Quantitative sensory testing as a predictor of neuropathic pain in diabetic patients
Diabetic neuropathy is one of the most common complications of diabetes, affecting about half of patients with the disease. The development of chronic pain is one of the symptoms of diabetic neuropathy, occurring mainly in the extremities of the limbs, manifested as exacerbated responses to sensorial stimuli, with different sensory profiles associated with pain and the responsiveness to analgesia. The objective of this study was to evaluated the informative value of the Quantitative Sensory Testing (QST) features in regards to predicting the Douleur Neuropathique en 4 (DN4) and McGill Pain Questionnaire (MPQ) pain classification both in absolute value as well as in comparison to other variables. A machine-learning approach was used to analyze data collected from 29 men and 26 women of which 25 were diagnosed with Diabetes mellitus. Preliminary results indicate that a small number of features is sufficient to achieve above-chance accuracy level of pain classification prediction. The theoretical and practical implications of these findings will be discussed.