Validity of the cold pressor test and pain sensitivity questionnaire via online self-administration

Does pain tolerance mediate the effect of physical activity on chronic pain in the general population? The Tromsø Study

ABSTRACT

Knowledge is needed regarding mechanisms acting between physical activity (PA) and chronic pain. We investigated whether cold pain tolerance mediates an effect of leisure-time physical activity on the risk of chronic pain 7 to 8 years later using consecutive surveys of the population-based Tromsø Study. We included participants with information on baseline leisure-time PA (LTPA) and the level of cold pressor-assessed cold pain tolerance, who reported chronic pain status at follow-up as any of the following: chronic pain for ≥3 months, widespread chronic pain, moderate-to-severe chronic pain, or widespread moderate-to-severe chronic pain. We included 6834 participants (52% women; mean age, 55 years) in counterfactual mediation analyses. Prevalence decreased with severity, for example, 60% for chronic pain vs 5% for widespread moderate-to-severe chronic pain. People with one level higher LTPA rating (light to moderate or moderate to vigorous) at baseline had lower relative risk (RR) of 4 chronic pain states 7 to 8 years later. Total RR effect of a 1-level LTPA increase was 0.95 (0.91-1.00), that is, -5% decreased risk. Total effect RR for widespread chronic pain was 0.84 (0.73-0.97). Indirect effect for moderate-to-severe chronic pain was statistically significant at RR 0.993 (0.988-0.999); total effect RR was 0.91 (0.83-0.98). Statistically significantly mediated RR for widespread moderate-to-severe chronic pain was 0.988 (0.977-0.999); total effect RR was 0.77 (0.64-0.94). This shows small mediation of the effect of LTPA through pain tolerance on 2 moderate-to-severe chronic pain types. This suggests pain tolerance to be one possible mechanism through which PA modifies the risk of moderate-to-severe chronic pain types with and without widespread pain.

Empirical comparison of deep learning models for fNIRS pain decoding

Introduction

Pain assessment is extremely important in patients unable to communicate and it is often done by clinical judgement. However, assessing pain using observable indicators can be challenging for clinicians due to the subjective perceptions, individual differences in pain expression, and potential confounding factors. Therefore, the need for an objective pain assessment method that can assist medical practitioners. Functional near-infrared spectroscopy (fNIRS) has shown promising results to assess the neural function in response of nociception and pain. Previous studies have explored the use of machine learning with hand-crafted features in the assessment of pain.

Methods

In this study, we aim to expand previous studies by exploring the use of deep learning models Convolutional Neural Network (CNN), Long Short-Term Memory (LSTM), and (CNN-LSTM) to automatically extract features from fNIRS data and by comparing these with classical machine learning models using hand-crafted features.

Results

The results showed that the deep learning models exhibited favourable results in the identification of different types of pain in our experiment using only fNIRS input data. The combination of CNN and LSTM in a hybrid model (CNN-LSTM) exhibited the highest performance (accuracy = 91.2%) in our problem setting. Statistical analysis using one-way ANOVA with Tukey's (post-hoc) test performed on accuracies showed that the deep learning models significantly improved accuracy performance as compared to the baseline models.

Discussion

Overall, deep learning models showed their potential to learn features automatically without relying on manually-extracted features and the CNN-LSTM model could be used as a possible method of assessment of pain in non-verbal patients. Future research is needed to evaluate the generalisation of this method of pain assessment on independent populations and in real-life scenarios.

Spatial summation of pain is associated with pain expectations: Results from a home-based paradigm

The purpose of this study was to reproduce the previously observed spatial summation of pain effect (SSp) using non-laboratory procedures and commercial equipment. An additional aim was to explore the association between expectations and SSp. The Cold Pressor Task (CPT) was used to induce SSp. Healthy participants (N = 68) immersed their non-dominant hands (divided into 5 segments) into cold water (CPT). Two conditions were used 1) gradual hand immersion (ascending condition) and 2) gradual hand withdrawal (descending condition). Pain intensity was measured on a Visual Analogue Scale (VAS). Psychological factors, such as the participants' expectations of pain intensity were also measured on a VAS. Results showed significant SSp (χ2(4) = 116.90, p < 0.001), reproduced with non-laboratory equipment in a home-based set-up. Furthermore, two novel findings were observed: i) there was a significant correlation between expectations and perceived pain, indicating a link between pain expectations and SSp, ii) spatial summation increased with the increase in duration exposure to the noxious stimulus (Wald χ2(8) = 80.80, p < 0.001). This study suggests that SSp is associated with pain expectations and can be formed by a mixture of excitatory and inhibitory mechanisms potentially driven by temporal characteristics of neural excitation. Moreover, this study proposes a new feasible way to induce SSp using a home-based set-up.

Do "central sensitization" questionnaires reflect measures of nociceptive sensitization or psychological constructs? A systematic review and meta-analyses

ABSTRACT

Central sensitization (CS) is defined as an increased nociceptive responsiveness due to sensitization of neurons in the central nervous system, usually the result of prolonged nociceptive input or a disease state associated with noxious inputs (eg, polyarthritis). The concept of CS has recently been adopted in clinical assessments of chronic pain, but its diagnosis in humans may now include a wide range of hypervigilant responses. The purpose of this review is to ascertain whether self-report questionnaires linked with CS are associated with enhanced nociceptive responses or whether they measure sensitivity in a broader sense (ie, emotional responses). According to our published, PROSPERO-registered review protocol (CRD42021208731), a predefined search of studies that involve the Central Sensitization Inventory (CSI) or Pain Sensitivity Questionnaire (PSQ), correlated with either nociceptive sensory tests or emotional hypervigilance was conducted on MEDLINE, PsycINFO, and Web of Science. Correlations between the CSI or PSQ with our primary outcomes were extracted and meta-analysed. A review of 66 studies totalling 13,284 participants found that the CSI (but not the PSQ) strongly correlated with psychological constructs: depression, anxiety, stress, pain catastrophising, sleep, and kinesiophobia. The CSI and PSQ showed weak or no correlations with experimental measures of nociceptive sensitivity: pain thresholds, temporal summation, or conditioned pain modulation. The PSQ did, however, correlate strongly with phasic heat and tonic cold pain tests. The studies reviewed did not provide sufficient evidence that self-report measures reflect a canonical understanding of CS. The CSI more closely reflects psychological hypervigilance than increased responsiveness of nociceptive neurons.

Automatic detection of pain using machine learning

Pain is one of the most common symptoms reported by individuals presenting to hospitals and clinics and is associated with significant disability and economic impacts; however, the ability to quantify and monitor pain is modest and typically accomplished through subjective self-report. Since pain is associated with stereotypical physiological alterations, there is potential for non-invasive, objective pain measurements through biosensors coupled with machine learning algorithms. In the current study, a physiological dataset associated with acute pain induction in healthy adults was leveraged to develop an algorithm capable of detecting pain in real-time and in natural field environments. Forty-one human subjects were exposed to acute pain through the cold pressor test while being monitored using electrocardiography. A series of respiratory and heart rate variability features in the time, frequency, and nonlinear domains were calculated and used to develop logistic regression classifiers of pain for two scenarios: (1) laboratory/clinical use with an F1 score of 81.9% and (2) field/ambulatory use with an F1 score of 79.4%. The resulting pain algorithms could be leveraged to quantify acute pain using data from a range of sources, such as ECG data in clinical settings or pulse plethysmography data in a growing number of consumer wearables. Given the high prevalence of pain worldwide and the lack of objective methods to quantify it, this approach has the potential to identify and better mitigate individual pain.

Genome-wide association study of pain sensitivity assessed by questionnaire and the cold pressor test

ABSTRACT

We deployed an online pain sensitivity questionnaire (PSQ) and an at-home version of the cold pressor test (CPT) in a large genotyped cohort. We performed genome-wide association studies on the PSQ score (25,321 participants) and CPT duration (6853). We identified one new genome-wide significant locus associated with the PSQ score, which was located in the TSSC1 (also known as EIPR1 ) gene (rs58194899, OR = 0.950 [0.933-0.967], P -value = 1.9 × 10 -8 ). Although high pain sensitivity measured by both PSQ and CPT was associated with individual history of chronic and acute pains, genetic correlation analyses surprisingly suggested an opposite direction: PSQ score was inversely genetically correlated with neck and shoulder pain ( rg = -0.71), rheumatoid arthritis (-0.68), and osteoarthritis (-0.38), and with known risk factors, such as the length of working week (-0.65), smoking (-0.36), or extreme BMI (-0.23). Gene-based analysis followed by pathway analysis showed that genome-wide association studies results were enriched for genes expressed in the brain and involved in neuronal development and glutamatergic synapse signaling pathways. Finally, we confirmed that females with red hair were more sensitive to pain and found that genetic variation in the MC1R gene was associated with an increase in self-perceived pain sensitivity as assessed by the PSQ.

Does art reduce pain and stress? A registered report protocol of investigating autonomic and endocrine markers of music, visual art, and multimodal aesthetic experience

The pain- and stress-reducing effects of music are well-known, but the effects of visual art, and the combination of these two, are much less investigated. We aim to (1) investigate the pain- and (2) stress-reducing effects of multimodal (music + visual art) aesthetic experience as we expect this to have stronger effects than a single modal aesthetic experience (music/ visual art), and in an exploratory manner, (3) investigate the underlying mechanisms of aesthetic experience, and the (4) individual differences. In a repeated-measures design (music, visual art, multimodal aesthetic experience, control) participants bring self-selected “movingly beautiful” visual artworks and pieces of music to the lab, where pain and stress are induced by the cold pressor test. Activity of the pain and stress responsive systems are measured by subjective reports, autonomic (electrocardiography, electrodermal activity, salivary alpha-amylase) and endocrine markers (salivary cortisol).

Cardiovascular Responses to Commonly Used Tests in and Outside of the Laboratory Settings

Several tests are available for assessing cardiovascular response to various interventions which may be given in the laboratory, or outside of it in the field. The tests are meant to excite or deactivate cardiovascular and other sensory receptors which signal the central mechanisms. They have been found useful in generating data to study cardiovascular effects on subjects exposed to specialized physical training (e.g., athletes), in the evaluation of people engaged in special occupations such as pilots, astronauts, and other military personnel, and in training undergraduate and postgraduate students. If the response does not fit into the physiological norm, it may reflect a temporary aberration, or a more serious defect in the cardiovascular control mechanism because of disease. Interpretation of data generated may vary between various operators/observers. Here, an attempt has been made to bring out responses of the cardiovascular system to the commonly used tests, and their applicability in clinical situations.

Factors Associated with Pain Treatment Satisfaction Among Patients with Chronic Non-Cancer Pain and Substance Use

INTRODUCTION

A better understanding of pain treatment satisfaction in patients with chronic noncancer pain (CNCP) and substance use is needed, especially as opioid prescribing policies are changing. We sought to identify factors associated with pain treatment satisfaction in individuals with CNCP on recent opioid therapy and prior or active substance use.

METHODS

An exploratory cross-sectional analysis using baseline data from a cohort study of 300 adults with CNCP receiving >20 morphine milligram equivalents of opioids for ≥3 of the preceding 12 months and prior or active substance use. Participants completed interviews, clinical assessments, urine drug screening, and medical chart review.

RESULTS

Participants were predominantly middle-aged (mean age 57.5 years), Black (44%), and cisgender men (60%). One-third (33%) had high, 28% moderate, and 39% low pain treatment satisfaction. Post-traumatic stress disorder (PTSD), tobacco use, past-year opioid discontinuation, and higher average pain scores were associated with lower satisfaction. HIV and prescription cannabis use were associated with higher satisfaction.

CONCLUSIONS

The relationship between PTSD and tobacco use with lower satisfaction should be explored to augment pain outcomes. Higher satisfaction among individuals with HIV and prescription cannabis use presents potential research areas to guide CNCP management and reduce reliance on opioid therapies.

More Insight on the Role of Personality Traits and Sensitivity to Experimental Pain

Purpose

The present study aimed to assess the influence of personality traits on the variability of sensitivity to pain in two distinct groups of healthy subjects with low versus high sensitivity to pain (LSP vs HSP, respectively).

Methods

Healthy subjects (n=156) were allocated to two groups according to their tolerability to cold stimulation (cold pressor test, CPT, 1°C). Group LSP (n=76) reached the cut-off time of 180±0 sec, and a size matched group of HSP (n=80) tolerated the CPT for an average of 10.5±3.4 sec only. Subjects from both groups completed the self-reported pain sensitivity questionnaire (PSQ), the Pain Catastrophizing Scale (PCS), and the Neuroticism Extraversion Openness - Five Factor Inventory (NEO-FFI).

Results

In comparison to the LSP group, HSP individuals had higher scores of PSQ (p<0.001), catastrophizing (p=0.001), and extraversion (p=0.01). By adjusting for age and gender, mediation analyses revealed that catastrophizing mediated the relationship between neuroticism and pain sensitivity, both in the allocation of subjects to a certain group of sensitivity to pain (LSP or HSP, B=0.02 95% CI: 0.006–0.040) and in the PSQ score (B=0.01 95% CI: 0.001–0.023).

Conclusion

These results, which were demonstrated by two different prisms (CPT and PSQ), point to the potential of the five-factor inventory and pain catastrophizing scale as tools for identifying specific personality traits associated with a high sensitivity to pain.

Race, pain, and opioids among patients with chronic pain in a safety-net health system

BACKGROUND

Recent changes in opioid prescribing practices in the US may exacerbate disparities in opioid access among Black compared to White patients.

METHODS

To evaluate racial disparities in opioid prescribing and stewardship, we used baseline data collected from 2017 to 2019 for a longitudinal cohort of patients with chronic non-cancer pain and a history of illicit substance use. Sociodemographic characteristics, pain, psychological distress, substance use, and opioid prescription practices were compared between Black and White participants. We conducted multivariable logistic regression with race as the outcome. We also compared yellow flag events (opioid-related emergency department visits, illicit substances on urine drug screens, provider-documentation of concerning behaviors) by race.

RESULTS

Over half of participants analyzed were Black (57%) and the remainder White (43%). Participants with worse average pain in the past three months (adjusted odds ratio [AOR]:1.29, 95%CI:1.08-1.55, p = 0.006) had higher odds of being Black. Past-year injection drug use (AOR:0.39, 95%CI:0.16-0.94, p = 0.04) and a higher past-year maximum opioid dose (AOR per 10 morphine milligram equivalents (MME):0.99, 95%CI:0.98-1.00, p = 0.006) were associated with lower odds of being Black. We found no differences by race in the use of opioid stewardship measures or discontinuation of opioids based on yellow flag events.

CONCLUSION

Lower past-year maximum MME dose, despite higher average pain and less injection drug use, may represent bias away from prescribing opioids for chronic pain among Black patients. This could be due to unmeasured implicit provider bias or patient-level factors (e.g., utilizing non-opioid pain coping strategies or being less likely to request additional opioids).