European Journal of Pain

Despite advances in understanding the mechanistic underpinnings of chronic pain (CP) conditions, knowledge on the brain anatomy microstructure associated to CP trajectories is still scarce. We sought to fill this knowledge gap by combining longitudinal self-reported CP assessments with brain imaging in a community dwelling adult population (n = 976). Aiming to provide anatomical insights beyond morphometry (based on T1 brain images), we analyzed the derived relaxometry measures MTsat, R1 and R2* and we could investigate myelin and iron content. Participants were divided in three groups according to persistent, resolved or new CP and were compared to those without CP at timepoint. Participants with persistent CP exhibited lower grey matter (GM) in fronto-temporal cortical regions and reduced myelin-related signal in subcortical and thalamic areas, alongside higher iron-sensitive metrics in the entorhinal cortex. Those who recovered from CP showed reduced cortical GM and myelin encompassing subcortical nuclei, thalamus, frontal, parietal, and temporal regions. New-onset CP participants displayed reduced GM in cortical areas. Overall, we observed reduced GM volume in a widespread network of fronto-temporal cortical areas in participants with current, resolved and new-onset CP. Myelin-related metrics were lower in the subcortical nuclei and thalamus in participants with persistent and -to a greater extent- with resolved CP, whilst persistent CP was associated with higher iron-sensitive metrics in the entorhinal cortex. Hence, CP trajectories appear to leave differential imprints on brain morphometry and tissue microstructure, with each trajectory associated with distinct non-overlapping spatial and temporal patterns in GM, myelin, and iron content.

Chronic pain is highly heterogeneous, with individuals varying substantially in symptoms. pain severity, disability, affective distress, cognitive functioning, and trauma-related symptoms. This study examined whether working memory, post-traumatic stress symptoms (PTSS), trauma exposure, and pain modulation explain distinct or shared dimensions of chronic pain variability. Individuals with chronic pain completed clinical, cognitive, trauma-related, and behavioural pain modulation measures, as well as resting-state functional magnetic resonance imaging. Multivariate regressions were used to determine whether working memory, PTSS, trauma exposure, and pain modulation independently predicted chronic pain outcomes. Principal component analysis was used to identify latent dimensions of chronic pain, and mediation analyses tested whether behavioural pain modulation explained relationships between dlPFC to vlPAG resting-state functional connectivity and clinical pain outcomes. PTSS independently predicted affective outcomes, including depression, state anxiety, and trait anxiety, whereas working memory independently predicted pain severity and pain interference. Trauma exposure was associated with greater PTSS and poorer working memory, but did not independently predict core pain outcomes after accounting for these more proximal factors. Principal component analysis identified partially distinct affective and sensory-disability dimensions, while trauma exposure loaded primarily on a separate component characterized by greater PTSS and poorer working memory. Behavioural pain modulation showed broader relationships across symptom dimensions and was associated with dlPFC to vlPAG connectivity. Exploratory mediation analyses demonstrated that pain modulation mediated relationships between dlPFC to vlPAG connectivity and both pain severity and affective distress. These findings support an integrated model where PTSS and working memory are more proximal predictors of affect and severity respectively, and trauma exposure represents a more distal vulnerability factor that predicts both. Thus, pain modulation represents a shared mechanism linking cortico-brainstem connectivity to chronic pain intensity and affect. These variables need further testing for phenotyping people with chronic pain based on their specific clinical needs.

Background Context Chronic low back pain (cLBP) is the leading global cause of disability, yet the anatomical, psychological, and socioeconomic determinants of cLBP are typically studied in isolation, with limited large-scale integration of imaging data. Purpose To determine the relative contributions of anatomical, demographic, anthropometric, socioeconomic, and psychological factors to diagnosed cLBP and to spinal pathology burden. Study Design Retrospective cross-sectional analysis of a single-center imaging cohort. Patient Sample 1,480 adults undergoing lumbar spine MRI at a single academic center, March 2014-March 2024. Outcome Measures Primary: physician-diagnosed cLBP ([&ge;]2 low back pain diagnoses [&ge;]6 months apart). Secondary: anatomical pathology burden, a composite count of stenosis, degenerative disc disease, facet arthropathy, and spondylolisthesis on lumbar MRI reports. Methods Pathologies were extracted from radiology reports using a large language model (GPT-4), benchmarked against a regex (keyword search) pipeline. Multivariable logistic regression assessed cLBP associations across all five domains; leave-one-domain-out analysis quantified each domain's contribution ({Delta}AIC). Parallel linear regression modeled pathology burden. Results The LLM pipeline achieved F1=0.98 versus 0.92 for regex. cLBP was most strongly associated with depression (OR=2.69, p<0.001) and anxiety (OR=2.31, p<0.001), with smaller contributions from stenosis (OR=1.07, p=0.006) and spondylolisthesis (OR=1.15, p=0.039). Psychological factors were the most impactful domain ({Delta}AIC=120.1), followed by anatomical (37.0), demographic/anthropometric (21.8), and socioeconomic (3.0). Anatomical burden was associated with age, male sex, higher BMI, and Non-Hispanic White race, with no socioeconomic or psychological associations. Conclusions Factors associated with diagnosed cLBP and with structural spinal pathology are largely dissociated: psychological comorbidities dominate cLBP, while anatomical burden reflects demographics.

Background: Chronic pain affects hundreds of millions worldwide and remains a major clinical challenge, despite numerous available treatments. Advances in brain imaging offer a promising path toward identifying neural signatures of chronic pain, potentially enhancing diagnosis and guiding treatment. However, while a core set of brain regions, including the insula, cingulate, and somatosensory cortices, has been repeatedly implicated, findings regarding other regions and connectivity patterns involved remain inconsistent, with limited robust replication. Objective: To address these gaps, the present work characterizes resting-state functional connectivity and gray matter volume differences between chronic pain patients and pain-free controls. Methods: In this secondary analysis of publicly available data, anatomical and resting-state functional MRI were analyzed from 56 patients with chronic knee pain due to osteoarthritis and 20 pain-free controls. Group comparisons used Network-Based Statistic (NBS) and Bayesian multivariate regression models, controlling for demographic covariates. Results: In the pain group, about 75% of parcellated brain regions exhibited increased functional connectivity compared to controls. The 30 highest degree centrality regions in the NBS network were concentrated in regions consistent with prior pain neuroimaging findings. Additionally, chronic pain patients exhibited reduced gray matter volume (-3.98%; SD 1.2%) across 33% of parcellated brain regions, including key regions implicated in pain processing. Conclusions: These findings demonstrate widespread functional and anatomical neural alterations in chronic pain, revealing a global pattern of reorganization extending beyond previously reported network-pair effects. Characterizing such alterations may contribute to ongoing efforts to identify neuroimaging markers of chronic pain, with potential translational relevance.

Background: Although opioids are frequently prescribed for refractory chronic neuropathic pain, few data are available on baseline factors that may identify individuals more likely to respond and inform individually tailored practice. Methods: This was a post hoc, exploratory analysis of individual-level data from a placebo-controlled trial of methadone for chronic neuropathic pain (NCT05235191). Baseline clinical, psychological, psychophysical and radiological variables were tested for association with 30% or more pain reduction in the methadone group. The correlation between expectation of improvement and pain reduction was examined in both groups. Results: Of the 81 participants completing the 8-week follow-up, 28 (70%) on methadone and 14 (34.1%) on placebo achieved 30% or more pain reduction. In the methadone group, responders had higher baseline expectation of improvement (median 100 [80-100] vs. 55 [50-81]; p=0.004), which correlated moderately with percentage pain reduction (rs=0.508; p<0.001). Neither finding was observed in the placebo group (p=0.211 and p=0.161, respectively), although the correlation did not differ significantly between groups (p for interaction=0.728). Other clinical, sociodemographic, psychological and psychophysical variables were not associated with response. In the subsample with peripheral neuropathic pain and structural MRI (n=37), lower left precentral cortex volume was associated with response to methadone (p=0.041), and lower right paracentral volume with response to placebo (p=0.003). Conclusions: Baseline expectation may influence treatment outcomes, supporting its inclusion as a covariate to improve the precision of treatment effect estimates in trials, and its use in clinical practice to help tailor treatment to individual patients. These exploratory findings require confirmation in larger studies.

Background: Clinical decision support (CDS) systems may improve chronic pain management by providing guideline-based recommendations within clinical workflows. However, low clinician use can limit their effectiveness. Understanding the association between CDS use and guideline-recommended care may help distinguish implementation challenges from limitations in CDS functionality. Objective: To estimate the association of OneSheet, a CDS system for chronic pain management, and guideline-recommended care when the system was used during patient encounters. Methods: We conducted a per-protocol secondary data analysis of data from a pragmatic randomized clinical trial conducted from October 2020 to May 2022 across 25 primary care clinics at 2 academic health systems in Indiana and North Carolina. The parent trial enrolled 137 primary care clinicians. This analysis included 145511 eligible chronic pain encounters and 15480 long term opioid therapy (LTOT) encounters that occurred after OneSheet implementation. OneSheet use at a patient encounter was the exposure of interest. Propensity score matching was used to create comparable groups of encounters with and without OneSheet use. Outcomes included documentation of pain-related goals, documentation of pain and function using the Pain, Enjoyment of Life and General Activity (PEG) scale, prescription drug monitoring (PDMP) review, urine drug screening (UDS) orders, and naloxone orders. Results: OneSheet was used in 959 of 145511 chronic pain encounters (0.7%) and 582 of 15480 LTOT encounters (4.0%). In matched analyses, OneSheet use was associated with increased documentation of pain-related goals (relative risk (RR)=11.70 (95% CI 4.25-32.50) and PEG score documentation (RR=9.70 (95% CI 4.14-22.31). Among LTOT encounters, OneSheet use was associated with increased UDS ordering (RR=1.52 (95% CI 1.40-1.65) and PDMP review (RR=1.06 (95% CI 1.03-1.09), but decreased naloxone ordering (RR=0.13 (95% CI, 0.02-0.90). Conclusions: OneSheet use was associated with several guideline-recommended chronic pain management actions, suggesting that they system may support care quality when clinicians use it. However, use was rare, indicating that increasing routine use through better workflow integration may be necessary to achieve population-level improvements in chronic pain care.

Chronic low back pain affects over half a billion people globally and is the leading cause of disability worldwide, yet objective tools for characterizing how individual patients experience pain over time remain lacking. Patients with chronic low back pain exhibit distinct pain trajectory patterns: some experience relatively stable pain while others experience episodic fluctuations with flare-ups. These trajectories have been found to be clinically meaningful but are currently captured only through subjective self-report. Consumer smartwatches offer an opportunity for passive, continuous, objective monitoring of physiological and behavioral signals that may reflect these fluctuations. We evaluated whether temporal features extracted from six months of smartwatch-derived resting heart rate, heart rate variability, and step count data could discriminate between episodic and non-episodic pain phenotypes in 261 chronic low back pain patients from a longitudinal observational cohort. We applied stability-selected elastic-net logistic regression models to temporal features and evaluated model performance using nested cross-validation and SHAP-based feature importance analysis. Summary statistics showed no significant differences between pain groups across any signal modality. Functional principal component analysis revealed high temporal heterogeneity in trajectories of resting heart rate, heart rate variability, and step count. Temporal trajectory models substantially outperformed summary-based approaches, with a models achieving areas under the receiver operating curve ranging from 0.66 to 0.82. Frequency-domain features and local variability measures drove classification performance, and combining heart rate and activity features provided complementary discriminative information, performing better than models trained on any subset of modalities. These findings demonstrate the feasibility of passively collected smartwatch data as objective digital biomarkers for pain phenotyping in chronic low back pain, establishing a methodological approach that may permit personalized pain management through objective monitoring of patient pain and response to intervention.

Background: Fluctuations in pain intensity are intrinsic to non-specific chronic low back pain (nsCLBP). Nevertheless, pain fluctuations have rarely been considered when investigating pathophysiological mechanisms. Therefore, a novel study protocol was developed and implemented to systematically assess the impact of fluctuating pain states on pain-related measures. Methods: The final study cohort consisted of 45 nsCLBP patients and 47 age- and sex-matched healthy controls (HCs). Patients participated in three visits, conducted during different pain states (i.e. clinically relevant pain, low-intensity clinical pain / pain-free, clinically irrelevant pain induced using a Qutenza 8% capsaicin patch). Pain fluctuations were monitored through online assessments every four days and guided the pseudorandomized visit scheduling. HCs participated in a single visit. Each study visit comprised a multimodal battery of pain-related measures. Results: 93.33% of patients completed all three visit types in a pseudorandomized order (chi-squared=1.50, p=0.826). Visit scheduling was possible due to the high self-report adherence (median=93.48%), unrelated to self-report burden (rho=-0.097, p=0.53). Study visits were conducted during different pain states, as indicated by: i) the significantly higher low back pain intensity in the clinically relevant pain visit (mean[SD]: 3.98[0.90]), compared to the low-intensity clinical pain (1.03[0.86]) and clinically irrelevant pain (1.13[0.82]) visits (p-values<0.001), as well as by ii) the successful induction of a moderate-to-high clinically irrelevant pain across assessments. Conclusion: Despite scheduling complexity and pain state transition uncertainty, a pain state-dependent pseudorandomized study design is feasible and could improve the understanding of nsCLBP mechanisms.

Background: Chronic musculoskeletal pain (CMP) is a common and debilitating symptom of Long COVID (LC), which shares several clinical features with Fibromyalgia Syndrome (FMS). Aims: This longitudinal study investigated whether the symptom overlap between LC-CMP and FMS persists over time, whether patterns differ according to pre-COVID CMP history, and the extent to which neuropathic pain features are present. Methods: Individuals with LC completed questionnaires assessing the symptom-based component of the 2010 American College of Rheumatology criteria for FMS and the presence of neuropathic pain features (PainDetect Questionnaire, PDQ) at baseline, 6- and 12-month follow-ups. Participants were grouped according to pre-COVID CMP history. Group differences were analysed using mixed-effects logistic regression. Results: 240 individuals completed the baseline assessment at a mean of 2.61 years after LC onset, including 131 (100 females) with new-onset CMP and 94 (87 females) with pre-existing CMP. The prevalence of participants meeting the symptom-based criteria for FMS remained high across follow-up (67.5-78.6%), with 50.0-61.0% of those with complete follow-up data fulfilling criteria at all timepoints. No significant subgroup differences were observed (OR = 0.43, 95% CI [0.14 1.39], p = 0.160). Across follow-up, 22.2-36.1% of participants reported likely neuropathic pain features, with significantly higher odds in the pre-existing CMP group (OR = 3.17, 95% CI [1.22 8.18], p = 0.017). Conclusions: FMS-like symptoms remain highly prevalent several years after acute COVID-19 and persist over a further 12 months, suggesting that LC-CMP frequently represents a persistent long-term condition with substantial overlap with FMS. These findings support closer integration of LC and chronic pain rehabilitation services and add to the wider literature linking post-infectious processes with FMS-like symptoms.

The spinal dorsal horn is the primary processing site of nociceptive sensory input from the periphery. Excitatory spinal interneurons releasing glutamate can amplify this information before it is sent to the brain, whereas inhibitory neurons releasing GABA and/or glycine can suppress the outflow of nociceptive signals. An imbalance favoring excitation is thought to underlie certain aspects of chronic pain. Although rodent studies have identified spinal mechanisms underlying hyperalgesia and allodynia, little is known about the anatomical changes associated with chronic pain in the human spinal cord, a gap in knowledge we sought to address in this study. Using immunohistochemistry and in situ hybridization on lumbar spinal cord tissue recovered from organ donors, we characterized neuronal size and density across the human dorsal horn and confirmed the presence of the human equivalent of the lateral spinal nucleus in many individuals. Chronic lower limb pain was not associated with changes in neuronal density in the dorsal horn. Likewise, the ratio of excitatory (SLC17A6+) to inhibitory (PAX2+) neurons remained consistent across laminae for age, sex and chronic pain state, providing no evidence for selective loss of inhibitory neurons with chronic pain in humans. We found no differences in the size or density of the postsynaptic markers Homer1 and gephyrin between groups, suggesting glutamatergic and GABAergic postsynaptic sites remain structurally stable. These findings provide a thorough evaluation of cellular anatomy of the human dorsal horn and form a foundation for future studies investigating neuronal changes that may contribute to chronic pain in humans.

While progress has been made in identifying pain biomarkers using neuroimaging, the development of reliable EEG-based biomarkers remains challenging, limited by small sample sizes and the lack of adequate control conditions. We present a comprehensive dataset from 125 pain-free adults, comprising electroencephalogram (EEG) recordings, and behavioural, sociodemographic, and psychological data. Galvanic skin response and electrocardiogram data were also recorded in a subset of participants (n = 76). Participants received two sustained painful stimulations (thermal, chemical) and two sustained aversive non-painful stimulations (auditory, taste), each delivered twice (with and without continuous intensity ratings). Data are provided in Brain Imaging Data Structure format, where all physiological, stimulus-related, and behavioural data are synchronized within the EEG data files for easy access and analysis. Technical validation confirmed data integrity, with spectral and physiological analyses showing responses associated with stimulus intensity and subjective pain/unpleasantness levels. By providing multimodal physiological data across painful and non-painful aversive conditions, this initiative represents a valuable resource for developing or validating biomarkers and exploring the multidimensional nature of pain perception.

Background: Sleep, pain, affect, cognition and energy (SPACE) has been described as a latent symptom-severity construct in chronic overlapping pain conditions. Its population-level structure and associations with chronic pain interference and functional disability remain uncertain. Methods: We conducted a cross-sectional analysis of UK Biobank participants. Prespecified standardised symptom domains were examined using correlation analysis, principal component analysis, exploratory factor analysis and k-means clustering. Associations with chronic pain interference, current work disability, poor self-rated health and longstanding illness or disability were assessed using covariate-adjusted logistic regression. A four-domain score excluding pain tested whether associations extended beyond the pain domain. Secondary analyses examined convergence with actigraphy, biomarkers, polygenic risk scores and brain magnetic resonance imaging phenotypes. Results: Of 501,935 eligible participants, 475,134 had complete domain data. Domains were modestly intercorrelated (r=0.04-0.46). Clustering identified lower- and higher-burden phenotypes comprising 70.5% and 29.5% of participants; current work disability occurred in 1.3% and 10.3%, respectively. Adding the four non-pain domains increased the area under the curve for chronic pain interference from 0.593 to 0.672 and for work disability from 0.748 to 0.850. Inclusion of pain increased the work-disability area under the curve to 0.863. Multimodal measures added smaller increments. Conclusions: A multidimensional symptom profile was identifiable at population scale and was concurrently associated with chronic pain interference and work disability, with non-pain domains contributing information beyond pain burden alone.

Pathophysiological mechanisms underlying the transition from acute to chronic neuropathic pain remain incompletely understood. The somatosensory and insular cortices are key cortical components of the pain matrix. We examined changes in activation of these cortical regions during the transition from acute to chronic neuropathic pain. The right sciatic nerve was ligated in activity reporter TRAP mice using standard procedures. Mechanical allodynia was confirmed after CCI or sham surgery using von Frey monofilaments applied to the hind paws. To label active neurons, 4-hydroxytamoxifen was administered to separate cohorts at 1, 3, and 6 weeks following nerve ligation. Passive tissue clearing of brain sections and confocal imaging was used to assess active neurons. Progressive reduction of ipsilateral hind paw in CCI mice indicated mechanical allodynia development. CCI mice showed robust neuronal activation in the bilateral somatosensory and insular cortices. The somatosensory cortical activation peaked at 3 weeks post-CCI, whereas insular cortical activity increased during the transition from acute to chronic neuropathic pain. These studies revealed that CCI induced progressive mechanical allodynia and distinct temporal patterns of cortical neuronal activation, with transient peak neuronal activity in the somatosensory cortex and sustained, increasing activation in the insular cortex during acute-to-chronic pain transformation.

Purpose: Fibromyalgia involves chronic widespread pain and heightened movement evoked pain (MEP), which can limit access to resistance training's functional and psychological benefits by hindering exercise participation and adherence. This study aimed to determine whether transcutaneous electrical nerve stimulation (TENS) applied during resistance exercise reduces MEP in women with fibromyalgia. Materials and methods: 21 women with fibromyalgia performed 2 sets of 10 leg press repetitions at 60% predicted 1 RM while receiving randomized active TENS (100 Hz) or sham TENS. Pain intensity and unpleasantness (0 to 10 numerical rating scales) were assessed at baseline, immediately post exercise, 15 min post-exercise, end-of-day, and 24h later. Results: Active TENS led to a greater reduction in post-exercise pain than sham, with 90% of participants experiencing at least a 15% decrease in whole body pain 15 minutes post-exercise, compared to none in the sham group. No group differences were observed at the end of the day or 24h after the exercise session. Conclusion: These results suggest that a single session of high frequency TENS during resistance exercise can produce short term reductions in MEP in women with fibromyalgia. While effects did not persist at 24h, these short-term effects may help mitigate acute exercise related pain and support early training adherence.

Pain is associated with dynamic brain reorganization. Electroencephalographic microstates can characterize transient large-scale brain states, yet findings across pain studies are inconsistent. Two features may contribute: conditions have been studied in isolation, and analytical pipelines vary widely. We applied a harmonized analysis pipeline across three pain conditions: capsaicininduced pain, assessed within participants against a pain-free baseline, and non-chronic and chronic back pain, each compared with matched controls. Using a five-minute resting-state electroencephalographic recordings we examined microstate topography, temporal expression and transition probabilities, and directly compared pain related differences across pain states. We identified five microstates (A-E), corresponding to auditory, visual, salience, and attentional networks. Capsaicin pain showed increased expression of microstate C and reduced expression of microstates A, D and E. Transitions were redistributed towards microstate C, indicating a shift toward salience-related processing at the expense of sensory and attentional dynamics. In clinical back pain, effects were smaller and diverged by pain type: non-chronic back pain showed lower microstate C occurrence, opposite in direction to the capsaicin effect, whereas chronic back pain showed lower microstate D global explained variance, suggesting salience and attentional differences in clinical pain. Direct comparisons showed weaker pain-related increases in microstate C expression in both clinical back pain groups than capsaicin pain, with additional differences involving microstates A, D and E. These findings argue against a unitary EEG microstate signature of pain and instead reveal pain-type-specific patterns of large-scale brain dynamics, with microstate C providing the clearest distinction between experimental and clinical pain.

Background Spinal manipulation therapy (SMT) is widely used for low back pain (LBP), yet comparative effectiveness findings across trials remain inconsistent. One potential explanation is incomplete separation of treatment-specific effects from natural recovery and placebo response, which may differ between acute and chronic presentations. Methods We conducted a Bayesian hierarchical analysis of 120 randomized controlled trials (298 arms; 19,059 patients) evaluating SMT, exercise, medical management, physical modalities, self-care, and control conditions. Natural history (NH) trajectories were derived from independent observational cohorts and incorporated as external model components. Treatment effects were estimated as deviations from NH, and sham-corrected effects as deviations from control conditions. Results In acute LBP, NH trajectories predicted substantial improvement by 26 weeks. Estimated treatment effects relative to NH were negative across all categories, and sham-corrected effects were near zero, with credible intervals overlapping zero. In chronic LBP, NH trajectories predicted more gradual improvement. Control conditions exceeded NH, consistent with a substantial placebo response. Exercise and SMT demonstrated positive sham-corrected effects with credible intervals excluding zero; however, estimated magnitudes were modest and did not consistently exceed commonly cited thresholds for clinical importance. Higher study quality was associated with smaller estimated effects in chronic trials. Conclusions Modeling natural history as a structural component of treatment response alters estimates of comparative effectiveness in LBP. Improvements observed in acute LBP appear largely consistent with underlying recovery processes, whereas in chronic LBP, contextual and placebo-related effects contribute substantially to observed outcomes. Explicit separation of these components may help reconcile inconsistencies in the literature and inform interpretation of treatment effects.

Background Chronic postsurgical pain (CPSP) affects between 7-23% and 13-44% of patients after hip and knee arthroplasty, respectively. Standardised methods of pain assessment provide superior evaluation of pain, including the Oxford Joint Score Pain Subscale (OJS-PS). We aim to estimate the proportion of patients with a phenotype consistent with CPSP through a k-medoids clustering technique and identify a threshold on the OJS-PS to highlight such patients at a population level. Methods In this cross-sectional study Patient Reported Outcomes Measures data 6-months after hip and knee arthroplasty from 2017 to 2025 were examined. An adapted k-medoid clustering technique utilising subsampling, batch assignment and probabilistic consensus allocated clusters. A receiver operator characteristic analysis identified a threshold on the OJS-PS noting the lowest scoring cluster. Our categorisation was compared to self-reported severe or moderate pain; sensitivity, specificity and accuracy of this categorisation were calculated. Results We analysed 109,542 hip and 113,799 knee arthroplasty patients; three clusters were used in each analysis. After hip arthroplasty: 14.4% of patients were assigned to the cluster with the lowest median OJS-PS of 11 [IQR 8 - 13]. A threshold of 15.5 classified patients as severe or moderate pain with 60.6% sensitivity, 91.0% specificity and 85.7% accuracy. Similarly, after knee arthroplasty, 25.3% were assigned to the cluster with the lowest median OJS-PS of 14 [IQR 11 - 16]. A threshold of 18.5 on the OJS-PS had an 85.4% sensitivity, 88.4% specificity and 87.8% accuracy for classifying patients with self-reported severe or moderate pain. Conclusions This robust and scalable clustering technique on ordinal clinical data estimates the proportion of patients reporting a phenotype consistent with CPSP. On a population level the thresholds identified on the OJS-PS could aid screening for potential CPSP patients 6 months after hip and knee arthroplasties.

The Acute to Chronic Pain Signatures (A2CPS) project is a large, multisite, longitudinal observational study designed to identify biomarkers that predict the transition from acute to chronic pain following surgery in more than 2200 patients. Two participant cohorts were recruited before undergoing either knee arthroplasty or thoracic surgery. A unique feature of this study is its comprehensive evaluation of pain, including evoked and recall pain measures collected at baseline, 6-weeks, and 3-months following surgery, in addition to the primary pain outcome assessed remotely at 6 months. This paper describes the acquisition, quality control procedures, and available pain and pain sensitivity variables included in the A2CPS study. Self-report pain assessments include surgical site (i.e., index) pain intensity, pain interference and quality, spatial distribution of pain using body maps, and pain-related dysfunction specific to each cohort. Quantitative sensory testing yielded evoked pain sensitivity data including pressure pain thresholds, temporal summation of pain, dynamic mechanical allodynia, and conditioned pain modulation at both index and common sites across cohorts. Movement-evoked pain was assessed for each cohort using relevant functional tasks (knee: 10m walk and five-time-sit-to-stand tests, thoracic: deep breathing and coughing). Using baseline data from release v2.1.0, comprising approximately 1,400 participants, we evaluated interrelationships among pain variables. Overall, the A2CPS pain and pain sensitivity data provide a robust, comprehensive set of variables that supports the study goal of uncovering predictive biomarkers of post-operative chronic pain and enables broader exploration relative to other study outcomes, including imaging, psychosocial, and omics data.

Objectives To analyse the long-term effects of a cruciate ligament (CL) injury on health and socioeconomic outcomes. Methods We used a comprehensive national injury insurance database to identify CL injuries occurring in New Zealand between 2009 and 2022, and employed a doubly robust staggered difference-in-differences research design to identify the effects of these injuries on outcomes up to 10 years after injury. The outcomes of interest were healthcare use (hospitalisations, emergency department visits, medications, knee replacement surgery for osteoarthritis), associated healthcare costs, and labour market outcomes (employment rates, income, and government benefit payments). Results We identified 61 344 CL injuries for inclusion in the analysis. Over 10-year follow-up, a CL injury resulted in increased healthcare use (0.6 more hospitalizations [95%CI 0.4 to 0.7], 1.7 more days spent in hospital [95%CI 1.3 to 2.1], 0.4 more emergency department visits [95%CI 0.3 to 0.6], 2.5 more outpatient visits [95%CI 1.8 to 3.2], and 4.7 more medications dispensed [95%CI -1.8 to 11.2]) and public healthcare costs ($7 537; 95%CI 5 888 to 9 186), reduced income (-$6 060; 95%CI -11 644 to -475), and increased benefit payments ($1 152; 95%CI 542 to 1 761). Conclusion CL injuries have long-term impacts on healthcare use and socioeconomic outcomes. Strategies to reduce the incidence of CL injuries have the potential to realise large health and economic benefits.

Placebo analgesia varies substantially across individuals, yet the sources of this heterogeneity remain incompletely understood. Pain-reporting variability may represent an underrecognized predictor of placebo responsiveness. This study examined whether variability and reliability of pain reporting predict placebo analgesia in an experimental pain setting. Eight hundred and three participants (401 individuals with temporomandibular disorder and 400 healthy controls) completed a standardized thermal pain paradigm involving calibration, placebo conditioning, and testing phases. We obtained repeated heat temperatures (four) during thermal calibration and pain ratings during conditioning test (24 trials). We used these measurements to quantify within-person pain-reporting variability using standard deviation (SD) and coefficient of variation (CoV), and reliability using intraclass correlation coefficients (ICC). Placebo analgesia was calculated as the difference in pain ratings between control and placebo cue trials during testing. Regression models examined associations between reporter characteristics and placebo analgesia controlling for age, sex, race and experimenters. Variability of thermal pain responses during calibration did not predict placebo analgesia. Greater pain-reporting variability during conditioning was associated with reduced placebo analgesia (higher SD and CoV), and this effect was mediated by slower acquisition of the cue pain contingency. Conditioning-phase reliability was not associated with placebo analgesia, whereas three clusters of learning profiles predicted placebo effects. Thus, individual differences in pain-reporting variability during conditioning, rather than baseline sensory variability, contribute to heterogeneity in placebo analgesia. These findings suggest that variability during acquisition processing matters more than general sensory variability influencing the magnitude of placebo effects.