object, there is still a mysterious understanding of how the pain in the nervous system,” they noticed. The consensus on the mechanisms behind the chronic pain – the pain that lasts for more than 3 months, affects 21 % of adults – It is less clear.

Shirvalkar and Rozell said that the signature of PAF and CME “are likely to have a widely applicable application through many medical fields.” “If it successfully translated into clinical practice, the vital indicators that predict the transition to chronic pain will have a tremendous effect of treating millions of individuals.”

Progress in the vital indicators of pain also needs to integrate progress in Global nervous ethics instructions The editorials referred to moral concerns about the treatment of pain. They wrote: “We must be careful to ensure that the quantitative measures do not replace living expertise reports, or to enter the lack of confidence in the relationship between the doctor and the patient, or put unrealistic expectations for the patient, or exacerbate the aspects of inequality in the treatment of pain through this weak population.” .

the Predispay The health verification study included 150 people (100 in the training group, and 50 in the test group) who obtained an injection from the neurosaamic growth factor in the right mass muscle on day 0 and day 2 to urge prolonged jaw pain that lasted up to 4 weeks.

Participants were healthy adults recruited in Australia with an average age of 25 years. They had no history of chronic pain, nervous or psychological condition, and 84 participants (56 %) of men were.

The research aims to determine whether individuals can be accurately classified as high or low pain based on PAF and CME readings. The researchers used electrical imaging to imagine PAF and skull magnetic stimulation with the potential to evaluate the CME per day 0, day 2 and day 5.

The initial results were the pain of jaw in chewing and yawning. The pain sensitivity was evaluated twice a day from the first day to the 30th day with self -reported pain.

Seminowicz and his colleagues use five automated learning models in the training group. From these, the winning work was the logistical slope. Including the disaster of sex and pain as the variables did not improve the typical performance.

The study evaluated healthy participants using the experimental pain model; Results may not apply to other people or other circumstances, as researchers admitted.