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Borrowing treatment principles from acute and end-of-life pain care, particularly a focus on pain intensity, has had harmful consequences for patients with chronic pain. Multimodal therapy, by contrast, aims to reduce pain-related distress, disability, and suffering. Pain causes widespread suffering, disability, social displacement, and expense. Whether the issue is viewed from a moral, political, or public health perspective, pain that can be relieved should be relieved. Yet the most rapidly effective drugs for relieving pain — opioids — are caught up in a morass of concerns about addiction. Achieving a balance between the benefits and potential harms of opioids has become a matter of national importance. The United States recently established a national plan to address pain, as Canada, Australia, Portugal, and Malaysia have previously done. 1 This National Pain Strategy grew out of recognition by the . . .

ObjectivesTo gain expert-judgement-free insight into the Gestalt of axial spondyloarthritis (axSpA), by investigating its ‘latent constructs’ and to test how well these latent constructs fit the Assessment of SpondyloArthritis international Society (ASAS) classification criteria.MethodsTwo independent cohorts of patients with early onset chronic back pain (SPondyloArthritis Caught Early (SPACE)) or inflammatory back pain (IBP) (DEvenir des Spondylarthopathies Indifférenciées Récentes (DESIR)) were analysed. Latent class analysis (LCA) was used to estimate the (unobserved) potential classes underlying axSpA. The best LCA model groups patients into clinically meaningful classes with best fit. Each class was labelled based on most prominent features. Percentage fulfilment of ASAS axSpA, peripheral SpA (pSpA) (ignoring IBP) or both classification criteria was calculated. Five-year data from DESIR were used to perform latent transition analysis (LTA) to examine if patients change classes over time.ResultsSPACE (n=465) yielded four discernible classes: ‘axial’ with highest likelihood of abnormal imaging and HLA-B27 positivity; ‘IBP+peripheral’ with 100% IBP and dominant peripheral symptoms; ‘at risk’ with positive family history and HLA-B27 and ‘no SpA’ with low likelihood for each SpA feature. LCA in DESIR (n=576) yielded similar classes, except for the ‘no-SpA’. The ASAS axSpA criteria captured almost all (SPACE: 98%; DESIR: 93%) ‘axial’ patients, but the ‘IBP+peripheral’ class was only captured well by combining the axSpA and pSpA criteria (SPACE: 78%; DESIR: 89%). Only 4% of ‘no SpA’ patients fulfilled the axSpA criteria in SPACE. LTA suggested that 5-year transitions across classes were unlikely (11%).ConclusionThe Gestalt of axSpA comprises three discernible entities, only appropriately captured by combining the ASAS axSpA and pSpA classification criteria. It is questionable whether some patients with ‘axSpA at risk’ will ever develop axSpA.

Background: The awareness is growing that central sensitization is of prime importance for the assessment and management of chronic pain, but its classification is challenging clinically since no gold standard method of assessment exists. Objectives: Designing the first set of classification criteria for the classification of central sensitization pain. Methods: A body of evidence from original research papers was used by 18 pain experts from 7 different countries to design the first classification criteria for central sensitization pain. Results: It is proposed that the classification of central sensitization pain entails 2 major steps: the exclusion of neuropathic pain and the differential classification of nociceptive versus central sensitization pain. For the former, the International Association for the Study of Pain diagnostic criteria are available for diagnosing or excluding neuropathic pain. For the latter, clinicians are advised to screen their patients for 3 major classification criteria, and use them to complete the classification algorithm for each individual patient with chronic pain. The first and obligatory criterion entails disproportionate pain, implying that the severity of pain and related reported or perceived disability are disproportionate to the nature and extent of injury or pathology (i.e., tissue damage or structural impairments). The 2 remaining criteria are 1) the presence of diffuse pain distribution, allodynia, and hyperalgesia; and 2) hypersensitivity of senses unrelated to the musculoskeletal system (defined as a score of at least 40 on the Central Sensitization Inventory). Limitations: Although based on direct and indirect research findings, the classification algorithm requires experimental testing in future studies. Conclusion: Clinicians can use the proposed classification algorithm for differentiating neuropathic, nociceptive, and central sensitization pain. Key words: Chronic pain, diagnosis, hypersensitivity, classification, neuropathic pain

Due to the complexity of pain, involving physical, psychological, emotional and social aspects, we are still unable to objectively quantify or fully understand this subjective experience. An increasing number of studies have attempted to identify biomarkers of pain using brain imaging tools like magnetoencephalography (MEG). In this study, we used machine learning to investigate the potential of MEG data as a biomarker for chronic pain and used this biomarker to quantify spinal cord stimulation (SCS) treatment effect. The study population consisted of 25 patients with SCS, for whom we recorded resting-state MEG during tonic, burst and sham stimulation, 25 patients with chronic pain and 25 pain-free controls. We derived average power spectral densities across each of the 94 automated anatomical labeling atlas based brain regions and extracted six spectral features: the alpha peak frequency, alpha power ratio, and average power across the theta, alpha, beta, and low-gamma bands. Based on these features, we used automated machine learning to find the optimal combination of machine learning methods to create classification and regression models for pain and pain intensity. The theta power and alpha power ratio were the most promising features to classify chronic pain with an accuracy of 76%. The classification model outputs and self-reported pain scores of patients with SCS showed a Spearman correlation coefficient of 0.12. A regression model based on pain scores of all participants showed Spearman correlation coefficients between 0.27 and 0.41. This study achieved a promising 76% accuracy in classifying patients with chronic pain and pain-free controls using the theta power or alpha power ratio. However, this model's output poorly correlated with pain scores of patients with SCS. A larger variety of input features and outcome parameters is recommended.

Unlike acute pain that warns us of injury or disease, chronic or persistent pain serves no adaptive purpose. Though there is no agreed on definition of chronic pain, it is commonly referred to as pain that is without biological value, lasting longer than the typical healing time, not responsive to treatments based on specific remedies, and of a duration greater than 6 months. Chronic pain that is severe and intractable has detrimental consequences, including psychological distress, job loss, social isolation, and, not surprisingly, it is highly comorbid with depression and anxiety. Historically, pain without an apparent anatomical or neurophysiological origin was labelled as psychopathological. This approach is damaging to the patient and provider alike. It pollutes the therapeutic relationship by introducing an element of mutual distrust as well as implicit, if not explicit, blame. It is demoralizing to the patient who feels at fault, disbelieved, and alone. Moreover, many medically unexplained pains are now understood to involve an interplay between peripheral and central neurophysiological mechanisms that have gone awry. The new Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, somatic symptom disorder overpsychologizes people with chronic pain; it has low sensitivity and specificity, and it contributes to misdiagnosis, as well as unnecessary stigma. Adjustment disorder remains the most appropriate, accurate, and acceptable diagnosis for people who are overly concerned about their pain.

Chronic pain is prevalent and disproportionately impacts adults with a lower quality of life. Although subjective self-reporting is the “gold standard” for pain assessment, tools are needed to objectively monitor and account for inter-individual differences. This study introduced a novel framework to objectively classify pain intensity levels using physiological signals during Quantitative Sensory Testing sessions. Twenty-four participants participated in the study wearing physiological sensors (blood volume pulse (BVP), galvanic skin response (GSR), electromyography (EMG), respiration rate (RR), skin temperature (ST), and pupillometry). This study employed two analysis plans. Plan 1 utilized a grid search methodology with a 10-fold cross-validation framework to optimize time windows (1–5 s) and machine learning hyperparameters for pain classification tasks. The optimal time windows were identified as 3 s for the pressure session, 2 s for the pinprick session, and 1 s for the cuff session. Analysis Plan 2 implemented a leave-one-out design to evaluate the individual contribution of each sensor modality. By systematically excluding one sensor’s features at a time, the performance of these sensor sets was compared to the full model using Wilcoxon signed-rank tests. BVP emerged as a critical sensor, significantly influencing performance in both pinprick and cuff sessions. Conversely, GSR, RR, and pupillometry demonstrated stimulus-specific sensitivity, significantly contributing to the cuff session but with limited influence in other sessions. EMG and ST showed minimal impact across all sessions, suggesting they are non-critical and suitable for reducing sensor redundancy. These findings advance the design of sensor configurations for personalized pain management. Future research will focus on refining sensor integration and addressing stimulus-specific physiological responses.

Background and ObjectivesNeck pain exerts a steep personal and socioeconomic toll, ranking as the fourth leading cause of disability. The principal determinant in treatment decisions is whether pain is neuropathic or nonneuropathic, as this affects treatment at all levels. Yet, no study has sought to classify neck pain in this manner.MethodsOne hundred participants referred to an urban, academic military treatment facility with a primary diagnosis of neck pain were enrolled and followed up for 6 months. Pain was classified as neuropathic, possible neuropathic, or nonneuropathic using painDETECT and as neuropathic, mixed, or nociceptive by s-LANSS (self-completed Leeds Assessment of Neuropathic Symptoms and Signs pain scale) and physician designation. Based on previous studies, the intermediate possible neuropathic pain category was considered to be a mixed condition. The final classification was based on a metric combining all 3 systems, slightly weighted toward physician's judgment, which is considered the reference standard.ResultsFifty percent of participants were classified as having possible neuropathic pain, 43% as having nonneuropathic pain, and 7% with primarily neuropathic pain. Concordance was high between the various classification schemes, ranging from a low of 62% between painDETECT and physician designation for possible neuropathic pain, to 83% concordance between s-LANSS and the 2 other systems for neuropathic pain. Individuals with neuropathic pain reported higher levels of baseline disability, were more likely to have a coexisting psychiatric illness, and underwent surgery more frequently than other pain categories, but were also more likely to report greater reductions in disability after 6 months.ConclusionsAlthough pure neuropathic pain comprised a small percentage of our cohort, 50% of our population consisted of mixed pain conditions containing a possible neuropathic component. There was significant overlap between the various classification schemes.

Background This cross-sectional study analyzed patients with temporomandibular joint disorders (TMD) through the Research Diagnostic Criteria Axis II and compared the outcomes in patient groups separated according to the Okeson Classification. Materials and methods The study included 270 TMD patients (212 female, 58 male) admitted to the Oral and Maxillofacial Surgery clinic at Ankara University. Following the Okeson classification, patients separated into four groups of osteoarthritis, internal derangement, myofascial pain, and local myalgia were evaluated with RDC/TMD Axis II form and also questioned about the usage of antidepressants and smoking habits. SPSS version 20 (IBM, Chicago, IL, USA) was employed for statistical analyses. Results While patients with myofascial pain had the highest rates of depression, somatization, usage of antidepressants, graded chronic pain, patients with internal derangement had the lowest rates of depression, somatization, and graded pain. Rates of smoking did not differ between the patient groups. Conclusions Delineating the features of TMD patients by RDC/TMD Axis II in subgroups according to Okeson classification would improve understanding of the divergent pathogenesis of TMD and lead to optimizing future treatments.

Background: The COVID-19 pandemic has worsened the pain and suffering of chronic pain patients due to stoppage of “elective” interventional pain management and office visits across the United States. The reopening of America and restarting of interventional techniques and elective surgical procedures has started. Unfortunately, with resurgence in some states, restrictions are once again being imposed. In addition, even during the Phase II and III of reopening, chronic pain patients and interventional pain physicians have faced difficulties because of the priority selection of elective surgical procedures. Chronic pain patients require high intensity care, specifically during a pandemic such as COVID-19. Consequently, it has become necessary to provide guidance for triaging interventional pain procedures, or related elective surgery restrictions during a pandemic. Objectives: The aim of these guidelines is to provide education and guidance for physicians, healthcare administrators, the public and patients during the COVID-19 pandemic. Our goal is to restore the opportunity to receive appropriate care for our patients who may benefit from interventional techniques. Methods: The American Society of Interventional Pain Physicians (ASIPP) has created the COVID-19 Task Force in order to provide guidance for triaging interventional pain procedures or related elective surgery restrictions to provide appropriate access to interventional pain management (IPM) procedures in par with other elective surgical procedures. In developing the guidance, trustworthy standards and appropriate disclosures of conflicts of interest were applied with a section of a panel of experts from various regions, specialties, types of practices (private practice, community hospital and academic institutes) and groups. The literature pertaining to all aspects of COVID-19, specifically related to epidemiology, risk factors, complications, morbidity and mortality, and literature related to risk mitigation and stratification was reviewed. The evidence -- informed with the incorporation of the best available research and practice knowledge was utilized, instead of a simplified evidence-based approach. Consequently, these guidelines are considered evidence-informed with the incorporation of the best available research and practice knowledge. Results: The Task Force defined the medical urgency of a case and developed an IPM acuity scale for elective IPM procedures with 3 tiers. These included emergent, urgent, and elective procedures. Examples of emergent and urgent procedures included new onset or exacerbation of complex regional pain syndrome (CRPS), acute trauma or acute exacerbation of degenerative or neurological disease resulting in impaired mobility and inability to perform activities of daily living. Examples include painful rib fractures affecting oxygenation and post-dural puncture headaches limiting the ability to sit upright, stand and walk. In addition, urgent procedures include procedures to treat any severe or debilitating disease that prevents the patient from carrying out activities of daily living. Elective procedures were considered as any condition that is stable and can be safely managed with alternatives. Limitations: COVID-19 continues to be an ongoing pandemic. When these recommendations were developed, different stages of reopening based on geographical regulations were in process. The pandemic continues to be dynamic creating every changing evidence-based guidance. Consequently, we provided evidence-informed guidance. Conclusion: The COVID-19 pandemic has created unprecedented challenges in IPM creating needless suffering for pain patients. Many IPM procedures cannot be indefinitely postponed without adverse consequences. Chronic pain exacerbations are associated with marked functional declines and risks with alternative treatment modalities. They must be treated with the concern that they deserve. Clinicians must assess patients, local healthcare resources, and weigh the risks and benefits of a procedure against the risks of suffering from disabling pain and exposure to the COVID-19 virus. Key words: Coronavirus, COVID-19, interventional pain management, COVID risk factors, elective surgeries, interventional techniques, chronic pain, immunosuppression

To subgroup chronic pain patients using psychometric data and regress the variables most responsible for subgroup discrimination. Cross-sectional, registry-based study. Chronic pain patients assessed at a multidisciplinary pain centre between 2008 and 2015. Data from the Swedish quality registry for pain rehabilitation (SQRP) were retrieved and analysed by principal component analysis, hierarchical clustering analysis, and partial least squares-discriminant analysis. Four subgroups were identified. Group 1 was characterized by low \"psychological strain\", the best relative situation concerning pain characteristics (intensity and spreading), the lowest frequency of fibromyalgia, as well as by a slightly older age. Group 2 was characterized by high \"psychological strain\" and by the most negative situation with respect to pain characteristics (intensity and spreading). Group 3 was characterized by high \"social distress\", the longest pain durations, and a statistically higher frequency of females. The frequency of three neuropathic pain conditions was generally lower in this group. Group 4 was characterized by high psychological strain, low \"social distress\", and high pain intensity. The identification of these four clusters of chronic pain patients could be useful for the development of personalized rehabilitation programs. For example, the identification of a subgroup characterized mainly by high perceived \"social distress\" raises the question of how to best design interventions for such patients. Differentiating between clinically important subgroups and comparing how these subgroups respond to interventions is arguably an important area for further research.