Background: Spinal cord injury (SCI) frequently leads to pain, leading to significant disability. Pain sensitization, a key feature of SCI, is commonly assessed via quantitative sensory testing like the Pressure Pain Threshold (PPT), though the factors influencing PPT changes remain unclear. This study hypothesizes that specific clinical and neurophysiological factors modulate PPT in SCI patients. The primary objective is to identify predictors of PPT in SCI patients. Methods: We conducted a cross-sectional analysis of neurophysiological, clinical, and demographic data from 102 SCI patients in an ongoing prospective cohort study called “Deficit of Inhibition as a Marker of Neuroplasticity” (DEFINE study). Multivariable regression analyses were used to evaluate demographic, clinical, and functional variables associated with PPT, the primary outcome measure. Results: The sample comprised 87.9% males with an average age of 41. Trauma was the leading cause of SCI (77.45%), predominantly affecting the cervical and thoracic levels. Pain was reported by 44% of participants, and the mean PPT was 8.3 kPa, measured bilaterally. Multivariate analysis of PPT in the left, right, and bilateral thenar regions revealed consistent trends. Significant negative associations were found between bilateral PPT and low beta EEG frequency in the central area (β = −14.94, p = 0.017), traumatic lesion etiology (β = −1.99, p = 0.038), and incomplete lesions by the American Spinal Injury Association classification (β = −1.68, p = 0.012). In contrast, positive associations were observed with age (β = 0.08, p < 0.001). Conclusions: Our findings show that increased beta oscillations and traumatic brain injury having a lower PPT indicate that factors associated with maladaptive plasticity are associated with decreased and likely less functional PPT. On the other hand, increased motor function may help to regulate PPT in a more functional status.

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 While some evidence supports this association, existing systematic reviews are static and rapidly outdated, and none have leveraged advanced methods for continuous updating and robust uncertainty modeling.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.