Effect of transcranial magnetic stimulation on prognosis in patients with postherpetic neuralgia and comorbid depression undergoing interventional neuromodulation therapy: protocol for a randomized double-blind placebo-controlled trial

BackgroundPostherpetic neuralgia (PHN) is often accompanied by depression, creating a vicious cycle that exacerbates symptoms and contributes to suboptimal treatment outcomes, even with interventional therapies. Repetitive transcranial magnetic stimulation (rTMS) has demonstrated potential in alleviating both pain and mood disturbances. However, its efficacy in enhancing prognosis when used alongside interventional neuromodulation therapy for PHN accompanied by depression remains inadequately explored and requires further investigation.ObjectiveThis study aims to generate preliminary evidence on the efficacy and safety of rTMS in enhancing prognosis and alleviating pain in patients with PHN and mild to moderate depression undergoing interventional neuromodulation therapy.MethodsThis study is a single-center, randomized, double-blind, placebo-controlled trial involving 174 adult patients with PHN. Participants will be randomly assigned, stratified by interventional neuromodulation therapy, to either the rTMS group (n=87) or the control group (n=87). Both groups will undergo either 10 Hz rTMS or sham stimulation for five consecutive days. The primary outcome is the incidence of poor prognosis at 3 months post-discharge. Secondary outcomes include the incidence of poor prognosis at 6 months post-discharge; Visual Analog Scale (VAS) sleep scores; short-form McGill Pain Questionnaire (SF-MPQ) scores; Self-Rating Depression Scale (SDS) scores; patient satisfaction; Pain Disability Index (PDI) scores; Multidimensional Fatigue Inventory-20 (MFI-20) scores; pregabalin oral doses; and the need for tramadol or antidepressants. Safety outcomes will include assessments of headache, pain at the stimulation site, neck pain, insomnia, muscle soreness, dizziness, nausea, tinnitus, irritability, tachycardia (heart rate > 100 bpm), and epilepsy. Data will be analyzed using a modified intention-to-treat approach.DiscussionThis study aims to provide preliminary evidence on the efficacy and safety of 10 Hz rTMS in improving prognosis and alleviating pain in PHN patients with mild to moderate depression undergoing interventional pain management.Trial registrationhttps://www.chictr.org.cn/bin/project/edit?pid=261070, identifier ChiCTR2500096978.

Prefrontal and hippocampal microstructural gray matter following cognitive training under moderate hypoxia in mood disorders: a randomized controlled trial

BackgroundCognitive impairment persists during partial or full remission in 50–70% of individuals with mood disorders and impacts daily functioning and clinical prognosis. Preclinical evidence suggests that extended exposure to moderate hypoxia, combined with motor-cognitive learning, may elevate neuroplasticity and improve cognition. In these individuals with remitted mood disorders, we found that cognitive training under repeated moderate normobaric hypoxia improved executive function, and here investigate neurobiological mechanisms.MethodsParticipants with major depressive disorder (MDD) or bipolar disorder (BD) in partial or full remission were randomized to 3 weeks of 3.5-h daily normobaric hypoxia (12% O2) combined with cognitive training five to 6 days per week or treatment-as-usual (TAU). Participants were assessed with cognitive tests and diffusion-weighted MRI at baseline and 1 month after treatment completion (week 8) as part of the ALTIBRAIN trial (ClinicalTrials.gov: NCT06121206). Prefrontal and hippocampal gray matter microstructure were modelled with Neurite Orientation Dispersion and Density Imaging (NODDI).ResultsFifty-seven participants (mean age 39 years, SD: 13, 70% female) with baseline MRI data were included. No significant effects of hypoxia-cognition training vs. TAU on neurite density index (NDI) or orientation dispersion index (ODI) were observed in either the prefrontal cortex or hippocampus (all p-FDR ≥ 0.832). No significant associations were observed between microstructural changes and changes in cognitive function in either region (all p-FDR ≥ 0.721). At baseline, microstructure in both regions was not associated with executive function or global cognition (all p > 0.40).ConclusionThe absence of detectable microstructural changes, despite selective improvements in executive function, indicates that NODDI-derived metrics did not capture structural correlates of the cognitive response to hypoxia-cognition training. Whether this reflects functional neural mechanisms, measurement insensitivity, or the timing of the single follow-up assessment remains to be determined. Future studies should incorporate multiple imaging time points to capture the dynamic trajectories of putative microstructural brain changes.

A Gamified Pain Management Intervention for Adults With Chronic Pain in Mainland China: Single-Arm Pre-Post Pilot Study With Machine Learning Predictive Modeling

Background: The widespread prevalence of chronic pain (CP) significantly impacts daily functioning worldwide. In mainland China, maintaining engagement in biopsychosocial interventions remains challenging. Gamification, designed based on self-determination theory, can enhance motivation, while machine learning (ML) algorithms can assist clinicians in dynamically optimizing pain management. Objective: This study aimed to (1) evaluate the preliminary effectiveness of a gamified pain management (GPM) program on CP and psychological outcomes and (2) identify key factors of significant pain improvements through the application of ML to guide intervention adjustments. Methods: A single-arm, pre-post study was conducted with 16 participants with CP in mainland China, recruited via social media using convenience sampling. Participants engaged in a 10-week web-based GPM intervention consisting of education, physical activities, and gamified elements, including points, avatars, and feedback. Primary outcomes were pain intensity and interference measured by the Brief Pain Inventory. Secondary outcomes included anxiety, depression, and quality of life. Analysis included paired tests, and ML models were trained to predict clinically meaningful pain reductions. Shapley additive explanations, least absolute shrinkage and selection operator regression, association rule mining, and Kaplan-Meier survival analysis were used to identify key predictors and optimal sessions and intervention durations across subgroups. Results: A total of 16 participants were engaged, with a mean age of 27.63 (SD 9.584) years. Results from paired tests reported significant improvements in pain intensity (decreased by 27.3%, 95% CI 1.061 to 3.064; =.001), pain interference (decreased by 27.3%, 95% CI 8.159-17.216; <.001), and psychological distress, including anxiety (=3.538, 95% CI 0.969 to 3.906; =.003) and depression (=4.559, 95% CI 2.230 to 6.145; <.001). The gradient boosting model demonstrated the highest predictive accuracy (area under the curve=0.89 and accuracy=0.82). Least absolute shrinkage and selection operator regression identified session 3 (β=−0.45, 95% CI −0.68 to −0.22; <.001) and session 5 (β=−0.32, 95% CI −0.59 to −0.05; =.02) as most predictive of clinical success, while association rule mining revealed effective session combinations for different patient subgroups. Time-to-event analyses indicated that individuals with low back pain and higher baseline severity required longer intervention durations for improvement (5 wk; =.03). Conclusions: This pilot study presents an innovative method that combines ML with dynamic engagement data from a GPM program during interventions, rather than relying on static baseline data in prior studies. The results show preliminary efficacy and identify specific optimal session combinations and personalized treatment durations for different pain subgroups. These exploratory findings contribute to the field by providing a data-driven method for adaptive, personalized digital health interventions that move beyond one-size-fits-all strategies, potentially enabling clinicians to modify content and dosage to improve engagement and outcomes if validated in larger sample trials. Trial Registration: Chinese Clinical Trial Registry ChiCTR2400094247; https://www.chictr.org.cn/showprojEN.html?proj=245138