Joao Pedro Perin

Background: Placebo effects are well documented in Parkinson’s disease (PD) clinical trials and represent a major methodological challenge in interpreting neuromodulation studies. Although sham stimulation has been associated with clinical improvement, the magnitude, durability, and outcome specificity of placebo-related effects across non-invasive neuromodulation trials remain incompletely characterized. Methods: This systematic review and meta-analysis followed PRISMA guidelines and was registered in PROSPERO (CRD1272381). PubMed/MEDLINE, Embase, Web of Science, and the Cochrane Library were searched from inception through September 2025. Randomized, sham-controlled trials of non-invasive neuromodulation in adults with PD were included. Results: Seventeen randomized sham-controlled trials (n = 654 participants) involving repetitive transcranial magnetic stimulation and transcranial direct current stimulation were included. Sham stimulation was associated with small but statistically significant improvements in UPDRS Part III (motor examination) at post-intervention and follow-up, whereas no significant placebo-related improvement was observed for UPDRS Total score. Placebo effects were modest and did not increase over time. In contrast, active neuromodulation produced larger and more durable improvements in both UPDRS Total and Part III, with statistically significant effects maintained at follow-up. Conclusions: Placebo effects contribute to short-term clinical improvement in non-invasive neuromodulation trials for PD, particularly for motor examination outcomes, but do not fully account for the sustained benefits observed with active stimulation. Placebo responsiveness is outcome- and time-dependent, underscoring the importance of rigorous trial design, including careful outcome selection, assessment timing, expectancy management, and comparator structures, to accurately estimate neuromodulation efficacy and support clinical translation.

Background: Chronic pain conditions such as fibromyalgia syndrome (FMS) reflect maladaptive network physiology across perceptual–autonomic–immune axes, yet most treatments remain symptomatic and incompletely effective. Methods: We conducted a comprehensive systematic review to evaluate vagus nerve stimulation (VNS) and FMS within a network physiology framework. PubMed, Embase, and Cochrane CENTRAL were searched on October 24, 2025. Risk of bias was assessed using the ROB-2 tool. An iterative thematic synthesis was performed to develop an integrative conceptual framework and to identify knowledge gaps and future research directions. Results: We first summarize physiological evidence showing autonomic imbalance (e.g., decreased heart rate variability), neuroinflammatory activation, and aberrant cortical network connectivity in FMS, supporting a network-dysregulation model. We then included 6 studies (4 clinical studies and 2 protocols) on VNS effects, highlighting improvements in pain, fatigue, sleep disturbance and autonomic regulation, along with emerging mechanistic insights. Key methodological heterogeneity—such as stimulation parameters, outcome metrics, type of control arm, sham definition, and small samples—limits current interpretability. Finally, we outline a research agenda centered on network-based biomarkers, immunophenotyping, adaptive trial designs and stratification of responders, with the aim of validating taVNS as a scalable neuromodulatory intervention for FMS. Conclusions: By reframing FMS from a symptom-centric pharmacologic model to a network-centric neuromodulation approach, taVNS is a promising tool for mechanism-based therapeutics in central sensitization syndromes and chronic pain.

Background: Chronic pain affects nearly one in five adults worldwide and is increasingly recognized not only as a disease but as a potential risk factor for neurocognitive decline and dementia. While some evidence supports this association, existing systematic reviews are static and rapidly outdated, and none have leveraged advanced methods for continuous updating and robust uncertainty modeling. Objective: This protocol describes a living systematic review with dose–response Bayesian meta-analysis, enhanced by artificial intelligence (AI) tools, to synthesize and maintain up-to-date evidence on the prospective association between any type of chronic pain and subsequent cognitive decline. Methods: We will systematically search PubMed, Embase, Web of Science, and preprint servers for prospective cohort studies evaluating chronic pain as an exposure and cognitive decline as an outcome. Screening will be semi-automated using natural language processing models (ASReview), with human oversight for quality control. Bayesian hierarchical meta-analysis will estimate pooled effect sizes and accommodate between-study heterogeneity. Meta-regression will explore study-level moderators such as pain type, severity, and cognitive domain assessed. If data permit, a dose–response meta-analysis will be conducted. Living updates will occur biannually using AI-enhanced workflows, with results transparently disseminated through preprints and peer-reviewed updates. Results: This is a protocol; results will be disseminated in future reports. Conclusions: This living Bayesian systematic review aims to provide continuously updated, methodologically rigorous evidence on the link between chronic pain and cognitive decline. The approach integrates innovative AI tools and advanced meta-analytic methods, offering a template for future living evidence syntheses in neurology and pain research.