A prognostic risk score for development and spread of chronic pain

Current state of psychological therapies for children and adults with chronic pain: Where next?

Pain is influenced by biological, psychological and social factors. Whilst analgesics are often prescribed for chronic pain, they provide little benefit for most patients. Psychological therapies manage pain and disability in children and adults with chronic pain. Evidence for cognitive behavioural therapies is the most robust in the field, although benefits are modest. Technological innovation has led to Internet-delivered therapies, but innovation in research often lags behind technological developments due to funding and regulation. Despite the promising outlook, critical gaps in our knowledge of how to manage pain need addressing for both adults and children and their parents. Here we summarise the evidence base of psychological therapies using Cochrane reviews, gaps, and the role of preventing chronic pain onset.

Prevalence of Depression and Anxiety Among Adults With Chronic Pain: A Systematic Review and Meta-Analysis

Importance

Depression and anxiety are common among adults with chronic pain, but their prevalence is unclear.

Objectives

To evaluate the prevalence of depression and anxiety among adults with chronic pain and identify factors that moderate prevalence.

Data Sources

A literature search was conducted of MEDLINE, Embase, PsycINFO, and Cochrane Library from January 2013 to October 2023.

Study Selection

Studies reporting the prevalence of depression or anxiety using a validated assessment tool among adults with chronic pain (excluding chronic headache disorders).

Data Extraction and Synthesis

A total of 31 159 initial records were identified, and 5177 full texts were screened. Data were extracted per the Preferred Reporting Items for Systematic Reviews and Meta-analyses guideline using Covidence. Two independent reviewers completed abstract screening, full-text review, and data extraction and rated risk of bias. Random-effects meta-analyses were applied to pool prevalence, assess moderation, and compare prevalence of depression or anxiety among samples with chronic pain vs control samples.

Main Outcomes and Measures

Prevalence of depression and anxiety based on clinically significant symptoms or diagnosis. The moderators of prevalence identified were pain condition, recruitment setting, continent, age, percentage female, and pain duration.

Results

The search identified 376 studies from 50 countries comprising 347 468 individuals (mean [SD] age, 51.3 [9.5] years; 70.0% female) with chronic pain. Among adults with chronic pain, clinical symptoms of depression were present in 39.3% (95% CI, 37.3%-41.1%; I2 = 98.9%), and clinical symptoms of anxiety were present in 40.2% (95% CI, 38.0%-42.4%; I2 = 99.0%). Prevalence differed by pain condition (highest among samples of people with fibromyalgia [depression, 54.0% (95% CI, 48.5%-59.4%); anxiety, 55.5% (95% CI, 50.4%-60.4%)]; lowest among samples of people with arthritis conditions [eg, osteoarthritis: depression, 29.1% (95% CI, 20.3%-39.7%); anxiety, 17.5% (95% CI, 6.6%-38.8%)]) and was highest among younger people (depression, β = -0.02 [95% CI, -0.03 to -0.01]; anxiety, β = -0.02 [95% CI, -0.03 to -0.01]) and women (depression, β = 0.69 [95% CI, 0.31-1.08]; anxiety, β = 0.90 [95% CI, 0.48-1.33]). With regard to diagnoses, 36.7% (95% CI, 29.0%-45.1%) had a major depressive disorder, and 16.7% (95% CI, 11.8%-23.2%) had generalized anxiety disorder. Women, younger people, and people with nociplastic pain (ie, pain arising from altered nociception without tissue damage) were most likely to have depression and anxiety.

Conclusions and Relevance

In this systematic review and meta-analysis of depression and anxiety among individuals with chronic pain, approximately 40% of adults had clinically significant depression and anxiety. Women, younger people, and people with nociplastic pain were most likely to have depression and anxiety. The co-occurrence of chronic pain with depression and anxiety is a significant public health concern necessitating routine screening in clinical settings, equitable access to specialty care, and innovative treatment development.

Genetic causal effects of multi-site chronic pain on post-traumatic stress disorder: Evidence from a two-sample, two-step Mendelian randomization study

BACKGROUND

Existing evidence supports a correlation between multi-site chronic pain and post-traumatic stress disorder (PTSD), but it is yet to be determined if this correlation is causal and in what direction the causation works.

METHODS

Applying two-sample Mendelian randomization (MR) analysis to data from available genome-wide association studies in populations of European ancestry, we estimated the causal association between multi-site chronic pain and no pain versus PTSD. Moreover, we used multivariable and mediation MR analysis to assess the mediating effects of 13 lifestyle factors or diseases on the causal relationship between multi-site chronic pain and PTSD. The MR analyses were mainly conducted with the inverse variance weighted (IVW) method, followed by various sensitivity and validation analyses.

RESULTS

Multi-site chronic pain dramatically increases the risk of developing PTSD (odds ratio [OR]IVW = 2.39, 95 % confidence interval [CI] = 1.72-3.31, p = 2.10 × 10-7), and no pain significantly reduces the risk of developing PTSD (ORIVW = 0.12, 95 % CI = 0.05-0.30, p = 3.14 × 10-6). Multivariable MR found that 13 potential confounding factors do not influence the causal effect of multi-site chronic pain on PTSD. Moreover, body mass index (BMI) (6.98 %), educational attainment (8.79 %), major depressive disorder (MDD) (36.98 %) and insomnia (27.25 %) mediate the causal connection between multi-site chronic pain and PTSD.

CONCLUSION

Overall, individuals with multi-site chronic pain may be at a higher risk of developing PTSD, and this risk is partially influenced by the pathways involving BMI, educational attainment, MDD, and insomnia. These factors offer potential targets for therapeutic interventions.

A Multidimensional Regression Model for Predicting Recurrence in Chronic Low Back Pain

BACKGROUND

Recurrence is common in chronic low back pain (CLBP). However, predicting the recurrence risk remains a challenge. The aim is to develop and validate a machine learning tool to predict the recurrence risk in patients with CLBP by using multidimensional medical information.

METHODS

This prospective cohort study consecutively enrolled 341 patients with CLBP from two hospitals between 1 January 2021 and 31 December 2021. Patients from both centres were used for model development and internal validation, employing multivariate logistic regression (MRL) along with three additional machine learning algorithms. The multidimensional model (MDM) was used to predict recurrence in the next 2 years and was compared with the widely used prognostic tool, the STarT BACK Tool (SBT). The models' performance in detecting recurrence was evaluated using several metrics, including the area under the receiver operating characteristic curve (AUC), decision curve analysis, accuracy, sensitivity and specificity.

RESULTS

A total of 131 patients (38.42%) experienced recurrence. In the MRL model, factors linked to recurrence odds included progressive lower limb weakness, anxiety, mechanical pressure test, number of previous episodes, Oswestry disability index and multifidus proton density fat fraction. For recurrence prediction, the MRL-MDM achieved an AUC of 0.813 (95% CI, 0.765-0.862), sensitivity of 85.2% and specificity of 70.2% in internal validation. In comparison, the SBT for recurrence had an AUC of 0.555 (95% CI, 0.518-0.592), sensitivity of 93.3% and specificity of 17.6%.

CONCLUSION

The MDM may predict recurrence in patients with CLBP over a 2-year period, surpassing the performance of SBT.

SIGNIFICANCE STATEMENT

This study found that the STarT BACK tool is suboptimal in predicting the 2-year recurrence of chronic low back pain (CLBP). Our proposed multidimensional machine learning model aids clinicians in identifying patients at high risk for future recurrence of CLBP and in implementing appropriate preventive measures. Given the considerable healthcare resource utilisation associated with the frequent recurrence of CLBP, our novel model provides significant assistance in addressing this issue, demonstrating substantial clinical relevance.

The number of central nervous system-driven symptoms predicts subsequent chronic primary pain: evidence from UK Biobank

BACKGROUND

Chronic primary pain describes conditions where pain is the principal problem rather than a consequence of another disease. Primary pain is thought to be primarily owing to nociplastic pain (i.e. pain as a result of altered nociception despite the absence of tissue damage). Primary pain is often accompanied by other bothersome central nervous system (CNS)-driven symptoms, including disturbed sleep, mood, and cognition; however, it is unclear whether these symptoms precede onset of primary pain.

METHODS

In a prospective cohort study of the UK Biobank, we examined adults with no self-reported recent or chronic pain at baseline. Using linked primary care record data, we investigated the association between the number of CNS-driven symptoms and subsequent incidence of primary pain conditions. Multivariable regression analyses adjusted for sociodemographic and lifestyle factors.

RESULTS

Of 502 369 participants, 70 630 (14.0%) met the inclusion criteria, with a mean (range) age of 56.7 (40-70) yr, 51% being female. After 7.4 (range 0.5-11.02) yr, 12.2% developed a primary pain condition. We observed a positive relationship between the number of CNS-driven symptoms at baseline and risk of future primary pain (HR 1.43, 95% CI 1.34-1.52, P<0.001). Participants with more CNS-driven symptoms at baseline were also more likely to have chronic and more severe nociplastic pain, but not non-nociplastic pain at follow-up.

CONCLUSIONS

In adults with no current self-reported pain, those with a greater number of CNS-driven symptoms at baseline were more likely to develop a primary pain condition. This suggests a potential opportunity for early intervention in mitigating the burden of primary pain.

Refining chronic pain phenotypes: A comparative analysis of sociodemographic and disease-related determinants using electronic health records

The use of electronic health records (EHR) for chronic pain phenotyping has gained significant attention in recent years, with various algorithms being developed to enhance accuracy. Structured data fields (e.g., pain intensity, treatment modalities, diagnosis codes, and interventions) offer standardized templates for capturing specific chronic pain phenotypes. This study aims to determine which chronic pain case definitions derived from structured data elements achieve the best accuracy, and how these validation metrics vary by sociodemographic and disease-related factors. We used EHR data from 802 randomly selected adults with autoimmune rheumatic diseases seen at a large academic center in 2019. We extracted structured data elements to derive multiple phenotyping algorithms. We confirmed chronic pain case definitions via manual chart review of clinical notes, and assessed the performance of derived algorithms, e.g., sensitivity/recall, specificity, positive predictive value (PPV). The highest sensitivity (67%) was observed when using ICD codes alone, while specificity peaked at 96% with a quadrimodal algorithm combining pain scores, ICD codes, prescriptions, and interventions. Specificity was generally higher in males and younger patients, particularly those aged 18-40 years, and highest among Asian/Pacific Islander and privately insured patients. PPV was highest among patients who were female, younger, or privately insured. PPV and sensitivity were lowest among males, Asian/Pacific Islander, and older patients. Variability of phenotyping results underscores the importance of refining chronic pain phenotyping algorithms within EHRs to enhance their accuracy and applicability. While our current algorithms provide valuable insights, enhancement is needed to ensure more reliable chronic pain identification across diverse patient populations. PERSPECTIVE: This study evaluates chronic pain phenotyping algorithms using electronic health records, highlighting variability in performance across sociodemographic and disease-related factors.

Prediction of Central Post-Stroke Pain by Quantitative Sensory Testing

OBJECTIVE

Among patients with acute stroke, we aimed to identify those who will later develop central post-stroke pain (CPSP) versus those who will not (non-pain sensory stroke [NPSS]) by assessing potential differences in somatosensory profile patterns and evaluating their potential as predictors of CPSP.

METHODS

In a prospective longitudinal study on 75 acute stroke patients with somatosensory symptoms, we performed quantitative somatosensory testing (QST) in the acute/subacute phase (within 10 days) and on follow-up visits for 12 months. Based on previous QST studies, we hypothesized that QST values of cold detection threshold (CDT) and dynamic mechanical allodynia (DMA) would differ between CPSP and NPSS patients before the onset of pain. Mann-Whitney U-tests and mixed analysis of variances with Bonferroni corrections were performed to compare z-normalized QST scores between both groups.

RESULTS

In total, 26 patients (34.7%) developed CPSP. In the acute phase, CPSP patients showed contralesional cold hypoesthesia compared to NPSS patients (p = 0.04), but no DMA differences. Additional exploratory analysis showed NPSS patients exhibit cold hyperalgesia on the contralesional side compared to the ipsilesional side, not seen in CPSP patients (p = 0.011). A gradient-boosting approach to predicting CPSP from QST patterns before pain onset had an overall accuracy of 84.6%, with a recall and precision of 75%. Notably, both in the acute and the chronic phase, approximately 80% of CPSP and NPSS patients showed bilateral QST abnormalities.

INTERPRETATION

Cold perception differences between CPSP and NPSS patients appear early post stroke before pain onset. Prediction of CPSP through QST patterns seems feasible. ANN NEUROL 2025;97:507-520.

Associations between endogenous sex hormones and multisite chronic musculoskeletal pain

BACKGROUND

Sex-differences in pain perception have been documented; however, the role of sex hormones in chronic musculoskeletal pain (CMP) remains unclear. Therefore, this study investigated whether sex hormones and sex hormone-binding globulin (SHBG) are associated with CMP.

METHODS

We utilised data from the UK Biobank (n=357 424; females: 51.6%; white: 95.2%). Serum concentrations of oestradiol (E2), testosterone (T), and SHBG were measured at baseline. Chronic pain (≥3 months) in the neck/shoulder, back, hip, knee, or 'all over the body' was assessed at baseline and three follow-ups. Mixed-effects multinomial/logistic regression models were used.

RESULTS

In multivariable analyses, greater concentrations of T and T/SHBG were associated with a lower number of CMP sites in both males (T: relative risk ratio=0.81 per standard deviation, 95% confidence interval [0.77-0.86] and T/SHBG: 0.85 [0.80-0.92]) and females (T: 0.85 [0.81-0.89] and T/SHBG: 0.93 [0.89-0.97] [all P-values for trend ≤0.001]). Greater T concentrations and T/SHBG were also associated with lower odds of CMP across all sites, while higher concentrations of SHBG were associated with lower odds of neck/shoulder CMP in both sexes. There was no association between concentrations of E2, SHBG, or E2/SHBG and number of CMP or site-specific CMP in either sex.

CONCLUSION

In both sexes, greater T concentrations and T/SHBG were associated with lower number of CMP sites and site-specific CMP, while greater concentrations of SHBG were linked to lower odds of neck/shoulder CMP. These findings suggest a potential involvement of sex steroids in the pathogenesis of CMP and underscore the need for further investigation into their potential in chronic pain management strategies.

Does birth weight or preterm birth predict worse pain prognosis in adulthood? A Northern Finland Birth Cohort study followed up to 46 years of age

Although pain is a highly common symptom, only a subset of individuals develops chronic and disabling conditions. Delving into the predictors for poor musculoskeletal pain (MSK) outcomes in adulthood may help identify those needing early prevention and intervention. This study aimed to evaluate whether birth weight or preterm birth predicts worse prognosis of MSK pain in adulthood. Participants in the Northern Finland Birth Cohort 1966 were followed from birth to 46 years of age. Associations of birth weight (measured using corrections to gestational age) and preterm birth (<37 completed weeks) with high-risk classification for worse pain using three prognostic tools: the Örebro Musculoskeletal Pain Screening Questionnaire-Short Form (ÖMPSQ-SF), STartT Back Tool (SBT), and Risk of Pain Spreading (ROPS) assessed at 46 years among people reporting MSK pain (n=3200-4525). Log-binomial regression models for dummy outcomes (ÖMPSQ-SF and SBT) and generalized linear regression models for continuous outcomes (ROPS) were employed. Birth weight did not predict high-risk classification by any tool. Compared to full-term participants, those born preterm had higher risk of being classified into the high-risk group only according to ÖMPSQ-SF (relative risk 1.61, 95% confidence interval 1.00-2.59) and SBT (1.61, 1.14-2.28). Adjustments did not change these results. Preterm birth appeared to predict allocation to the group with poorer prognosis of MSK outcomes as measured by ÖMPSQ-SF and SBT, but not by ROPS. This highlights the need for further research into the role of preterm birth in the development or accumulation of adverse pain-related thoughts and experiences in mid-life. PERSPECTIVE: Preterm birth tended to predict allocation to the high-risk group for worse pain prognosis in adulthood. Similar was not observed concerning birth weight. Further research is warranted to validate the results and delve into explanatory pathways.

Correlates of chronic pain onset and recovery in the CoLaus cohort

BACKGROUND

Only few previous cohort studies examined simultaneously predictors of chronic pain (CP) onset and recovery. Furthermore, these studies used various sociodemographic and pain-related characteristics, without standardized measures of sleep and depression. The present study aimed at expanding and strengthening these findings in a large Swiss population.

METHODS

We analysed data from a longitudinal cohort (n = 4602) collected at two time points separated by 5 years in Lausanne, Switzerland. We studied through two independent multivariable logistic regression models, the predictors of CP onset and recovery, including socio-demographic data as well as standardized measures of sleep and mood.

RESULTS

Chronic pain was reported by 43.1% and 44.4% of participants, with 11.6% at the second follow-up reporting moderate or intense pain. Neuropathic pain, regardless of intensity, had a more negative impact on quality of life. An inferential model (n = 1331) identified the male sex as predictive for recovering from CP. Older age, being overweight or obese (compared to normal weight), higher depression scores and pain medication intake were predictive for sustained pain at the second follow-up. A second model (n = 1886) identified being overweight or obese (compared to normal weight), low quality of sleep and being a former smoker (compared to a non-smoker) as predictive for developing CP, while the male sex was lowering the risk.

CONCLUSIONS

While sex and weight are associated with both recovery and new CP onset, separate variables also need to be considered in these processes, underlining specific factors to be addressed, depending on the context, whether preventive or therapeutic.

SIGNIFICANCE STATEMENT

Multivariable models in a Swiss cohort (N = 4602) associate male sex, not taking pain medication, normal weight, lower depression scores and younger age with recovery from chronic pain, while females, obese or overweight, having worse sleep and former smokers are associated with onset of new chronic pain. These common and separate factors need to be considered in treatment and prevention efforts.

Co-occurrence of mental distress and insomnia associates with more severe musculoskeletal pain - Northern Finland Birth Cohort 1966 study

OBJECTIVE

This cross-sectional study demonstrates the differences in the dimensions of musculoskeletal (MSK) pain between participants with mental distress and/or insomnia among general population with MSK pain within the past 12 months.

METHODS

Participants of Northern Finland Birth Cohort 1966 (NFBC1966) were studied (n = 4316). They were divided into groups based on their mental distress and insomnia status (co-occurring mental distress and insomnia [CMI], isolated mental distress [M] and insomnia [I], and absence of both [AMI]). The AMI group was used as a reference for the main analyses. The dimensions of MSK pain included frequency, bothersomeness (Numerical Rating Scale [NRS] 0-10), intensity of pain (NRS), and number of pain sites (1-8). Multinomial and general linear regression analyses were used to study the associations, and adjustments were made for sex, education, number of somatic diseases, and physical activity.

RESULTS

The CMI group was associated with more severe pain in every dimension when contrasted to all other groups (daily pain adjusted OR 5.08, 95 % CI 3.43-7.51; bothersomeness adjusted β 1.7, 95 % CI 1.5-2.0; intensity adjusted β 1.4, 95 % CI 1.2-1.7; number of pain sites adjusted β 1.2, 95 % CI 1.0-1.4). Compared to AMI, I and M groups also had relationships with all pain dimensions, but with lower magnitude compared to the CMI group.

CONCLUSIONS

The results suggest that insomnia and mental distress co-exist with more severe MSK pain, and when co-occurring, MSK pain severity tends to increase. Therefore, contemplating insomnia and mental distress are important to consider when comprehensively evaluating MSK pain symptoms.

Antenatal socioeconomic status of childhood family and the risk of pain spreading (ROPS) in early and mid-adulthood - a descriptive study from the northern Finland birth cohort 1966

OBJECTIVE

The Risk of Pain Spreading (ROPS) is a six-item tool capturing key data-driven prognostic factors for chronic pain and its spreading. Higher values on the ROPS indicate a higher risk. Early factors potentially associated with the ROPS are unknown. We aimed to examine the associations between antenatal socioeconomic status of childhood family (antenatal SES) and ROPS at ages 31 and 46 years.

METHODS

The study was based on the Northern Finland Birth Cohort 1966 and previously formulated latent clusters of antenatal family SES: Highest status (the reference), Small, Larger, Average wealth, and Rural families. The ROPS ranged from zero (the reference) to two or more points out of six. A multinomial regression model was used to identify antenatal SES clusters associated with ROPS.

RESULTS

At 31 years (n = 8252), only the Larger families cluster was associated with having accumulated points (two or more) (Odds ratio [OR]: 1.46, 95 % Confidence Interval [CI]: 1.14-1.87) on the ROPS compared to the Highest status families cluster. Corresponding finding was observed at 46 years (n = 6245), but the Small families and Average wealth families clusters were also associated with this outcome. The association of Larger families cluster was, however, the strongest (OR 1.48, 95 % CI 1.16-1.89).

CONCLUSIONS

Offspring born into families with ≥5 members are likely to accumulate higher sums of key data-driven prognostic factors for worse pain across the life course until middle age. In future, associations between antenatal SES and pain would be important to be examined in a light of the ROPS.

Education, gender, and frequent pain among middle-aged and older adults in the United States, England, China, and India

ABSTRACT

Using cross-sectional data from the United States, England, China, and India, we examined the relationship between education and frequent pain, alongside the modification role of gender in this relationship. We further examined patterns of 3 pain dimensions among participants who reported frequent pain, including pain severity, interference with daily activities, and medication use (these pain dimension questions were not administered in all countries). Our analytical sample included 92,204 participants aged 50 years and above. We found a high prevalence of frequent pain across the 4 countries ranging from 28% to 41%. Probit models showed that higher education was associated with lower risk of pain (United States: -0.26, 95% CI: -0.33, -0.19; England: -0.32, 95% CI: -0.39, -0.25; China: -0.33, 95% CI -0.41, -0.26; India: -0.18, 95% CI -0.21, -0.15). Notably, in China and India, the negative association between higher education and frequent pain was less pronounced among women compared with men, which was not observed in the United States or England. Further analysis showed that individuals with higher education experiencing frequent pain reported less severity, fewer daily activity interferences, and less medication use compared with those with lower education. In the United States, these associations were stronger among women. Our findings highlight the prevalent pain among middle-aged and older adults in these 4 countries and emphasize the potentially protective role of higher education on frequent pain, with nuanced gender differences across different settings. This underscores the need for tailored strategies considering educational and gender differences to improve pain management and awareness.

Chronic pain is specifically associated with updating working memory: a longitudinal twin study

ABSTRACT

Worse executive function (EF) is associated with chronic pain and could mechanistically contribute to pain chronification. It is unclear whether there is overall impairment in EFs or whether there are impairments in specific cognitive domains. Furthermore, the possible genetic risk underlying these associations has not been tested. Participants were from the Colorado Longitudinal Twin study; 786 same-sex twins completed a battery of EF tasks at ages 23 and/or 28 and 634 of these twins self-reported chronic pain at mean age = 28.1; prevalence = 27.76% using the Brief Pain History Questionnaire. The EF tasks were used to define a Common EF factor and 2 factors specific to updating working memory and shifting mental set. We estimated the phenotypic and genetic associations of stable EF variance across ages 23 and 28, as well as EF variance unique to age 28, with pain. With respect to stable EF variance, pain phenotypically correlated with the Updating-specific factor ( r = -0.21, P = 0.008) but did not significantly correlate with the Common EF factor ( r = -0.06, P = 0.350) nor with the Shifting-specific factor ( r = -0.03, P = 0.709). There were no significant phenotypic correlations between pain and EF variance unique to age 28. A twin model indicated that pain and Updating-specific variance share genetic risk ( r A = -0.46, P = 0.005) but not environmental risk ( r E = 0.05, P = 0.844). Updating working memory shares a phenotypic and genetic relationship with pain in young adults. Impairments in gating or monitoring pain signals may play a mechanistic role in pain development.

A multisite validation of brain white matter pathways of resilience to chronic back pain

Chronic back pain (CBP) is a global health concern with significant societal and economic burden. While various predictors of back pain chronicity have been proposed, including demographic and psychosocial factors, neuroimaging studies have pointed to brain characteristics as predictors of CBP. However, large-scale, multisite validation of these predictors is currently lacking. In two independent longitudinal studies, we examined white matter diffusion imaging data and pain characteristics in patients with subacute back pain (SBP) over 6- and 12-month periods. Diffusion data from individuals with CBP and healthy controls (HC) were analyzed for comparison. Whole-brain tract-based spatial statistics analyses revealed that a cluster in the right superior longitudinal fasciculus (SLF) tract had larger fractional anisotropy (FA) values in patients who recovered (SBPr) compared to those with persistent pain (SBPp), and predicted changes in pain severity. The SLF FA values accurately classified patients at baseline and follow-up in a third publicly available dataset (Area under the Receiver Operating Curve ~0.70). Notably, patients who recovered had FA values larger than those of HC suggesting a potential role of SLF integrity in resilience to CBP. Structural connectivity-based models also classified SBPp and SBPr patients from the three data sets (validation accuracy 67%). Our results validate the right SLF as a robust predictor of CBP development, with potential for clinical translation. Cognitive and behavioral processes dependent on the right SLF, such as proprioception and visuospatial attention, should be analyzed in subacute stages as they could prove important for back pain chronicity.

Pain can't be carved at the joints: defining function-based pain profiles and their relevance to chronic disease management in healthcare delivery design

BACKGROUND

Pain is a complex problem that is triaged, diagnosed, treated, and billed based on which body part is painful, almost without exception. While the "body part framework" guides the organization and treatment of individual patients' pain conditions, it remains unclear how to best conceptualize, study, and treat pain conditions at the population level. Here, we investigate (1) how the body part framework agrees with population-level, biologically derived pain profiles; (2) how do data-derived pain profiles interface with other symptom domains from a whole-body perspective; and (3) whether biologically derived pain profiles capture clinically salient differences in medical history.

METHODS

To understand how pain conditions might be best organized, we applied a carefully designed a multi-variate pattern-learning approach to a subset of the UK Biobank (n = 34,337), the largest publicly available set of real-world pain experience data to define common population-level profiles. We performed a series of post hoc analyses to validate that each pain profile reflects real-world, clinically relevant differences in patient function by probing associations of each profile across 137 medication categories, 1425 clinician-assigned ICD codes, and 757 expert-curated phenotypes.

RESULTS

We report four unique, biologically based pain profiles that cut across medical specialties: pain interference, depression, medical pain, and anxiety, each representing different facets of functional impairment. Importantly, these profiles do not specifically align with variables believed to be important to the standard pain evaluation, namely painful body part, pain intensity, sex, or BMI. Correlations with individual-level clinical histories reveal that our pain profiles are largely associated with clinical variables and treatments of modifiable, chronic diseases, rather than with specific body parts. Across profiles, notable differences include opioids being associated only with the pain interference profile, while antidepressants linked to the three complimentary profiles. We further provide evidence that our pain profiles offer valuable, additional insights into patients' wellbeing that are not captured by the body-part framework and make recommendations for how our pain profiles might sculpt the future design of healthcare delivery systems.

CONCLUSION

Overall, we provide evidence for a shift in pain medicine delivery systems from the conventional, body-part-based approach to one anchored in the pain experience and holistic profiles of patient function. This transition facilitates a more comprehensive management of chronic diseases, wherein pain treatment is integrated into broader health strategies. By focusing on holistic patient profiles, our approach not only addresses pain symptoms but also supports the management of underlying chronic conditions, thereby enhancing patient outcomes and improving quality of life. This model advocates for a seamless integration of pain management within the continuum of care for chronic diseases, emphasizing the importance of understanding and treating the interdependencies between chronic conditions and pain.

An observational cross-sectional study on the characteristics of children and adolescents with non-specific spinal pain stratified by pain severity

BACKGROUND

Distinguishing self-limiting ('trivial') from potentially consequential spinal pain in childhood and adolescence is crucial to prevent over- or under-medicalization. The aim of this study was to stratify participants for severity of spinal pain and to investigate associations of pain severity with potential consequences of pain and some psychophysical and clinical factors.

METHODS

In 2020 and 2021, children and adolescents took part in a voluntary population-based spine screening event across Switzerland organized by the Swiss Chiropractors Association. The screening consisted of a questionnaire (14 questions) based on the Young Spine Questionnaire and a clinical examination by a chiropractor. Three subgroups of pain severity [no pain (including mild, occasional pain), one-sited moderate pain, one-sited severe or moderate/severe pain at multiple sites of the spine] were formed by combining the self-reported measures for pain intensity and pain frequency for two recall periods (lifetime, last week) according to literature. Multivariable logistic regression analyses were conducted to determine the associations between pain severity and potential pain consequences (impact of spinal pain on health and seeking medical advice because of spinal pain), as well as between pain severity and some psychophysical factors (head and/or belly pain, sleep problems, daytime tiredness) and clinical measures [trunk symmetry (rib hump), trunk muscle endurance (plank position)].

RESULTS

Of all participants (N = 457; 6-16 years; mean age = 10.9 ± 3.0 years; 220 boys), those with most severe spinal pain and with one-sited moderate pain in the last week had higher odds for reporting an impact of spinal pain on their health (OR = 13.5, 95%CI = 4.9-36.8; OR = 4.7, 95%CI = 1.5-14.4) and for searching medical advice because of spinal pain (OR = 11.6, 95%CI = 4.5-30.1; OR = 3.9, 95%CI = 1.6-9.2). Headache and/or belly pain (OR = 2.6, 95%CI = 1.2-5.5) and daytime tiredness (OR = 3.2, 95%CI = 1.3-7.9) increased the odds for having most severe pain compared to having no pain. The clinical measures were not associated with pain severity.

CONCLUSION

Stratification by pain severity, particularly when asked for pain in the last week, might help to minimize over- and under-medicalization of spinal pain in childhood and adolescence. Prospective studies are needed to clarify the relevance of the investigated clinical tests in the context of adolescent spinal pain.

Predicting Pain Response to a Remote Musculoskeletal Care Program for Low Back Pain Management: Development of a Prediction Tool

BACKGROUND

Low back pain (LBP) presents with diverse manifestations, necessitating personalized treatment approaches that recognize various phenotypes within the same diagnosis, which could be achieved through precision medicine. Although prediction strategies have been explored, including those employing artificial intelligence (AI), they still lack scalability and real-time capabilities. Digital care programs (DCPs) facilitate seamless data collection through the Internet of Things and cloud storage, creating an ideal environment for developing and implementing an AI predictive tool to assist clinicians in dynamically optimizing treatment.

OBJECTIVE

This study aims to develop an AI tool that continuously assists physical therapists in predicting an individual's potential for achieving clinically significant pain relief by the end of the program. A secondary aim was to identify predictors of pain nonresponse to guide treatment adjustments.

METHODS

Data collected actively (eg, demographic and clinical information) and passively in real-time (eg, range of motion, exercise performance, and socioeconomic data from public data sources) from 6125 patients enrolled in a remote digital musculoskeletal intervention program were stored in the cloud. Two machine learning techniques, recurrent neural networks (RNNs) and light gradient boosting machine (LightGBM), continuously analyzed session updates up to session 7 to predict the likelihood of achieving significant pain relief at the program end. Model performance was assessed using the area under the receiver operating characteristic curve (ROC-AUC), precision-recall curves, specificity, and sensitivity. Model explainability was assessed using SHapley Additive exPlanations values.

RESULTS

At each session, the model provided a prediction about the potential of being a pain responder, with performance improving over time (P<.001). By session 7, the RNN achieved an ROC-AUC of 0.70 (95% CI 0.65-0.71), and the LightGBM achieved an ROC-AUC of 0.71 (95% CI 0.67-0.72). Both models demonstrated high specificity in scenarios prioritizing high precision. The key predictive features were pain-associated domains, exercise performance, motivation, and compliance, informing continuous treatment adjustments to maximize response rates.

CONCLUSIONS

This study underscores the potential of an AI predictive tool within a DCP to enhance the management of LBP, supporting physical therapists in redirecting care pathways early and throughout the treatment course. This approach is particularly important for addressing the heterogeneous phenotypes observed in LBP.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04092946; https://clinicaltrials.gov/ct2/show/NCT04092946 and NCT05417685; https://clinicaltrials.gov/ct2/show/NCT05417685.

Childhood maltreatment and chronic "all over" body pain in adulthood: a counterfactual analysis using UK Biobank

ABSTRACT

Evidence linking adverse childhood experiences and chronic pain in adulthood is largely cross-sectional, potentially subject to recall bias and does not allow exploration of mediating pathways. We analysed a large population-based cohort (UK Biobank) using a causal framework, to determine if childhood maltreatment is related to chronic "all over" body pain in adulthood. We used doubly robust estimation with inverse probability weights to estimate the difference in risk of chronic pain "all over" between those exposed/not exposed to childhood maltreatment (abuse or neglect). In addition, we looked at interaction with adult stressful life events and examined mediation using inverse odds weighting in a generalized linear model. Using cases with complete data (n = 118,347), the risk of chronic "all over" body pain was higher in the exposed (6.3%, 95% confidence interval [CI] 6.0%-6.5%) than in the unexposed (4.0%; 95% CI 3.8%-4.2%). This difference remained in analyses stratified by sex. Conversely, when analyses were repeated with a negative control exposure, childhood sunburn, risk differences were 0.8% in women (95% CI 0.3%-1.3%) and 0.5% in men (95% CI 0.1%-0.9%). Childhood maltreatment and adult life events had similar effects, and there was a supra-additive risk (1.2%; 95% CI 0.6-1.7) when experiencing both. In mediation analyses, the total effect was a relative risk of 1.57 (95% CI 1.49-1.66), while the estimated indirect effect via all mediators was relative risk 1.16 (95% CI 1.14-1.18). Reducing childhood maltreatment would likely prevent cases of chronic widespread pain in adulthood. Stressful adult events and mediators may offer opportunities for intervention.

Predictors of outcome following an epidural steroid injection for disc-related sciatica: a Delphi consensus study

PURPOSE

Trial data shows modest reductions in leg pain, disability and surgery avoidance following epidural steroid injections (ESI) for severe sciatica. Despite their common use, there is no clear evidence about which patients are more likely to benefit from ESI. The aim of this study was to generate consensus on potential predictors of outcome following ESI for disc-related sciatica.

METHODS

A list of potential predictors of outcome was generated during a consensus meeting of seven experts. The items were subsequently presented in a two round on-line Delphi study to generate consensus among experts on which items are potential predictors of outcome. Consensus was defined as 70% agreement among participants.

RESULTS

Sixty-one items were generated during the consensus meeting. Of ninety experts invited to participate in the on-line Delphi study, 44 (48%) and 33 (73%) took part in rounds one and two respectively. Twenty-eight additional items suggested by participants in round one were included in round two. Overall, 14 items reached consensus reflecting domains of health, medication use, pain intensity, psychosocial factors, imaging findings and type of injection.

CONCLUSION

Based on expert consensus, items that can be routinely collected in clinical practice were identified as potential predictors of outcomes following ESI.

From fibrositis to fibromyalgia to nociplastic pain: how rheumatology helped get us here and where do we go from here?

Rheumatologists and rheumatology have had a prominent role in the conceptualisation of nociplastic pain since the prototypical nociplastic pain condition is fibromyalgia. Fibromyalgia had been previously known as fibrositis, until it became clear that this condition could be differentiatied from autoimmune disorders because of a lack of systemic inflammation and tissue damage. Nociplastic pain is now thought to be a third descriptor/mechanism of pain, in addition to nociceptive pain (pain due to peripheral damage or inflammation) and neuropathic pain. Nociplastic pain can occur in isolation, or as a co-morbidity with other mechanisms of pain, as commonly occurs in individuals with autoimmune disorders. We now know that the cardinal symptoms of nociplastic pain are widespread pain (or pain in areas not without evidence of inflammation/damage), accompanied by fatigue, sleep and memory issues. There is objective evidence of amplification/augmentation of pain, as well as of non-painful stimuli such as the brightness of lights and unpleasantness of sound or odors. Nociplastic pain states can be triggered by a variety of stressors such as trauma, infections and chronic stressors. Together these features suggest that the central nervous system (CNS) is playing a major role in causing and maintaining nociplastic pain, but these CNS factors may in some be driven by ongoing peripheral nociceptive input. The most effective drug therapies for nociplastic pain are non-opioid centrally acting analgesics such as tricyclics, serotonin-norepinephrine reuptake inhibitors and gabapentinoids. However the mainstay of therapy of nociplastic pain is the use of a variety of non-pharmacological integrative therapies, especially those which improve activity/exercise, sleep and address psychological co-morbidities.

Assessing the Association of Pain Intensity Scales on Quality of Life in Elderly Patients with Chronic Pain: A Nursing Approach

BACKGROUND

Chronic pain is prevalent among the elderly and significantly affects their quality of life (QoL). Pain intensity scales are crucial tools in evaluating the severity of pain and tailoring management strategies. This study investigates the relationship between various pain intensity scales and QoL among elderly patients with chronic pain, highlighting the implications for nursing practice.

METHODS

A cross-sectional study was conducted with 150 elderly patients (aged 65 and above) in Riyadh, Saudi Arabia. Participants were assessed using the Numeric Rating Scale (NRS), Visual Analog Scale (VAS), and McGill Pain Questionnaire (MPQ) alongside the 36-Item Short-Form Health Survey (SF-36) to evaluate QoL. Data analysis involved Pearson correlation and multiple regression to explore the association of pain intensity on QoL.

RESULTS

All pain scales showed significant negative correlations with QoL. The MPQ exhibited a significant association, suggesting its comprehensive nature captures the multidimensional association of pain more effectively. Regression analysis identified pain intensity, age, and duration of chronic pain as significant predictors of reduced QoL.

CONCLUSIONS

The findings emphasize the importance of selecting appropriate pain assessment tools that reflect the complex nature of pain in elderly patients. Implementing comprehensive pain assessments like the MPQ can enhance individualized care strategies and potentially improve the QoL in this population. This study underscores the role of nurses in optimizing pain management approaches tailored to the elderly.

Child maltreatment elevated the risk of late-life chronic pain: a biopsychosocial framework from the UK Biobank cohort

ABSTRACT

Understanding the development of chronic pain (CP) is challenging due to its multifactorial etiology. Child maltreatment (CM), encompassing various types of neglect and abuse affecting more than one-third of the population, is a critical aspect of early-life adversity with long-lasting impacts. It is increasingly recognized for its role in altering biopsychosocial processes, potentially increasing vulnerability to CP. However, the exact path connecting CM to CP is not fully elucidated, primarily attributable to limitations in prior research, including insufficient sample sizes, inadequate consideration of comprehensive mediative variables, and a lack of longitudinal data. To address these gaps, our study utilizes a large-scale dataset (n = 150,989) comprising both cross-sectional and longitudinal data, along with an extensive range of biopsychosocial variables. Our findings reveal that all types of CMs, except physical neglect, significantly increase the risk of CP, and all types of CPs, except headache, were affected by CM. Furthermore, we demonstrate that individuals with CM histories are more predisposed to comorbid CP conditions. Importantly, biopsychosocial factors are found to explain over 60% of the association between CM and CP, with psychological factors playing a key role. This study not only characterizes the relationship between CM and CP but also underscores the influence of psychosocial elements in this dynamic interplay. These findings offer important insights into the long-term impacts of CM and provide a foundation for developing targeted therapeutic and preventive strategies for CP.

Association of night-time sleep and daytime napping with painful temporomandibular disorder

BACKGROUND

Painful temporomandibular disorder (TMD) is the common cause of chronic oro-facial pain, which may interfere with sleep. Previous studies have documented an association between sleep and TMD.

OBJECTIVES

This study aimed to further explore the association of night-time sleep and daytime napping with painful TMD.

METHODS

A total of 419 patients (aged 31.88 ± 11.54 years with women forming 85.4%) from a TMD/Orofacial Pain center were enrolled. Patients' sleep conditions were evaluated with the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and information on night-time sleep duration, napping duration and napping frequency was interviewed. TMD was diagnosed according to the Diagnostic Criteria for TMD protocol and stratified into myalgia (muscle pain), arthralgia (joint pain) and combined (muscle and joint pain) subgroups. The severity of TMD was measured with the Fonseca Anamnestic Index (FAI) questionnaire. Restricted cubic spline (RCS) regression models were established to explore relationships between sleep and painful TMD subgroups.

RESULTS

Patients with poor sleep quality (PSQI≥6) had higher FAI scores (median 60, p < .001) and higher proportions of painful TMDs. The myalgia subgroup had higher PSQI scores (median 8, p < .001) than the arthralgia subgroup. The RCS models indicated a non-linear relationship between night-time sleep duration and myalgia (p < .001), which was not observed in arthralgia. However, there were no significant findings concerning napping and painful TMD subgroups.

CONCLUSION

This study found that the association between sleep and TMD is mainly related to painful TMD conditions, which are associated with night-time sleep duration.

Long-term Trajectories of Low Back Pain in Older Men: A Prospective Cohort Study With 10-Year Analysis of the Osteoporotic Fractures in Men Study

Although low back pain (LBP) may persist or recur over time, few studies have evaluated the individual course of LBP over a long-term period, particularly among older adults. Based on data from the longitudinal Osteoporotic Fractures in Men (MrOS) Study, we aimed to identify and describe different LBP trajectories in older men and characterize members in each trajectory group. A total of 5 976 community-dwelling men (mean age = 74.2) enrolled at 6 U.S. sites were analyzed. Participants self-reported LBP (yes/no) every 4 months for a maximum of 10 years. Latent class growth modeling was performed to identify unique LBP trajectory groups that explained variation in the LBP data. The association of baseline characteristics with trajectory group membership was assessed using univariable and multivariable multinominal logistic regression. A 5-class solution was chosen; no/rare LBP (n = 2 442/40.9%), low frequency-stable LBP (n = 1 040/17.4%), low frequency-increasing LBP (n = 719/12%), moderate frequency-decreasing LBP (n = 745/12.5%), and high frequency-stable LBP (n = 1 030/17.2%). History of falls (OR = 1.52), history of LBP (OR = 6.37), higher physical impairment (OR = 1.51-2.85), and worse psychological function (OR = 1.41-1.62) at baseline were all associated with worse LBP trajectory groups in this sample of older men. These findings present an opportunity for targeted interventions and/or management to older men with worse or increasing LBP trajectories and associated modifiable risk factors to reduce the impact of LBP and improve quality of life.

A novel temperature‐controlled device with standardized manipulation improves chronic back pain mediated by modulating deep muscle thickness: A multicenter randomized controlled trial

Background

Chronic back pain affected 619 million people globally in 2020 which accounts for a heavy disease burden causing tremendous productivity losses. Current therapies including ibuprofen, duloxetine, and opioids might cause side effects and even severe drug use disorders. Therefore, a non‐pharmacologic therapy with better or equivalent efficacy and fewer side effects is needed.

Methods

We did a multi‐center, single‐blinded, randomized, positive drug controlled, clinical trial. Patients with chronic back pain in moderate severity were randomized into receiving hot stone massage or flurbiprofen plaster group. Both interventions were 2 weeks with a follow‐up of 4 weeks. The primary outcome was the change in the score of the Global Pain Scale (GPS) from baseline to week 2. Secondary outcomes included Numerical Rating Scale (NRS), Chronic Pain Acceptance Questionnaire (CPAQ), Pain Self‐Efficacy Questionnaire (PSEQ), Hospital Anxiety and Depression Scale (HADS), and Short Form‐36 (SF36) from baseline to week 2 and week 6. Exploratory outcome assessment included the muscle thickness measured by ultrasound. Any adverse event was monitored throughout the study period.

Results

A total of 120 patients were enrolled in this trial. At 2 weeks GPS decreased significantly in the hot stone massage group compared to the flurbiprofen group (difference between groups = ‐8.1 points, 95% confidence interval [CI] ‐15.8 to ‐0.3, p = 0.047). Moreover, hot stone massage also showed more improvement at 2 weeks compared to flurbiprofen, including NRS (‐0.5 points, 95% CI ‐1.0 to ‐0.1, p = 0.029), PSEQ (5.4 points, 95% CI 0.5 to 10.2, p = 0.030), and mental component of Short Form‐36 (SF‐36) (1.7 points, 95% CI 0.4 to 2.9, p = 0.010), but not in CPAQ (p = 0.131), HADS (p = 0.303 for depression, p = 0.399 for anxiety), or SF‐36 (p = 0.129 for physical component, p = 0.246 for social component, p = 0.076 for fatigue component). A total of two participants in the hot stone massage group reported mild pain on skin surface when receiving the procedure at the first intervention session.

Does the distribution of musculoskeletal pain shape the fate of long-term sick leave? A prospective cohort study with register follow-up

ABSTRACT

Although multisite pain can markedly reduce work ability, the relevance of the bodily pain distribution as a predictor of long-term sick leave is still unknown. This study aimed to investigate the association between musculoskeletal pain distributions and long-term sick leave in the general working population of Denmark and included 66,177 currently employed wage earners without long-term sick leave during the prior 52 weeks. Participants reported whether they had pain in the lower extremity (hips/knees), upper extremity (neck/shoulders), or the low back. The analysis controlled for age, sex, year of survey reply, educational level, occupational group, psychosocial work factors, body max index, smoking, leisure-time physical activity, and mental health confounders. The results demonstrated that the risk of long-term sick leave increased with the number of pain sites. Compared with no pain, localized pain in any body region increased the risk/hazard by 25% to 29% (HR [95% CI]: 1.29 [1.07-1.54] for pain only in the low back), whereas pain in 2 regions increased the risk by 39% to 44% (HR [95% CI]: 1.41 [1.18-1.69] for pain in the low back + hips/knees). Workers reporting pain in all 3 regions experienced a 72% increased risk (HR [95% CI]: 1.72 [1.55-1.91]). Thus, the number of pain regions seems to matter more than the exact pain location. The spatial extension of musculoskeletal pain in workers functions as a gradient system, where pain spread throughout the body is an independent indicator of the high risk of long-term sick leave.

Preserved tactile distance estimation despite body representation distortions in individuals with fibromyalgia

Our mental representation of our body depends on integrating various sensory modalities, such as tactile information. In tactile distance estimation (TDE) tasks, participants must estimate the distance between two tactile tips applied to their skin. This measure of tactile perception has been linked to body representation assessments. Studies in individuals with fibromyalgia (FM), a chronic widespread pain syndrome, suggest the presence of body representation distortions and tactile alterations, but TDE has never been examined in this population. Twenty participants with FM and 24 pain-free controls performed a TDE task on three Body regions (upper limb, trunk, lower limb), in which they manually estimated the interstimuli distance on a tablet. TDE error, the absolute difference between the estimation and the interstimuli distance, was not different between the Groups, on any Body region. Drawings of their body as they felt it revealed clear and frequent distortions of body representation in the group with FM, compared to negligible perturbations in controls. This contrast between distorted body drawings and unaltered TDE suggests a preserved integration of tactile information but an altered integration of this information with other sensory modalities to generate a precise and accurate body representation. Future research should investigate the relative contribution of each sensory information and prior knowledge about the body in body representation in individuals with FM to shed light on the observed distortions.

Association between chronic pain and risk of cardiometabolic multimorbidity: a prospective cohort study

BACKGROUND

Although chronic pain was deleteriously related to single cardiometabolic diseases, the relationship between chronic pain and cardiometabolic multimorbidity remains unclear. The purpose of this study was to investigate the association between chronic pain with the risk of cardiometabolic multimorbidity.

METHODS

A prospective cohort study included 452 818 participants who were free of cardiometabolic multimorbidity at baseline. Chronic pain was assessed in diverse anatomical sites including the head, face, neck/shoulder, stomach/abdominal area, back, hip and knee or 'all over the body'. Participants were classified into six groups according to the amount of chronic pain sites: no chronic pain, chronic pain at one, two, three and four or more sites, and those reporting pain 'all over the body'. Cardiometabolic multimorbidity was defined as the occurrence of at least two cardiometabolic diseases, involving type 2 diabetes, ischaemic heart disease and stroke.

RESULTS

After a median follow-up of 13.7 years, 4445 participants developed cardiometabolic multimorbidity. Compared with individuals without chronic pain, those experiencing chronic pain in four or more sites were associated with a 1.82-fold (HR: 1.82, 95% CI: 1.61, 2.06) higher risk of cardiometabolic multimorbidity. Pain distributed 'all over the body' was associated with a 59% (HR: 1.59, 95% CI: 1.30, 1.93) increased risk of cardiometabolic multimorbidity Additionally, individuals who had chronic pain in both the head and stomach/abdomen showed the highest risk with cardiometabolic multimorbidity (HR: 1.88, 95% CI: 1.60, 2.20).

CONCLUSIONS

Our findings suggested that there was an elevated risk of cardiometabolic multimorbidity associated with an increased amount of chronic pain sites.

Pressure Pain Sensitivity and Chronotype: A Population-based Study of Middle-aged Finns

Evening chronotype individuals experience pain more often than morning chronotypes, but relationships with pain sensitivity have rarely been studied. We examined whether chronotype is associated with pressure pain sensitivity, with special reference to mental health disorders, insomnia, and chronic musculoskeletal (MSK) pain as potential moderating factors. The study sample consisted of members of the Northern Finland Birth Cohort 1966 aged 46. Pressure pain threshold and tolerance were measured via the standardized protocol, categorized as lowest quartile versus others. Chronotype (morning [M; the reference], intermediate [I], and evening [E]) was defined using the Short Morningness-Eveningness questionnaire. Sex-stratified binary logistic regression models were separately adjusted for education, body mass index, long-term diseases (fully adjusted model), and for mental health disorders, insomnia, and chronic MSK pain (a residual confounding analysis). Interaction terms (Chronotype × Mental health/insomnia/chronic MSK pain) were tested. The study had 2,132 males and 2,830 females. The E-type males had 1.5-fold odds of having a low pain threshold (fully adjusted odds ratio [OR] 1.45, 95% confidence interval 1.05-2.00) and pressure pain tolerance (fully adjusted OR 1.47, 1.07-2.02), in comparison to M-types. Having a mental health disorder intensified the association with low pain threshold fourfold (4.06, 1.56-10.6). Being an E-type female was also associated with a low pain threshold, but the association was statistically nonsignificant (fully adjusted OR 1.18, .90-1.53). No statistically significant interactions were found among females. These results emphasize the role of chronotype in pain sensitivity and add an understanding of pain experience in light of innate circadian types. PERSPECTIVE: Male evening chronotypes are more sensitive to pain than morning chronotypes. Diagnosed mental health disorders in particular indicate a low pain threshold for evening chronotype males.

Minocycline Abrogates Individual Differences in Nerve Injury-Evoked Affective Disturbances in Male Rats and Prevents Associated Supraspinal Neuroinflammation

Chronic neuropathic pain precipitates a complex range of affective and behavioural disturbances that differ markedly between individuals. While the reasons for differences in pain-related disability are not well understood, supraspinal neuroimmune interactions are implicated. Minocycline has antidepressant effects in humans and attenuates affective disturbances in rodent models of pain, and acts by reducing neuroinflammation in both the spinal cord and brain. Previous studies, however, tend not to investigate how minocycline modulates individual affective responses to nerve injury, or rely on non-naturalistic behavioural paradigms that fail to capture the complexity of rodent behaviour. We investigated the development and resolution of pain-related affective disturbances in nerve-injured male rats by measuring multiple spontaneous ethological endpoints on a longitudinal naturalistic foraging paradigm, and the effect of chronic oral minocycline administration on these changes. Disrupted foraging behaviours appeared in 22% of nerve-injured rats - termed 'affected' rats - and were present at day 14 but partially resolved by day 21 post-injury. Minocycline completely prevented the emergence of an affected subgroup while only partly attenuating mechanical allodynia, dissociating the relationship between pain and affect. This was associated with a lasting downregulation of ΔFosB expression in ventral hippocampal neurons at day 21 post-injury. Markers of microglia-mediated neuroinflammation were not present by day 21, however proinflammatory microglial polarisation was apparent in the medial prefrontal cortex of affected rats and not in CCI minocycline rats. Individual differences in affective disturbances following nerve injury are therefore temporally related to altered microglial morphology and hippocampal neuronal activation, and are abrogated by minocycline.

Deciphering nociplastic pain: clinical features, risk factors and potential mechanisms

Nociplastic pain is a mechanistic term used to describe pain that arises or is sustained by altered nociception, despite the absence of tissue damage. Although nociplastic pain has distinct pathophysiology from nociceptive and neuropathic pain, these pain mechanisms often coincide within individuals, which contributes to the intractability of chronic pain. Key symptoms of nociplastic pain include pain in multiple body regions, fatigue, sleep disturbances, cognitive dysfunction, depression and anxiety. Individuals with nociplastic pain are often diffusely tender - indicative of hyperalgesia and/or allodynia - and are often more sensitive than others to non-painful sensory stimuli such as lights, odours and noises. This Review summarizes the risk factors, clinical presentation and treatment of nociplastic pain, and describes how alterations in brain function and structure, immune processing and peripheral factors might contribute to the nociplastic pain phenotype. This article concludes with a discussion of two proposed subtypes of nociplastic pain that reflect distinct neurobiological features and treatment responsivity.

Variability in the prevalence of depression among adults with chronic pain: UK Biobank analysis through clinical prediction models

BACKGROUND

The prevalence of depression among people with chronic pain remains unclear due to the heterogeneity of study samples and definitions of depression. We aimed to identify sources of variation in the prevalence of depression among people with chronic pain and generate clinical prediction models to estimate the probability of depression among individuals with chronic pain.

METHODS

Participants were from the UK Biobank. The primary outcome was a "lifetime" history of depression. The model's performance was evaluated using discrimination (optimism-corrected C statistic) and calibration (calibration plot).

RESULTS

Analyses included 24,405 patients with chronic pain (mean age 64.1 years). Among participants with chronic widespread pain, the prevalence of having a "lifetime" history of depression was 45.7% and varied (25.0-66.7%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.66; good calibration on the calibration plot) included age, BMI, smoking status, physical activity, socioeconomic status, gender, history of asthma, history of heart failure, and history of peripheral artery disease. Among participants with chronic regional pain, the prevalence of having a "lifetime" history of depression was 30.2% and varied (21.4-70.6%) depending on patient characteristics. The final clinical prediction model (optimism-corrected C statistic: 0.65; good calibration on the calibration plot) included age, gender, nature of pain, smoking status, regular opioid use, history of asthma, pain location that bothers you most, and BMI.

CONCLUSIONS

There was substantial variability in the prevalence of depression among patients with chronic pain. Clinically relevant factors were selected to develop prediction models. Clinicians can use these models to assess patients' treatment needs. These predictors are convenient to collect during daily practice, making it easy for busy clinicians to use them.

Clinical data mining: challenges, opportunities, and recommendations for translational applications

Clinical data mining of predictive models offers significant advantages for re-evaluating and leveraging large amounts of complex clinical real-world data and experimental comparison data for tasks such as risk stratification, diagnosis, classification, and survival prediction. However, its translational application is still limited. One challenge is that the proposed clinical requirements and data mining are not synchronized. Additionally, the exotic predictions of data mining are difficult to apply directly in local medical institutions. Hence, it is necessary to incisively review the translational application of clinical data mining, providing an analytical workflow for developing and validating prediction models to ensure the scientific validity of analytic workflows in response to clinical questions. This review systematically revisits the purpose, process, and principles of clinical data mining and discusses the key causes contributing to the detachment from practice and the misuse of model verification in developing predictive models for research. Based on this, we propose a niche-targeting framework of four principles: Clinical Contextual, Subgroup-Oriented, Confounder- and False Positive-Controlled (CSCF), to provide guidance for clinical data mining prior to the model's development in clinical settings. Eventually, it is hoped that this review can help guide future research and develop personalized predictive models to achieve the goal of discovering subgroups with varied remedial benefits or risks and ensuring that precision medicine can deliver its full potential.

Introduction to a special issue on big data and pain

This special issue comprised 7 articles from leaders in the field that focus on "big pain data", the large datasets and the associated methods for data analysis that are currently emerging in pain research. This collection of articles highlights the power and potential as well as points of caution that multi-disciplinary research utilising big data and their associated methods and interpretations present for pain research.