Influence of self-reported physical activity and sleep quality on conditioned pain modulation in the orofacial region

The Impact of Sleep Disturbances on Endogenous Pain Modulation: A Systematic Review and Meta-Analysis

The bidirectional relationship between sleep and pain problems has been extensively demonstrated but despite all the accumulating evidence, their shared mechanisms are currently not fully understood. This review examined the association between sleep disturbances, defined as a broad array of sleep-related outcomes (eg, poor quality, short duration, insomnia), and endogenous pain modulation (EPM) in healthy and clinical populations. Our search yielded 6,151 references, and 37 studies met the eligibility criteria. Qualitative results showed mixed findings regarding the association between sleep disturbances and temporal summation of pain (TSP) and conditioned pain modulation (CPM), with poor sleep more commonly associated with decreased pain inhibition in both populations. Quantitative results indicated that such associations were not statistically significant, neither in healthy populations when EPM outcomes were assessed for changes pre-/post-sleep intervention (TSP: .31 [95%CI: -.30 to .92]; P = .321; CPM: .40 [95%CI: -.06 to .85] P = .088) nor in clinical populations when such association was assessed via correlation (TSP: -.00 [95%CI: -.22 to .21] P = .970; CPM: .12 [95%CI: -.05 to .29]; P = .181). For studies that reported results by sex, meta-analysis showed that experimental sleep disturbances impaired pain inhibition in females (1.43 [95%CI: .98-1.88]; P < .001) but not in males (-.30 [95%CI: -2.69 to 1.60]; P = .760). Only one study investigating the association between sleep disturbances and offset analgesia was identified, while no studies assessing spatial summation of pain were found. Overall, this review provides a comprehensive overview of the association between sleep disturbances and EPM function, emphasizing the need for further investigation to clarify specific mechanisms and phenotypic subtypes. PERSPECTIVE: This review shines a light on the association between sleep disturbances and endogenous pain modulation function. Qualitatively, we found a frequent association between reduced sleep quality and impaired pain inhibition. However, quantitatively such an association was not corroborated. Sex-specific effects were observed, with females presenting sleep-related impaired pain inhibition but not males.

Exploratory analysis of 5 supervised machine learning models for predicting the efficacy of the endogenous pain inhibitory pathway in patients with musculoskeletal pain

OBJECTIVES

The identification of factors that influence the efficacy of endogenous pain inhibitory pathways remains challenging due to different protocols and populations. We explored five machine learning (ML) models to estimate the Conditioned Pain Modulation (CPM) efficacy.

DESIGN

Exploratory, cross-sectional design.

SETTING AND PARTICIPANTS

This study was conducted in an outpatient setting and included 311 patients with musculoskeletal pain.

METHODS

Data collection included sociodemographic, lifestyle, and clinical characteristics. CPM efficacy was calculated by comparing the pressure pain thresholds before and after patients submerged their non-dominant hand in a bucket of cold water (cold-pressure test) (1-4 °C). We developed five ML models: decision tree, random forest, gradient-boosted trees, logistic regression, and support vector machine.

MAIN OUTCOME MEASURES

Model performance were assessed using receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity, precision, recall, F1-score, and the Matthews Correlation Coefficient (MCC). To interpret and explain the predictions, we used SHapley Additive explanation values and Local Interpretable Model-Agnostic Explanations.

RESULTS

The XGBoost model presented the highest performance with an accuracy of 0.81 (95% CI = 0.73 to 0.89), F1 score of 0.80 (95% CI = 0.74 to 0.87), AUC of 0.81 (95% CI: 0.74 to 0.88), MCC of 0.61, and Kappa of 0.61. The model was influenced by duration of pain, fatigue, physical activity, and the number of painful areas.

CONCLUSIONS

XGBoost showed potential in predicting the CPM efficacy in patients with musculoskeletal pain on our dataset. Further research is needed to ensure the external validity and clinical utility of this model.

Effect of High-definition Transcranial Direct Current Stimulation on Conditioned Pain Modulation in Healthy Adults: A Crossover Randomized Controlled Trial

The disorder of the conditioned pain modulation (CPM) system is one of the main causes of pain perception in individuals. High-definition transcranial direct current stimulation (HD-tDCS) targeting specific brain areas was indicated to have an analgesic effect possibly by activating the endogenous pain inhibition pathway evident in CPM. However, discrepancies were found in previous limited studies of varied homogeneity and quality. Therefore, the present study applied 2 mA HD-tDCS (20 min) in the left primary motor cortex (M1) among 35 healthy adults with a blinded crossover study design, to investigate its effectiveness on optimizing the analgesic effect in healthy individuals through assessing changes of the CPM. The univariate and multivariate general linear models were used to evaluate the intervention effect between-group on the Δ-value (after-intervention minus before-intervention) during CPM (primary outcome), pressure pain threshold (PPT), and cold pressure threshold (CPT) (secondary outcome), respectively. A significant between-group difference in Δ-CPM was found for active stimulation. HD-tDCS significantly improved the analgesic efficiency of Δ-CPM, compared with the sham control, after adjusting the confounding factors including age, gender, psychological status, as well as the sequence effect. The changes of CPM were positively correlated with the total physical activity volume. In conclusion, our findings provide evidence support to the effectiveness of HD-tDCS on endogenous pain modulation among healthy adults. Further studies are required to explore the analgesic effect of tDCS among patients with chronic pain, thereby facilitating optimal chronic pain management.