Frontiers in Human Neuroscience

BackgroundUnderstanding the associations among biopsychosocial factors is essential for improving research and treatment of chronic low back pain (CLBP). Here we characterized interrelations among biopsychosocial domains using network analysis and identified the most influential features in CLBP. MethodsData came from Quebec Low Back Pain Study, comprising 4,489 CLBP participants. We modeled relationships among baseline biopsychosocial features as networks, where nodes represent features and edges encode statistical or causal dependencies among them. Undirected network was inferred using distance correlation. Directed network was constructed using the Linear Non-Gaussian Acyclic Model, which estimates plausible causal directions. Influence maximization was performed using the Independent Cascade (IC) model to identify the most influential features in each network. ResultsIn the undirected network, physical function and pain interference were the most central nodes, followed by depression. In the directed network, fear of movement, catastrophizing, and widespread pain emerged as key downstream hubs receiving multiple causal inputs, whereas pain interference, physical function, and depression acted as major upstream drivers exerting broad causal influence. IC diffusion simulations further identified pain interference and physical function as the most influential features in the undirected and directed networks, respectively. ConclusionsPain interference, physical function, and depression consistently emerged as key components of the CLBP biopsychosocial network. These features exert causal effects on fear of movement, catastrophizing, and widespread pain, with diffusion analyses confirming their roles as system-wide drivers. Interventions targeting functionality and pain interference, rather than pain intensity alone, may yield broader benefits across psychological and functional domains.

Sensory gating -- the brains ability to filter out repetitive sensory input -- is essential for preventing sensory overload. Impaired gating is frequently observed in nociplastic and other chronic overlapping pain conditions, yet the specific brain regions supporting this inhibitory process in humans remains unclear. Neuroimaging studies examining pain processing implicate the anterior insula (AI), posterior insula (PI), and anterior mid-cingulate cortex (aMCC), but their deeper locations limit direct mechanistic testing using conventional non-invasive techniques. Here, we leveraged low-intensity focused ultrasound (LIFU), a novel non-invasive neuromodulation method with high depth-penetration and millimeter resolution, to examine the contributions of the AI, PI, and aMCC to sensory gating of nociceptive stimuli. Twelve healthy adults completed four counterbalanced visits of a paired-pulse contact heat evoked potential (CHEP) paradigm while receiving LIFU targeted to each region or an active sham. Using surface electroencephalography (EEG), placed at site Cz, we quantified the peak-to-peak (P2P) amplitude of the cortical response to the first stimulus (S1), the second stimulus (S2), and used the ratio of the response to each stimulus (S2/S1 ratio) as an index of sensory gating. Subjective ratings of pain intensity to the second stimulus were also recorded. Results demonstrated that all subjects displayed sensory gating at baseline and thatLIFU produced region-specific effects. Both PI and aMCC neuromodulation reduced subjective pain ratings and significantly decreased S2 amplitude relative to sham, whereas LIFU to AI had no effect. Critically, only PI neuromodulation enhanced sensory gating by reducing the S2/S1 ratio. These findings identify the PI as a key contributor to gating of repetitive nociceptive input and a promising neuromodulation target for remediating sensory gating deficits in nociplastic pain.

New-onset chronic pain is a common and debilitating symptom of Long COVID (LC) that remains not fully understood in terms of pathophysiology and therapeutic targets. A growing body of evidence in chronic pain syndromes similar to LC demonstrates an association between EEG alpha oscillatory activity and the experience of pain, with clinical studies showing maladaptive changes in oscillatory activity, particularly a slowing of alpha activity. This study aims to investigate the association between EEG alpha oscillatory activity and pain perception in new-onset LC-chronic pain. We recruited 31 individuals (20 females) with a clinical diagnosis of LC reporting new-onset chronic pain and 31 healthy pain-free age-and sex-matched controls. Participants completed questionnaires regarding symptoms and psychological functioning prior to recording eyes-open resting-state EEG. Peak alpha frequency (PAF) and spectral power within the alpha band (8-13 Hz) were extracted from EEG signals. Lower PAF over the posterior scalp region was significantly associated with higher LC-chronic pain severity when controlling for age and depression. This observation was consistent across PAF estimation methods. PAF was significantly increased, particularly in the posterior region, in the moderate pain LC subgroup compared to both severe pain subgroup and controls, while alpha power did not differ between the three groups and was not associated with pain severity. Our findings highlight associations between PAF and pain symptoms in a new post-infection chronic pain syndrome. PAF can thus be explored as a potential biomarker and therapeutic target for EEG-based neuromodulation interventions in LC-chronic pain. These results may have implications for other similar chronic pain syndromes. SummaryLower resting-state EEG peak alpha frequency in posterior scalp region is associated with higher severity of new-onset Long COVID chronic pain.

Chronic pain (CP) is a multidimensional condition characterized by physical, emotional, and cognitive symptoms. However, many neuroimaging studies investigating the brain mechanisms of CP have focused on single-domain measures, most commonly pain intensity. Incorporating multidimensional symptom profiles may advance the understanding of CP, its neural underpinnings, and the development of clinically actionable biomarkers. Here, we aimed to empirically derive symptom dimensions of CP and relate them to resting-state brain activity and connectivity measured by electroencephalography (EEG). Using a data-driven approach, we identified latent symptom dimensions in 207 individuals with CP based on the brief, internationally validated PROMIS-29 profile, which assesses general health across key physical, mental, and social domains. Principal component analysis revealed two dimensions, affective burden and physical burden, closely corresponding to established PROMIS-derived health dimensions in other clinical populations. Resting-state EEG was obtained in a subsample of 116 participants using a mobile, rapid-to-deploy 29-channel dry-electrode system. Bayesian regression analyses provided moderate to strong evidence for a negative association between affective burden and beta-band connectivity, particularly in left frontal and somatomotor regions. Together, these findings demonstrate how empirically derived symptom dimensions captured by PROMIS-29 can be linked to scalable, network-level EEG biomarkers. This framework illustrates an EEG-informed strategy for biopsychosocial stratification in CP, with potential relevance for personalized symptom-targeted interventions.

Repetitive transcranial magnetic stimulation (rTMS) of non-motor cortical targets, including the left dorsolateral prefrontal cortex (DLPFC), anterior cingulate cortex (ACC), and posterosuperior insula (PSI), has been proposed as a treatment for chronic pain with variable clinical outcomes. Pre-treatment local cortical dynamics were hypothesized to serve as markers of chronic pain reduction. In this secondary analysis of a large clinical trial comparing different rTMS targets for pain relief, it was examined whether pre-treatment evoked cortical responses measured by electroencephalography after TMS of DLPFC, ACC, or PSI were associated with at least 30 percent reduction in pain intensity scored on a visual analogue scale. Forty-five patients with chronic pain received 12 sessions over eight weeks of 10 Hz rTMS to DLPFC, ACC or PSI. Cortical reactivity was quantified using global and local mean field power, and oscillatory dynamics were assessed using event-related spectral perturbation (ERSP) and inter-trial coherence (ITC) in the alpha-band (8-12 Hz). Responders (20 of 45, 44%) compared with non-responders showed higher pre-treatment alpha-band ERSP and ITC over the stimulated cortical targets (both P<0.05), and higher alpha-band ERSP and ITC values were negatively correlated with the percentage change in pain intensity (both P < 0.05). These results suggest that elevated pre-treatment TMS-evoked alpha-band oscillatory activity may indicate a higher probability of pain reduction to non-motor rTMS in chronic pain. This supports the development of enrichment strategies using cortical neurophysiology-based markers in neuromodulation trials aimed at individualized, precision-oriented treatments.

BackgroundPatients understanding of pain and its biopsychosocial nature is thought to be important in order to optimize treatment decisions and treatment outcomes. A validated Spanish questionnaire for patients based on a biopsychosocial model assessing knowledge and attitudes of pain was unavailable. The aim of this study is to validate the Spanish version of the PACKA, to have a Spanish questionnaire to be used among pain patients in both clinical and research settings. MethodsPhase 1: forward and backward translation, and expert committee; Phase 2: a cross-sectional and longitudinal study among Fibromyalgia patients. In the cross-sectional study (n =330), internal consistency, structural validity and hypothesis testing were examined. ResultsThe 26-item PACKA was translated and validated in 4 stages. Acceptable internal consistency and test-retest reliability was demonstrated. Internal consistency: Cronbachs =0.776. Hypotheses testing: associations with the Neurophysiology of Pain Questionnaire r =0.31. ConclusionThis Spanish version of PACKA has shown acceptable validity and reliability in patients with Fibromyalgia. Further use and reanalysis of the questionnaire might improve this preliminary validation.

BackgroundChronic pain affects 28 million UK adults. While physiotherapy and social prescribing are recognised as effective, evidence on integrating them remains limited. Digital biomarkers could objectively assess movement quality and pain physiology to support clinical decision-making. ObjectivesTo explore whether simple kinematic and electroencephalography (EEG) biomarkers can discriminate between correct versus incorrect exercise performance and high versus low pain states, and to consider how such tools might streamline social prescribing pathways for chronic pain. MethodsSecondary analyses of two open datasets: (1) KERAAL kinematic dataset: 900 recordings of trunk rotation exercises (21 participants) labelled "correct" or "incorrect" by physiotherapists; (2) EEG dataset: 145 resting-state recordings (100 individuals with chronic pain) categorised as high or low pain. Classification models (logistic regression, support vector machines, gradient boosting) were trained on extracted kinematic features (range of motion, smoothness, symmetry, jerk, coordination) and EEG features (frontal alpha asymmetry, connectivity, sample entropy, aperiodic exponents). Performance was assessed using accuracy, F1 score, AUC and calibration curves. ResultsKinematic classification achieved near-perfect performance: 100% accuracy and AUC = 1.00. Key features were shoulder abduction peak angle, symmetry index and jerk. EEG classification was strong: 93% accuracy, 0.97 AUC. Global theta and alpha connectivity, frontal alpha asymmetry and sample entropy were most informative. ConclusionAutomated kinematic and EEG markers can reliably differentiate correct exercise performance and current pain state. These digital biomarkers could inform physiotherapists and link workers when triaging patients into social prescribing programmes. Integrating digital assessment into social prescribing may reduce unnecessary appointments, enhance self-management and align care with the biopsychosocial model. Further studies should validate the approach in broader populations and examine implementation in real-world social prescribing services.

In this randomized, double-blind, controlled trial of 8 weeks of repetitive transcranial magnetic stimulation (rTMS) for chronic pain, we compared the classic primary motor cortex (M1) rTMS with a novel target-selection strategy based on pre-therapy cortical connectivity. Guided by principles of homeostatic plasticity, we tested whether stimulating the cortical site with the lowest pre-therapy global connectivity would be more effective than two active comparators: stimulating the site with the highest pre-therapy global connectivity or stimulating M1 independent of connectivity. Before starting rTMS treatment, TMS-evoked EEG potentials were recorded from four cortical targets: M1, the dorsolateral prefrontal cortex, the anterior cingulate cortex, and the posterosuperior insular cortex. For each target, global connectivity was quantified using a distance-weighted, phase-based index (debiased weighted phase lag index, wPLI) derived from pre- and post-TMS-evoked EEG activity, capturing both the magnitude and spatial extent of TMS-induced oscillatory phase locking across cortical regions. Target allocation in the Low- and High-Connectivity groups was based on this global connectivity measure. Ninety patients with chronic pain were randomized to Low-Connectivity, High-Connectivity, or Classic-M1 groups. Treatment consisted of 12 rTMS sessions delivered over 8 weeks to the assigned target. The primary outcome was the proportion of patients achieving [&ge;] 30% reduction in pain intensity. Secondary outcomes included continuous change in pain intensity, pain interference, sleep, fatigue, mood, quality of life, and patient global impression of change. No between-group differences were observed for primary or secondary outcomes (p > 0.05). In prespecified exploratory analyses, we examined whether pre-therapy local connectivity (within-target wPLI) predicted treatment response. In the Classic-M1 group, lower pre-therapy local M1 connectivity was associated with a greater reduction in pain intensity (r = 0.50, p = 0.005). This association was not observed in the Low- or High-Connectivity groups. A regression model including group-by-connectivity interaction indicated that the relationship between local connectivity and pain reduction differed between the Classic-M1 and High-Connectivity groups (p = 0.038). The results of this clinical trial showed that connectivity-based target allocation using global connectivity did not improve clinical outcomes. However, lower local M1 connectivity was associated with greater pain reduction following Classic-M1 stimulation, suggesting that local M1 connectivity may serve as a potential biomarker of response.

BackgroundNeuropathic pain (NP) is a debilitating chronic pain condition caused by injury or disease of the somatosensory nervous system. Accumulating evidence indicates that astrocytes play a central role in neuroinflammatory regulation and synaptic remodeling, thereby critically influencing the initiation and persistence of neuropathic pain. However, a comprehensive overview of research trends and knowledge structures in this field is still lacking. MethodsThe analysis was conducted based on publications retrieved from the Web of Science Core Collection and Scopus, covering the period from 2000 to 2025. Studies focusing on astrocytes and neuropathic pain were systematically identified. Visualization and network analyses were performed using CiteSpace, VOSviewer, and the R package bibliometrix. Collaboration networks, co-citation patterns, keyword co-occurrence, and thematic evolution were analyzed to delineate research hotspots, developmental trajectories, and scholarly contributions across countries, institutions, authors, and journals. Results1,828 publications were included, showing a 15% average annual growth in output, which accelerated post-2010. The USA and China led in research and international collaboration, with studies concentrated in North American and East Asian institutions. Author productivity was uneven, with key researchers (Ji RR, Zhang Y, Watkins LR) contributing heavily to publications and citations. Pain and Molecular Pain were the core journals. Key themes included spinal astrocytic mechanisms, glial activation, and therapeutic modulation, with the focus evolving from injury models/markers to astrocytic activation and targeted pathways. ConclusionOur analysis shows a substantial growth in astrocyte-related NP research the past 25 years, underscoring astrocytes key role in chronic pain pathophysiology. Current trends underscore the integration of mechanistic insights with translational relevance, thereby informing future therapeutic and mechanistic advancements in NP.

Chronic pain is increasingly conceptualized within a stress-related framework. However, it remains unclear whether chronic pain and prototypical stress-related conditions--such as post-traumatic stress disorder (PTSD)--share common neurobiological substrates. To this end, we conducted a pre-registered transdiagnostic meta-analytic study of gray matter volume alterations in chronic pain (60 studies) and PTSD (20 studies). Disorder-specific meta-analyses revealed that chronic pain was associated with distributed volume reductions across ventromedial prefrontal, middle cingulate, and insular cortices, whereas PTSD exhibited a single cluster of reduced volume in the anterior cingulate/dorsomedial prefrontal cortices. A conjunction analysis revealed that both conditions converged onto an overlapping cluster of reduced volume in the bilateral medial orbitofrontal/anterior cingulate area. Using normative resting-state fMRI data (HCP 7T dataset), we found that chronic pain neuroanatomical abnormalities were embedded within a distributed architecture of large-scale circuits encompassing mesocorticolimbic/reward, default mode, salience, frontoparietal, dorsal attention, and somatosensory networks. On the other hand, the PTSD focal neuroanatomical alteration was embedded in a single large-scale circuit mapping onto the mesocorticolimbic/reward, default mode, salience, and visual networks. In both conditions, the mesocorticolimbic/reward circuit emerged as the most robustly involved large-scale network. Notably, the shared cluster of reduced volume showed functional integration within the mesocorticolimbic/reward and default mode networks, with neurochemical fingerprinting revealing robust spatial correspondence with dopaminergic, serotonergic, opioid, and endocannabinoid receptor/transporter maps. Overall, these findings suggest that chronic pain and PTSD, beyond disorder-specific alterations, converge on a shared large-scale network organization. The overlap between chronic pain and a prototypical stress-related disorder at the network level provides neurobiological support for conceptualizing chronic pain within a stress-related framework.

Resting-state electroencephalography (EEG) has been proposed as a scalable source of biomarkers for chronic pain, but its clinical potential remains uncertain. To systematically evaluate this potential, we benchmarked nine modeling strategies, spanning conventional machine learning with handcrafted features to state-of-the-art deep learning. Across 72 configurations of signal representations and model architectures, we trained models to predict self-reported pain intensity, using chronological age decoding as a positive control. Pain prediction performance was limited (R=0.15), with the best results achieved by conventional connectivity-based models. In contrast, age was robustly decoded from the same dataset (R=0.53), confirming technical efficacy. These findings indicate that resting-state EEG contains limited information about inter-individual differences in chronic pain intensity, making it unlikely to yield clinically actionable biomarkers in cross-sectional settings. Instead, its potential may lie in intra-individual modeling of pain dynamics, which could advance individualized mechanistic insights and more personalized treatment of chronic pain.

Why some surgical participants experience pain that extends beyond the original site of injury while others do not remains poorly understood. Both pain intensity and widespread pain contribute to recovery and quality of life, yet their psychosocial correlates are often examined separately. Using data from two large pre-surgical cohorts--participants preparing for knee replacement or thoracic surgery--we examined associations between sociodemographic and psychosocial factors, pain intensity at surgical and non-surgical sites, and widespread chronic pain. Across cohorts and outcomes, fatigue showed the strongest and most consistent associations with pain intensity and widespread pain, independent of other measured factors. Fatigue also occupied a central position in statistical association networks and accounted for substantial shared variance among multiple psychosocial variables, including sleep disturbance, depression, stress, and socioeconomic disadvantage. Pain at non-surgical sites was strongly associated with widespread pain and frequently accounted for observed associations between surgical-site pain and widespread pain. Together, these findings highlight robust patterns of association linking fatigue, pain intensity, and widespread pain in pre-surgical populations. One Sentence SummaryFatigue is the strongest and most consistent factor linked to how pain intensifies and spreads before surgery.

IntroductionChronic pain in fibromyalgia may be driven by abnormal ongoing activity in a subclass of C-fibre nociceptors known as Type1B or CMi nociceptors. As is common in C-nociceptor microneurography studies, the modest patient numbers in these prior studies generate large confidence intervals around the point estimate of the prevalence of this abnormal activity. This complicates the interpretation of the relative importance of this ongoing nociceptor activity as a pain generating mechanism in fibromyalgia. The study aims to improve precision via an adaptive Bayesian protocol that maximises the yield and quality of data collection whilst minimising patient burden. MethodsThe study employs an optimised microneurography protocol with an adaptive study design. The microneurography protocol incorporates early identification of CMi nociceptors via an abbreviated activity dependent slowing protocol to increase yields enabling efficient collection of the primary outcome data. The adaptive study design will use Bayesian principles to iteratively assess the predictive probability of futility, and terminate early if there is high confidence that the hypothesis is false. Furthermore, the study will employ questionnaires to explore links with pain in the area under study to the electrophysiology data. Finally, quantitative sensory testing will be used to investigate whether the irritable nociceptor phenotype is associated with abnormalities in CMi nociceptor physiology. Ethics & DisseminationThis study has received HRA REC approval in the UK. Participants will provide written informed consent, and may withdraw at any time without consequence. At the end of the study, the results will be disseminated through peer-reviewed publication, and the data made available via a data repository. Strengths & limitations of this studyBayesian predictive probability of futility to minimise patient burden in microneurography Microneurography for objective interrogation of the peripheral nervous system Optimised microneurography protocol to efficiently answer primary hypotheses Subjective elements of early termination criteria of the study assessed and co-developed with Patient and Public Inclusion and Engagement Group

BackgroundPersistent Spinal Pain Syndrome (PSPS) type II represents a challenging clinical entity with limited therapeutic options. Various spinal cord stimulation (SCS) modalities have emerged as potential treatments, but their comparative effectiveness remains unclear. ObjectiveOur goal in this paper is to systematically evaluate and compare the efficacy of different SCS modalities in patients with PSPS type II through meta-analysis of available randomized controlled trials. Evidence ReviewWe conducted a systematic review following PRISMA guidelines, searching major databases for randomized controlled trials evaluating SCS modalities in PSPS type II patients until the end of May 2025(search updated on October 3rd). Primary outcomes included pain intensity (VAS) and functional disability (ODI) at 6 and 12 months. Subgroup analyses compared tonic versus burst stimulation and high-frequency versus low-frequency SCS. FindingsNine randomized controlled trials were included, encompassing 565 patients across different SCS modalities. For the primary outcome of clinically meaningful pain relief ([&ge;]50% reduction), pooled analysis demonstrated that 45% (95% CI: 18-75%, I{superscript 2} = 92.2%) of patients achieved this threshold for back pain and 55% (95% CI: 45-65%, I{superscript 2} = 0%) for leg pain. Subgroup analysis revealed significant differences in back pain responder rates by stimulation modality: High-frequency SCS demonstrated responder rates of 92% (95% CI: 79-98%) versus 28% (95% CI: 13-49%) for conventional frequencies (p < 0.001). For leg pain, no significant difference was observed between tonic (51%, 95% CI: 37-65%) and burst stimulation (60%, 95% CI: 45-74%, p = 0.36) and mean VAS scores demonstrated significantly lower pain with high-frequency SCS (13.30, 95% CI: 8.82-17.78) compared to conventional frequency (28.42, 95% CI: 24.02-32.88, p<0.0001). For back pain, mean VAS scores decreased from a baseline of 73.03 to 41.67 (95% CI: 36.12-47.22, I{superscript 2}=22.8%) at 6 months and remained stable at 35.66 (95% CI: 25.39-45.93, I{superscript 2}=75.0%) at 12 months. Leg pain showed more pronounced improvement, with VAS scores declining from a baseline of 61.81 to 23.75 (95% CI: 17.69-29.81, I{superscript 2}=78.8%) at 6 months and 29.16 (95% CI: 24.81-33.52, I{superscript 2}=0%) at 12 months). Meta-regression identified longer pain duration and older age as positive predictors of response, while higher baseline leg pain predicted lower responder rates. Serious adverse events occurred in 10%, with a 16% revision surgery rate. Only two studies demonstrated a low risk of bias across all domains. ConclusionsCurrent evidence demonstrates that various SCS modalities provide clinically meaningful pain relief in PSPS type II patients, with approximately half achieving [&ge;]50% pain reduction. High-frequency SCS shows significantly superior responder rates for back pain compared to conventional tonic stimulation, while burst stimulation yields significantly superior reductions in continuous pain intensity metrics. However, the limited number of studies, substantial heterogeneity, and lack of head-to-head comparisons prevent definitive recommendations regarding optimal stimulation parameters. Future large-scale randomized trials with standardized protocols and responder-based outcomes are needed to establish evidence-based treatment algorithms for PSPS type II patients.

BackgroundInertial measurement units (IMUs) have potential to be inexpensive, portable sensors for collecting gait parameters and joint kinematics. Current validation protocols generally do not investigate IMU accuracy in measuring altered gait; therefore, they cannot assess an IMUs ability to detect pathologies. The Stridelink IMU-based gait analysis device is intended for use in detecting and monitoring gait abnormalities, thus there is a need to evaluate the devices accuracy under abnormal gait conditions. Research questionHow well do measurements from the StrideLink IMU agree with motion capture (MoCap), particularly when gait is mechanically altered to simulate pathology? MethodsTwenty-eight healthy participants (ages 18-40) were analyzed during a one-minute tread-mill walk with Vicon MoCap and StrideLink. Tests were performed under normal and mechanically induced abnormal conditions (knee brace, walking boot). Equivalence testing and correlation analysis evaluated StrideLinks accuracy against MoCap. ResultsStrideLink showed statistical equivalence (within 5%) for average cadence, stride, swing, and stance times but not double support time. Many metrics were statistically equivalent (p < .001) despite induced abnormalities. Correlation analysis showed almost perfect agreement with MoCap for stride times, cadence, and stance. However, the abnormal gait protocol revealed nuances not observed in normal gait; specifically, the device underestimated swing time by [~]10 ms in knee brace restricted limbs. SignificanceThis study utilized mechanically induced gait abnormalities to assess the robustness of IMU measurements. Results indicate StrideLink yields valid temporal gait measurements comparable to reference systems, even under conditions of significant deviation, supporting the utility of using induced abnormalities for sensor validation.

BackgroundHealth literacy (HL) influences communication quality, treatment adherence, and equity in care. However, how general practitioners (GPs) recognize and respond to patients HL in everyday clinical reasoning remains insufficiently understood. ObjectiveTo investigate how Danish GPs incorporate patients health literacy into decisions about prescribing pain medication for chronic musculoskeletal pain, using insights from surveys, interviews, and a literature review. MethodsA mixed-methods design combined survey data from 39 Danish GPs, seven qualitative interviews, and a synthesis of 14 studies on HL in general practice. The literature was used to contextualize and contrast the empirical findings. Quantitative data were analyzed descriptively, while qualitative data underwent thematic analysis. All three datasets were integrated through mixed-methods comparison to assess convergence, divergence, and complementarity. ResultsAcross the integrated survey, interview, and literature findings, HL emerged as a largely implicit but consistent element of GP decision-making. In the Danish survey and interview data, some GPs explicitly reported considering HL in prescribing decisions, yet interviews showed that HL more often influenced clinical reasoning indirectly through intuition and conversation. GPs adapted communication, explanations, and treatment planning to their perceptions of patient understanding, but these adjustments were rarely guided by structured tools or frameworks. Conversation appeared as the main approach for assessing comprehension, echoing patterns observed in the literature. Many Danish GPs perceived most patients as competent and self-managing, a perception the literature cautions may mask hidden comprehension challenges. Finally, both local interviews and existing studies highlighted digital HL as an emerging theme, with GPs commonly managing patients online health information through conversational reframing rather than formal strategies. ConclusionsHL is tacitly integrated into GP reasoning but remains under-recognized as a professional skill. Making HL an explicit component of communication training, reflective practice, and prescribing guidelines could improve patient understanding, shared decision-making, and treatment equity.

We performed the first systematic review and meta-analysis of the prevalence of pain with neuropathic characteristics using Bayesian methods to correct prevalence estimates for the use of screening tools with imperfect sensitivity and specificity (CRD42023416845). We searched major databases for national or regional epidemiological studies that reported the prevalence of pain with neuropathic characteristics, as identified by the PainDETECT, S-LANSS, or DN4-interview. Of the 1,251 unique records retrieved, 8 were finally extracted. The uncorrected (apparent) prevalence data were pooled using a random-effects meta-analysis for proportions. The corrected (true) prevalence was estimated using Bayesian models incorporating sensitivity and specificity distributions under non-informative [beta(1,1)] and informative priors [beta(4.389, 29.522); based on apparent prevalence]. Using the mean values from Bayesian credible intervals, a pooled estimate of true prevalence was generated using a random-effects model. The pooled estimate for the apparent prevalence was 10.6% (95% CI: 8.5; 12.9). The pooled estimate for true prevalence was 4.9% (95% CI: 3.8; 6.1) using informative priors, and 2.3% (95% CI: 1.5; 3.2) using non-informative priors. The use of imperfect screening tools may have overestimated the prevalence of neuropathic pain. PerspectiveThe prevalence of neuropathic pain may be lower than previously estimated. A lower prevalence should not be equated with reduced societal or clinical significance, but it may have implications for healthcare resource allocation and research funding policies for neuropathic pain.

BackgroundArthroscopic release for elbow stiffness is considered a minimally invasive and effective treatment. However, the extent to which each intraoperative step contributes to improvement in range of motion (ROM) has not been well investigated. PurposeTo sequentially evaluate the relationship between intraoperative surgical steps and changes in elbow ROM during arthroscopic release for severe elbow stiffness, and to identify the key procedural stage contributing most significantly to ROM improvement. MethodsFive elbows in five patients with severe elbow stiffness following fracture or dislocation were retrospectively reviewed. Arthroscopic release was performed using a stepwise posterior-based approach, starting from the posterior soft-spot portal, followed by exposure of the olecranon fossa and progression into the posteromedial compartment. Changes in elbow ROM were assessed at each intraoperative step, and ROM at final follow-up was also evaluated. ResultsAll patients demonstrated improvement in elbow ROM at final follow-up. Intraoperative ROM improvement did not occur in a continuous manner but rather in a stepwise fashion. Gradual improvement was observed with establishment of the posterior and posteromedial working spaces, followed by the most substantial increase in ROM immediately after release of the soft tissue attached to the posterior aspect of the humeral medial epicondyle. Although the maximum ROM achieved intraoperatively was not fully maintained at final follow-up, no patient experienced deterioration to preoperative ROM levels. ConclusionsIn arthroscopic release for severe elbow stiffness, improvement in elbow ROM occurs in a stepwise rather than continuous pattern. Release of the posteromedial structures attached to the posterior aspect of the humeral medial epicondyle may represent a critical turning point contributing significantly to ROM improvement.

PurposeTo evaluate the predictive value of the thoracic spine-clavicle angle (TSCA) and the thoracic cage-clavicle angle (TCCA) for immediate postoperative shoulder balance. MethodsA total of 154 Lenke type 1 and 2 AIS patients who underwent corrective surgery in our hospital were included. The degree of clavicle angle (CA), thoracic spine tilt angle (TSTA), thoracic cage tilt angle (TCTA), proximal thoracic curve (PTC) Cobb angle, and main thoracic curve (MTC) Cobb angle were measured on standing full-length posteroanterior spine radiographs before and after surgery. Five parameters, TSCA, TCCA, correction rate of PTC, correction rate of MTC, relative PT/MT residual Cobb angle (RRCA), were calculated. Multinomial Logistic Regression was used to determine the risk factors of PSB. A p-value of less than 0.05 was considered statistically significant. ResultsFor TCCA, in group R (vs group B), pre-op right high (vs pre-op left high) (OR=8.102, 95%CI [1.650, 39.786], p=0.01) and RRCA (OR=1.015, 95%CI [1.004, 1.026], p=0.009) are risk factors. Pre-op left high (vs pre-op right high) (OR=0.123, 95%CI [0.025, 0.606], p=0.01) and correction rate of MTC (OR=0.886, 95%CI [0.809, 0.971], p=0.009) are protective factors. Correction rate of PTC shows no significant effect. In group L (vs group B), pre-op left high (vs pre-op right high) (OR=2.648, 95%CI [1.084, 6.469], p=0.033) is a risk factor. Pre-op right high (vs pre-op left high) (OR=0. 378, 95%CI [0. 155, 0.922], p=0. 033) is a protective factor. Correction rate of PTC, correction rate of MTC, and RRCA show no significant effect. ConclusionPreoperative shoulder balance, as defined by the TCCA, serves as an independent risk factor for PSB. Using postoperative balanced shoulders as the reference group, preoperative left shoulder high (vs right high) significantly increased the risk of postoperative left shoulder high, while significantly reducing the risk of postoperative right shoulder high. Preoperative right shoulder high (vs left high) significantly increased the risk of postoperative right shoulder high, while significantly reducing the risk of postoperative left shoulder high. The correction rate of MTC was an independent protective factor against postoperative right shoulder high, whereas RRCA was an independent risk factor for postoperative right shoulder high.

BackgroundReverse total shoulder arthroplasty (rTSA) is an increasingly common surgical procedure often performed to treat pain related to glenohumeral osteoarthritis or to rotator cuff arthropathy. Although surgical outcomes are generally excellent, recent evidence has found that postoperative pain ([&ge;] 3/10) two years following surgery is reported by an estimated 18% of patients. Recently, the NIH Acute-to-Chronic Pain Signatures program recommended longitudinal studies using select biomarkers to describe and predict individual patient responses to surgery. These data are not yet available for rTSA procedures. MethodsThis was a longitudinal cohort study performed at a single academic medical center. Twenty participants undergoing rTSA surgery were included, recruited from a tertiary hospital system in the southern United States. The first objective of this study was to describe changes in general pain intensity (Numerical Pain Rating Scale), widespread body pain, anxiety (General Anxiety Disorder-7), depression (Patient Health Questionnaire-9), neuropathic pain symptoms (painDETECT), and quantitative sensory testing from baseline to 6 weeks following rTSA. The second objective was to identify the baseline demographic and pain-related factors associated with 6-week postsurgical improvements in pain intensity. ResultsFrom before to after surgery, our cohort demonstrated significant improvement in shoulder pain intensity, widespread body pain, PainDETECT score, and temporal summation magnitude measured at the surgical deltoid. Degree of 6-week pain intensity improvement was associated with baseline pain intensity (F=18.79, p=0.0004) and temporal summation magnitude of the tibialis anterior (F=5.06, p=0.0380). ConclusionsPain intensity, location, nature, and mechanism can serve as biomarkers of the short-term postsurgical changes that can be expected following rTSA. Baseline pain intensity and temporal summation magnitude of the tibialis anterior were associated with the degree of pain improvement, suggesting their use for preoperative risk assessment. Future research should evaluate whether these 6-week biomarker changes are associated with the development of chronic postoperative pain at longer durations after surgery. Level of EvidenceLevel I, Prognostic Study