No abstract

Although pain is a widely known phenomenon and an important clinical symptom that occurs in numerous diseases, its mechanisms are still barely understood. Owing to the scarce information concerning its pathophysiology, particularly what is involved in the transition from an acute state to a chronic condition, pain treatment is frequently unsatisfactory, therefore contributing to the amplification of the chronic pain burden. In fact, pain is an extremely complex experience that demands the recruitment of an intricate set of central nervous system components. This includes cortical and subcortical areas involved in interpretation of the general characteristics of noxious stimuli. It also comprises neural circuits that process the motivational-affective dimension of pain. Hence, the reward circuitry represents a vital element for pain experience and modulation. This review article focuses on the interpretation of the extensive data available connecting the major components of the reward circuitry to pain suffering, including the nucleus accumbens, ventral tegmental area, and the medial prefrontal cortex; with especial attention dedicated to the evaluation of neuroplastic changes affecting these structures found in chronic pain syndromes, such as migraine, trigeminal neuropathic pain, chronic back pain, and fibromyalgia.

The control of hypertensive patients' blood pressure and heart rate using vasoconstrictors during surgical procedures under anesthesia is still a major concern in everyday surgical practice. This clinical trial aimed to evaluate the variation of blood pressure and heart rate in nonhypertensive and controlled hypertensive voluntary subjects undergoing oral surgery under local anesthesia with lidocaine hydrochloride and epinephrine at 1:100,000 (Alphacaine; DFL, Brazil), performed in the Oral Surgery Department, Dentistry School, Fluminense Federal University. In total, 25 voluntary subjects were divided into 2 groups: nonhypertensive (n = 15) and controlled hypertensives (n = 10). Blood pressure and heart rate were measured at 4 different times: T0, in the waiting room; T1, after placement of the surgical drapes; T2, 10 minutes after anesthesia injection; and T3, at the end of the surgical procedure. A statistically significant difference (P < 0.05) between the groups was found at times T0 and T2 for the systolic pressure but only at time T0 for the diastolic pressure. The assessment of the heart rate of both groups showed a statistically significant difference (P < 0.05) at time T1. An analysis of the employed anesthetic volume indicated no statistically significant difference (P > 0.05) between the amount administered to nonhypertensive and hypertensive subjects. It was concluded that the local anesthetics studied could safely be used in controlled hypertensive and nonhypertensive patients in compliance with the maximum recommended doses.

Background To quantify pain severity in patients and the efficacy treatments, researchers and clinicians apply tools such as the traditional visual analog scale (VAS) that leads to inaccurate interpretation of the main sensory pain. Objective This study aimed to validate the pain measurements of a neuroscience-based 3D body pain mobile app called GeoPain. Methods Patients with temporomandibular disorder (TMD) were assessed using GeoPain measures in comparison to VAS and positive and negative affect schedule (PANAS), pain and mood scales, respectively. Principal component analysis (PCA), scatter score analysis, Pearson methods, and effect size were used to determine the correlation between GeoPain and VAS measures. Results The PCA resulted in two main orthogonal components: first principal component (PC1) and second principal component (PC2). PC1 comprises a combination score of all GeoPain measures, which had a high internal consistency and clustered together in TMD pain. PC2 included VAS and PANAS. All loading coefficients for GeoPain measures in PC1 were above 0.70, with low loadings for VAS and PANAS. Meanwhile, PC2 was dominated by a VAS and PANAS coefficient >0.4. Repeated measure analysis revealed a strong correlation between the VAS and mood scores from PANAS over time, which might be related to the subjectivity of the VAS measure, whereas sensory-discriminative GeoPain measures, not VAS, demonstrated an association between chronicity and TMD pain in locations spread away from the most commonly reported area or pain epicenter (P=.01). Analysis using VAS did not detect an association at baseline between TMD and chronic pain. The long-term reliability (lag >1 day) was consistently high for the pain area and intensity number summation (PAINS) with lag autocorrelations averaging between 0.7 and 0.8, and greater than the autocorrelations for VAS averaging between 0.3 and 0.6. The combination of higher reliability for PAINS and its objectivity, displayed by the lack of association with PANAS as compared with VAS, indicated that PAINS has better sensitivity and reliability for measuring treatment effect over time for sensory-discriminative pain. The effect sizes for PAINS were larger than those for VAS, consequently requiring smaller sample sizes to assess the analgesic efficacy of treatment if PAINS was used versus VAS. The PAINS effect size was 0.51 SD for both facial sides and 0.60 SD for the right side versus 0.35 SD for VAS. Therefore, the sample size required to detect such effect sizes with 80% power would be n=125 per group for VAS, but as low as n=44 per group for PAINS, which is almost a third of the sample size needed by VAS. Conclusions GeoPain demonstrates precision and reliability as a 3D mobile interface for measuring and analyzing sensory-discriminative aspects of subregional pain in terms of its severity and response to treatment, without being influenced by mood variations from patients.