Chronic pain is one of the major causes of disability with a tremendous impact on an individual's quality of life and on public health. Transcutaneous vagus nerve stimulation (tVNS) is a safe therapeutic for this condition. We aimed to evaluate its effects in adults with chronic pain. A comprehensive search was performed, including randomized controlled trials published until October 2023, which assessed the effects of noninvasive tVNS. Cohen's d effect size and 95% confidence intervals (CIs) were calculated, and random-effects meta-analyses were performed. Fifteen studies were included. The results revealed a mean effect size of 0.41 (95% CI 0.17-0.66) in favor of tVNS as compared with control, although a significant heterogeneity was observed (χ² = 21.7, df = 10, P = 0.02, I ² = 53.9%). However, when compared with nonactive controls, tVNS shows a larger effect size (0.79, 95% CI 0.25-1.33), although the number of studies was small (n = 3). When analyzed separately, auricular tVNS and cervical tVNS against control, it shows a significant small to moderate effect size, similar to that of the main analysis, respectively, 0.42 (95% CI 0.08-0.76, 8 studies) and 0.36 (95% CI 0.01-0.70, 3 studies). No differences were observed in the number of migraine days for the trials on migraine. This meta-analysis indicates that tVNS shows promise as an effective intervention for managing pain intensity in chronic pain conditions. We discuss the design of future trials to confirm these preliminary results, including sample size and parameters of stimulation.

Background: Evidence suggests that vagus nerve stimulation can modulate heart rate variability (HRV). However, there is a lack of mechanistic studies in healthy subjects assessing the effects of bilateral transcutaneous auricular vagus nerve stimulation (taVNS) on HRV. Our study aims to investigate how taVNS can influence the HRV response, including the influence of demographic variables in this response. Methods: Therefore, we conducted a randomized controlled study with 44 subjects, 22 allocated to active and 22 to sham taVNS. Results: Our results showed a significant difference between groups in the high-frequency (HF) metric. Active taVNS increased the HF metric significantly as compared to sham taVNS. Also, we found that age was a significant effect modifier of the relationship between taVNS and HF-HRV, as a larger increase in HF-HRV was seen in the older subjects. Importantly, there was a decrease in HF-HRV in the sham group. Conclusions: These findings suggest that younger subjects can adapt and maintain a constant level of HF-HRV regardless of the type of stimulation, but in the older subjects, only the active taVNS recipients were able to maintain and increase their HF-HRV. These results are important because they indicate that taVNS can enhance physiological regulation processes in response to external events.

Evidence suggests that transauricular vagus nerve stimulation (taVNS) modulates the endogenous pain system and may be an alternative treatment for chronic pain conditions. To investigate the effects of taVNS in pain processing using quantitative sensory testing (QST) as a biomarker for pain sensitivity and modulation. We conducted a randomized double-blinded controlled study with 44 healthy subjects, 22 allocated to taVNS and 22 to sham taVNS. QST metrics (pain-60, temporal summation [TSPS], and conditioned pain modulation [CPM]) were the main outcomes of the study. Self-reported mood and fatigue were secondary outcomes. We performed regression analyses to evaluate the differences between pain-60 scores, TSPS, and CPM before and after intervention comparing taVNS and sham VNS groups. Moreover, Bayesian models were performed as sensitivity analysis. Our findings showed a statistically significant difference in the CPM score between taVNS and sham taVNS (beta coefficient = 0.80; 95% CI: 0.23-1.37; p = 0.007). The effect size (Cohen's d) of this difference was 0.97, which is considered a large effect size. Bayesian results (non-informative prior) supported the superiority of taVNS showing a strong probability of benefit (99.99%; beta coefficient = 0.80; 95% CrI: 0.25-1.35; BF = 234.29). No differences were found in pain-60 (unadjusted: p = 0.58; adjusted: p = 0.76) or TSPS (unadjusted: p = 0.25; adjusted: p = 0.40). Moreover, the analysis demonstrated a significant correlation between VAS fatigue and mood with CPM improvement in the taVNS group. Also, changes in fatigue significantly mediated taVNS effects. This study supports the taVNS positive effects on endogenous pain modulation in health subjects. Future RCTs using VNS in patients with chronic pain are still needed to establish the analgesic effects of taVNS in the clinical setting. NCT05801809.

This study aimed to investigate clinical and physiological predictors of brain oscillatory activity in patients with fibromyalgia (FM), assessing resting-state power, event-related desynchronization (ERD), and event-related synchronization (ERS) during tasks. We performed a cross-sectional analysis, including clinical and neurophysiological data from 78 subjects with FM. Multivariate regression models were built to explore predictors of electroencephalography bands. Our findings show a negative correlation between beta oscillations and pain intensity; fibromyalgia duration is positively associated with increased oscillatory power at low frequencies and in the beta band; ERS oscillations in the theta and alpha bands seem to be correlated with better symptoms of FM; fatigue has a signature in the alpha band—a positive relationship in resting-state and a negative relationship in ERS oscillations. Specific neural signatures lead to potential clusters of neural adaptation, in which beta oscillatory activity in the resting state represents a more adaptive activity when pain levels are low and stimulus-evoked oscillations at lower frequencies are likely brain compensatory mechanisms. These neurophysiological changes may help to understand the impact of long-term chronic pain in the central nervous system and the descending inhibitory system in fibromyalgia subjects.

Background: Clinical predictors of sleep quality in patients with fibromyalgia syndrome (FMS) are still unknown. By identifying these factors, we could raise new mechanistic hypotheses and guide management approaches. We aimed to describe the sleep quality of FMS patients and to explore the clinical and quantitative sensory testing (QST) predictors of poor sleep quality and its subcomponents. Methods: This study is a cross-sectional analysis of an ongoing clinical trial. We performed linear regression models between sleep quality (Pittsburgh Sleep Quality Index [PSQI]) and demographic, clinical, and QST variables, controlling for age and gender. Predictors for the total PSQI score and its seven subcomponents were found using a sequential modeling approach. Results: We included 65 patients. The PSQI score was 12.78 ± 4.39, with 95.39% classified as poor sleepers. Sleep disturbance, use of sleep medications, and subjective sleep quality were the worst subdomains. We found poor PSQI scores were highly associated with symptom severity (FIQR score and PROMIS fatigue), pain severity, and higher depression levels, explaining up to 31% of the variance. Fatigue and depression scores also predicted the subjective sleep quality and daytime dysfunction subcomponents. Heart rate changes (surrogate of physical conditioning) predicted the sleep disturbance subcomponent. QST variables were not associated with sleep quality or its subcomponents. Conclusions: Symptom severity, fatigue, pain, and depression (but no central sensitization) are the main predictors of poor sleep quality. Heart rate changes independently predicted the sleep disturbance subdomain (the most affected one in our sample), suggesting an essential role of physical conditioning in modulating sleep quality in FMS patients. This underscores the need for multidimensional treatments targeting depression and physical activity to improve the sleep quality of FMS patients.