The journal of pain : official journal of the American Pain Society
-
Congenital insensitivity to pain is an umbrella term used to describe a group of rare genetic diseases also classified as hereditary sensory autonomic neuropathies. These conditions are intriguing, with the potential to shed light on the poorly understood relationship concerning nociception and the experience of pain. However, the term congenital insensitivity to pain is epistemologically incorrect and is the product of historical circumstances. ⋯ The suggested term better reflects the nature of the conditions and incorporates current understandings of nociception. PERSPECTIVE: The umbrella term congenital insensitivity to pain conflates pain and nociception, which is epistemologically unacceptable. We suggest a new term, namely, congenital nociceptor deficiency, that overcomes this problem and is concordant with current neurobiological knowledge.
-
Implantable motor cortex stimulation (iMCS) has been performed for >25 years to treat various intractable pain syndromes. Its effectiveness is highly variable and, although various studies revealed predictive variables, none of these were found repeatedly. This study uses neural network analysis (NNA) to identify predictive factors of iMCS treatment for intractable pain. ⋯ The results from the present study show that these 6 predictive variables influence the outcome of iMCS and that, based on these variables, a fair prediction model can be built to predict outcome after iMCS surgery. PERSPECTIVE: The presented NNA analyzed the functioning of computational models and modeled nonlinear statistical data. Based on this NNA, 6 predictive variables were identified that are suggested to be of importance in the improvement of future iMCS to treat chronic pain.
-
Implantable motor cortex stimulation (iMCS) has been performed for >25 years to treat various intractable pain syndromes. Its effectiveness is highly variable and, although various studies revealed predictive variables, none of these were found repeatedly. This study uses neural network analysis (NNA) to identify predictive factors of iMCS treatment for intractable pain. ⋯ The results from the present study show that these 6 predictive variables influence the outcome of iMCS and that, based on these variables, a fair prediction model can be built to predict outcome after iMCS surgery. PERSPECTIVE: The presented NNA analyzed the functioning of computational models and modeled nonlinear statistical data. Based on this NNA, 6 predictive variables were identified that are suggested to be of importance in the improvement of future iMCS to treat chronic pain.