Pub Date : 2024-09-18DOI: 10.1101/2024.09.17.24313765
Evangelia Tsolaki, Wenxin Wei, Michael Ward, Ausaf Bari, Nader Pouratian
Background Chronic low back pain (CLBP) poses a significant challenge, contributing significantly to the ongoing opioid crisis while also being a leading cause of disability. Although spinal cord stimulation (SCS) stands as the primary FDA-endorsed method for neuromodulatory therapy in CLBP, there remains a subset of patients unresponsive to SCS and others who experience insufficient pain relief over time. In view of the evidence suggesting the critical role of subgenual cingulate cortex (SCC) connectivity in pain processing, in the current study we investigated the role of the baseline SCC structural as a potential neuroimaging predictive biomarker to identify patients that are likely to benefit from SCS. Methods Diffusion magnetic resonance imaging scans were acquired in 8 patients with CLBP (mean (SD) age = 70 (10) years; 6 female/2 male, 6 UCLA site, 2 UTSW) before their initial SCS trial. Probabilistic tractography from subject-specific anatomically defined SCC seed regions to the ventral striatum (VS), anterior cingulate cortex (ACC), uncinate fasciculus (UCF) and bilateral medial prefrontal cortex (mPFC) was used to calculate FSL structural probabilistic connectivity in the target network. To explore cross-sectional variations in SCC connectivity related to SCS trial response, we employed a general linear model (GLM) using the SCC probability of connectivity as dependent variable, and the response to the SCS trial as independent variable. We used Pearson correlation to evaluate further the relationships between the critical SCC probability of connectivity and the change in VAS score after the SCS trial. Finally, the role of depression in the treatment outcome was evaluated. Results Responders to SCS had significantly lower ipsilateral SCC connectivity to mPFC (F1,8 =8.19, p = 0.03) and VS (F1,8 =17.48, p=0.01) on the left hemisphere compared to non-responders. Pearson correlation analysis showed that decreased ipsilateral SCC baseline connectivity to left mPFC (p=0.03) and VS (p=0.01) was correlated with higher improvement in VAS scores. The baseline depression severity did not significantly influence the change in VAS score following the SCS trial. On the other hand, baseline SCC-VS connectivity on the left hemisphere was a significant predictor of change in VAS score (p=0.02). Conclusions Our study highlights the important role of SCC connectivity that can serve as a potential biomarker for CLBP stratification and prediction to SCS treatment. These results can reshape our perspective on CLBP management and can serve as early indicator of response to the treatment providing a personalized approach based on the individual's underlying SCC connectivity.
{"title":"Subcallosal Cingulate structural connectivity as a biomarker for chronic low back pain","authors":"Evangelia Tsolaki, Wenxin Wei, Michael Ward, Ausaf Bari, Nader Pouratian","doi":"10.1101/2024.09.17.24313765","DOIUrl":"https://doi.org/10.1101/2024.09.17.24313765","url":null,"abstract":"Background\u0000Chronic low back pain (CLBP) poses a significant challenge, contributing significantly to the ongoing opioid crisis while also being a leading cause of disability. Although spinal cord stimulation (SCS) stands as the primary FDA-endorsed method for neuromodulatory therapy in CLBP, there remains a subset of patients unresponsive to SCS and others who experience insufficient pain relief over time. In view of the evidence suggesting the critical role of subgenual cingulate cortex (SCC) connectivity in pain processing, in the current study we investigated the role of the baseline SCC structural as a potential neuroimaging predictive biomarker to identify patients that are likely to benefit from SCS. Methods\u0000Diffusion magnetic resonance imaging scans were acquired in 8 patients with CLBP (mean (SD) age = 70 (10) years; 6 female/2 male, 6 UCLA site, 2 UTSW) before their initial SCS trial. Probabilistic tractography from subject-specific anatomically defined SCC seed regions to the ventral striatum (VS), anterior cingulate cortex (ACC), uncinate fasciculus (UCF) and bilateral medial prefrontal cortex (mPFC) was used to calculate FSL structural probabilistic connectivity in the target network. To explore cross-sectional variations in SCC connectivity related to SCS trial response, we employed a general linear model (GLM) using the SCC probability of connectivity as dependent variable, and the response to the SCS trial as independent variable. We used Pearson correlation to evaluate further the relationships between the critical SCC probability of connectivity and the change in VAS score after the SCS trial. Finally, the role of depression in the treatment outcome was evaluated. Results\u0000Responders to SCS had significantly lower ipsilateral SCC connectivity to mPFC (F1,8 =8.19, p = 0.03) and VS (F1,8 =17.48, p=0.01) on the left hemisphere compared to non-responders. Pearson correlation analysis showed that decreased ipsilateral SCC baseline connectivity to left mPFC (p=0.03) and VS (p=0.01) was correlated with higher improvement in VAS scores. The baseline depression severity did not significantly influence the change in VAS score following the SCS trial. On the other hand, baseline SCC-VS connectivity on the left hemisphere was a significant predictor of change in VAS score (p=0.02). Conclusions\u0000Our study highlights the important role of SCC connectivity that can serve as a potential biomarker for CLBP stratification and prediction to SCS treatment. These results can reshape our perspective on CLBP management and can serve as early indicator of response to the treatment providing a personalized approach based on the individual's underlying SCC connectivity.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"45 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-09-16DOI: 10.1101/2024.09.15.24313716
Odelia Elkana, Iman Beheshti
Fibromyalgia (FM) is a chronic condition marked by widespread pain, fatigue, sleep problems, cognitive decline, and other symptoms. Despite extensive research, the pathophysiology of FM remains poorly understood, complicating diagnosis and treatment, which often relies on self-report questionnaires. This study explored structural and functional brain changes in women with FM, identified potential biomarkers, and examined their relationship with FM severity. MRI data from 33 female FM patients and 33 matched healthy controls were utilized, focusing on T1-weighted MRI and resting-state fMRI scans. Functional connectivity (FC) analysis was performed using a machine learning framework to differentiate FM patients from healthy controls and predict FM symptom severity. No significant differences were found in brain structural features, such as gray matter volume, white matter volume, deformation-based morphometry, and cortical thickness. However, significant differences in FC were observed between FM patients and healthy controls, particularly in the default mode network (DMN), somatomotor network (SMN), visual network (VIS), and dorsal attention network (DAN). The FC metrics were significantly associated with FM severity. Our prediction model differentiated FM patients from healthy controls with an area under the curve of 0.65. FC measures accurately estimated FM symptom severities with a significant correlation (r = 0.45, p = 0.007). Functional connections in the DMN, VIS, and DAN were crucial in determining FM severity. These findings suggest that integrating brain FC measurements could serve as valuable biomarkers for early detection of FM and predicting FM symptom severity, improving diagnostic accuracy and facilitating the development of targeted therapeutic strategies.
纤维肌痛（FM）是一种以广泛性疼痛、疲劳、睡眠问题、认知能力下降和其他症状为特征的慢性疾病。尽管进行了广泛的研究，但人们对 FM 的病理生理学仍然知之甚少，这使得诊断和治疗变得更加复杂，因为诊断和治疗通常依赖于自我报告问卷。本研究探讨了女性 FM 患者大脑结构和功能的变化，确定了潜在的生物标志物，并研究了它们与 FM 严重程度的关系。研究利用了 33 名女性 FM 患者和 33 名匹配的健康对照者的核磁共振成像数据，重点是 T1 加权核磁共振成像和静息态 fMRI 扫描。利用机器学习框架进行了功能连接（FC）分析，以区分 FM 患者和健康对照组，并预测 FM 症状的严重程度。在大脑结构特征（如灰质体积、白质体积、基于变形的形态测量和皮质厚度）方面未发现明显差异。然而，在FM患者和健康对照组之间观察到了明显的FC差异，尤其是在默认模式网络（DMN）、躯体运动网络（SMN）、视觉网络（VIS）和背侧注意网络（DAN）中。FC指标与FM的严重程度明显相关。我们的预测模型将 FM 患者与健康对照组区分开来，曲线下面积为 0.65。FC指标能准确估计FM症状的严重程度，并具有显著的相关性（r = 0.45，p = 0.007）。DMN、VIS和DAN的功能连接对确定FM的严重程度至关重要。这些研究结果表明，整合大脑FC测量可作为早期检测FM和预测FM症状严重程度的重要生物标志物，从而提高诊断的准确性，促进有针对性的治疗策略的开发。
{"title":"Women with fibromyalgia: Insights into behavioral and brain imaging","authors":"Odelia Elkana, Iman Beheshti","doi":"10.1101/2024.09.15.24313716","DOIUrl":"https://doi.org/10.1101/2024.09.15.24313716","url":null,"abstract":"Fibromyalgia (FM) is a chronic condition marked by widespread pain, fatigue, sleep problems, cognitive decline, and other symptoms. Despite extensive research, the pathophysiology of FM remains poorly understood, complicating diagnosis and treatment, which often relies on self-report questionnaires. This study explored structural and functional brain changes in women with FM, identified potential biomarkers, and examined their relationship with FM severity. MRI data from 33 female FM patients and 33 matched healthy controls were utilized, focusing on T1-weighted MRI and resting-state fMRI scans. Functional connectivity (FC) analysis was performed using a machine learning framework to differentiate FM patients from healthy controls and predict FM symptom severity. No significant differences were found in brain structural features, such as gray matter volume, white matter volume, deformation-based morphometry, and cortical thickness. However, significant differences in FC were observed between FM patients and healthy controls, particularly in the default mode network (DMN), somatomotor network (SMN), visual network (VIS), and dorsal attention network (DAN). The FC metrics were significantly associated with FM severity. Our prediction model differentiated FM patients from healthy controls with an area under the curve of 0.65. FC measures accurately estimated FM symptom severities with a significant correlation (r = 0.45, p = 0.007). Functional connections in the DMN, VIS, and DAN were crucial in determining FM severity. These findings suggest that integrating brain FC measurements could serve as valuable biomarkers for early detection of FM and predicting FM symptom severity, improving diagnostic accuracy and facilitating the development of targeted therapeutic strategies.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"208 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142262384","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-16DOI: 10.1101/2024.08.13.24311924
Paul W Hodges, Raimundo Sanchez, Shane Pritchard, Adam Turnbull, Andrew Hahne, Jon Ford
The International Association for the Study of Pain defines three pain types presumed to involve different mechanisms - nociceptive, neuropathic and nociplastic. Based on the hypothesis that these pain types should guide matching of patients with treatments, work has been undertaken to identify features to discriminate between them for clinical use. This study aimed to evaluate the validity of these features to discriminate between pain types. Subjective and physical features were evaluated in a cohort of 350 individuals with chronic musculoskeletal pain attending a chronic pain management program. Analysis tested the hypothesis that, if the features nominated for each pain type represent 3 different groups, then (i) cluster analysis should identify 3 main clusters of patients, (ii) these clusters should align with the pain type allocated by an experienced clinician, (iii) patients within a cluster should have high expression of the candidate features proposed to assist identification of that pain type. Supervised machine learning interrogated features with the greatest and least importance for discrimination; and probabilistic analysis probed the potential for coexistence of multiple pain types. Results confirmed that data could be best explained by 3 clusters, clusters were characterized by a priori specified features, and agreed with the designation of the experienced clinical with 82% accuracy. Supervised analysis highlighted features that contributed most and least to the classification of pain type and probabilistic analysis reinforced the presence of mixed pain types. These findings support the foundation for further refinement of a clinical tool to discriminate between pain types.
国际疼痛研究协会（International Association for the Study of Pain）定义了三种假定涉及不同机制的疼痛类型--痛觉性疼痛、神经性疼痛和神经痉挛性疼痛。基于这些疼痛类型应能指导患者进行匹配治疗的假设，人们已着手确定这些类型的特征，以便在临床上使用。本研究旨在评估这些特征在区分疼痛类型方面的有效性。研究人员对参加慢性疼痛管理项目的 350 名慢性肌肉骨骼疼痛患者的主观和身体特征进行了评估。分析检验了以下假设：如果为每种疼痛类型提名的特征代表 3 个不同的群体，那么（i）聚类分析应能识别出 3 个主要的患者群组；（ii）这些群组应与经验丰富的临床医师分配的疼痛类型一致；（iii）群组内的患者应具有较高的候选特征表达，以帮助识别该疼痛类型。有监督的机器学习分析了对识别最重要和最不重要的特征；概率分析探究了多种疼痛类型共存的可能性。结果证实，数据可以用 3 个群组进行最佳解释，群组的特征是先验指定的特征，与经验丰富的临床医生的指定一致，准确率为 82%。监督分析突出了对疼痛类型分类贡献最大和最小的特征，而概率分析则强化了混合疼痛类型的存在。这些发现为进一步完善临床工具以区分疼痛类型奠定了基础。
{"title":"Towards validation of clinical measures to discriminate between nociceptive, neuropathic and nociplastic pain: cluster analysis of a cohort with chronic musculoskeletal pain","authors":"Paul W Hodges, Raimundo Sanchez, Shane Pritchard, Adam Turnbull, Andrew Hahne, Jon Ford","doi":"10.1101/2024.08.13.24311924","DOIUrl":"https://doi.org/10.1101/2024.08.13.24311924","url":null,"abstract":"The International Association for the Study of Pain defines three pain types presumed to involve different mechanisms - nociceptive, neuropathic and nociplastic. Based on the hypothesis that these pain types should guide matching of patients with treatments, work has been undertaken to identify features to discriminate between them for clinical use. This study aimed to evaluate the validity of these features to discriminate between pain types. Subjective and physical features were evaluated in a cohort of 350 individuals with chronic musculoskeletal pain attending a chronic pain management program. Analysis tested the hypothesis that, if the features nominated for each pain type represent 3 different groups, then (i) cluster analysis should identify 3 main clusters of patients, (ii) these clusters should align with the pain type allocated by an experienced clinician, (iii) patients within a cluster should have high expression of the candidate features proposed to assist identification of that pain type. Supervised machine learning interrogated features with the greatest and least importance for discrimination; and probabilistic analysis probed the potential for coexistence of multiple pain types. Results confirmed that data could be best explained by 3 clusters, clusters were characterized by a priori specified features, and agreed with the designation of the experienced clinical with 82% accuracy. Supervised analysis highlighted features that contributed most and least to the classification of pain type and probabilistic analysis reinforced the presence of mixed pain types. These findings support the foundation for further refinement of a clinical tool to discriminate between pain types.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"116 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142175734","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-06DOI: 10.1101/2024.08.05.24310944
Ho-Ching Yang, Tyler Nguyen, Fletcher A White, Kelly M Naugle, Yu-Chien Wu
Post-traumatic headache (PTH) is a common consequence of mild traumatic brain injury (mTBI), significantly impacting an individual's quality of life and rehabilitation. However, the underlying neuropathogenesis of PTH remains poorly understood. This study utilized diffusion tensor imaging (DTI) to detect microstructural brain alterations in mTBI participants with or at risk of developing PTH. The current study investigated associations between early DTI metrics (1-month postinjury), pain sensitivity (quantitative sensory tests), and psychological assessments (1-month and 6-months postinjury) to identify differences between mTBI (n=12) and healthy controls (HC; n=10). Abnormalities in mean axial diffusivity in the forceps major were observed in mTBI relative to HCs at 1-month postinjury (p=0.02). Within the mTBI group, DTI metrics at 1-month postinjury were significantly associated (p<0.05) with pain-related measures and psychological outcomes at 6-months postinjury. Notably, the associations between early DTI metrics and later pain-related measures exhibited significant group differences in right sagittal stratum (p<0.01), white matter tract in left insula (p<0.04), and left superior longitudinal fasciculus (p<0.05). In conclusion, these findings indicate that DTI metrics can be used to predict pain and psychological measures in mTBI, suggesting an important role of white matter microstructure in PTH following mTBI.
{"title":"Pain-related white-matter changes following mild traumatic brain injury: A longitudinal diffusion tensor imaging pilot study","authors":"Ho-Ching Yang, Tyler Nguyen, Fletcher A White, Kelly M Naugle, Yu-Chien Wu","doi":"10.1101/2024.08.05.24310944","DOIUrl":"https://doi.org/10.1101/2024.08.05.24310944","url":null,"abstract":"Post-traumatic headache (PTH) is a common consequence of mild traumatic brain injury (mTBI), significantly impacting an\u0000individual's quality of life and rehabilitation. However, the underlying neuropathogenesis of PTH remains poorly understood. This\u0000study utilized diffusion tensor imaging (DTI) to detect microstructural brain alterations in mTBI participants with or at risk of\u0000developing PTH. The current study investigated associations between early DTI metrics (1-month postinjury), pain sensitivity\u0000(quantitative sensory tests), and psychological assessments (1-month and 6-months postinjury) to identify differences between mTBI\u0000(n=12) and healthy controls (HC; n=10). Abnormalities in mean axial diffusivity in the forceps major were observed in mTBI relative\u0000to HCs at 1-month postinjury (p=0.02). Within the mTBI group, DTI metrics at 1-month postinjury were significantly associated\u0000(p<0.05) with pain-related measures and psychological outcomes at 6-months postinjury. Notably, the associations between early\u0000DTI metrics and later pain-related measures exhibited significant group differences in right sagittal stratum (p<0.01), white\u0000matter tract in left insula (p<0.04), and left superior longitudinal fasciculus (p<0.05). In conclusion, these findings indicate that DTI\u0000metrics can be used to predict pain and psychological measures in mTBI, suggesting an important role of white matter\u0000microstructure in PTH following mTBI.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"46 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141942631","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-08-01DOI: 10.1101/2024.07.14.24310378
Julian Y. V. Borges
Abstract Background and Objectives: As the medical community seeks alternative pain management strategies, cannabinoids have emerged as a potential option. This review discusses the role of cannabinoids in chronic pain management and their potential as an alternative treatment in pain medicine, focusing on efficacy, safety, and possible opioid reduction. The objectives are to evaluate the efficacy and safety of cannabinoids in chronic pain management, explore their potential to reduce opioid use, and identify the mechanisms by which cannabinoids exert their analgesic effects. Additionally, the review seeks to highlight the clinical implications and limitations of using cannabinoids as an alternative to opioids. Methods: A comprehensive literature review and meta-analysis were conducted, focusing on studies from PubMed, MEDLINE, and Cochrane, focusing on various types of studies. Data were extracted and analyzed to assess the efficacy, safety, and potential opioid-sparing effects of cannabinoids. Mechanistic insights were also explored to understand how cannabinoids modulate pain. Results: Cannabinoids have shown efficacy in managing chronic pain, with evidence indicating their ability to reduce pain and improve quality of life. Studies suggest that cannabinoids can provide significant analgesic effects, although there is variability in efficacy across trials. Findings also show that Cannabinoids modulate pain through the endocannabinoid system, which plays a crucial role in pain perception and inflammation. Limitations: The variability in efficacy across studies suggests a need for standardized formulations and dosing regimens. Long-term effects of cannabinoid use are not fully understood, necessitating further research. More high-quality trials are needed to confirm findings and address potential biases. Conclusion: Cannabinoids offer a promising alternative for chronic pain management, with the potential to mitigate the opioid epidemic. Integrating cannabinoids into clinical practice, guided by evidence-based protocols, can provide a safer and effective approach to chronic pain management. Keywords: Opioid Epidemic, Chronic Pain Management, Cannabinoids, Medical Cannabis, Pain Relief, Opioid-Sparing Effects, Endocannabinoid System, Clinical Practice, Analgesia, Alternative Therapies
{"title":"Mitigating the Opioid Epidemic: The Role of Cannabinoids in Chronic Pain Management - A Systematic Review and Meta-Analysis of Clinical Evidence and Mechanisms","authors":"Julian Y. V. Borges","doi":"10.1101/2024.07.14.24310378","DOIUrl":"https://doi.org/10.1101/2024.07.14.24310378","url":null,"abstract":"Abstract\u0000Background and Objectives: As the medical community seeks alternative pain management strategies, cannabinoids have emerged as a potential option. This review discusses the role of cannabinoids in chronic pain management and their potential as an alternative treatment in pain medicine, focusing on efficacy, safety, and possible opioid reduction. The objectives are to evaluate the efficacy and safety of cannabinoids in chronic pain management, explore their potential to reduce opioid use, and identify the mechanisms by which cannabinoids exert their analgesic effects. Additionally, the review seeks to highlight the clinical implications and limitations of using cannabinoids as an alternative to opioids. Methods: A comprehensive literature review and meta-analysis were conducted, focusing on studies from PubMed, MEDLINE, and Cochrane, focusing on various types of studies. Data were extracted and analyzed to assess the efficacy, safety, and potential opioid-sparing effects of cannabinoids. Mechanistic insights were also explored to understand how cannabinoids modulate pain. Results: Cannabinoids have shown efficacy in managing chronic pain, with evidence indicating their ability to reduce pain and improve quality of life. Studies suggest that cannabinoids can provide significant analgesic effects, although there is variability in efficacy across trials. Findings also show that Cannabinoids modulate pain through the endocannabinoid system, which plays a crucial role in pain perception and inflammation. Limitations: The variability in efficacy across studies suggests a need for standardized formulations and dosing regimens. Long-term effects of cannabinoid use are not fully understood, necessitating further research. More high-quality trials are needed to confirm findings and address potential biases. Conclusion: Cannabinoids offer a promising alternative for chronic pain management, with the potential to mitigate the opioid epidemic. Integrating cannabinoids into clinical practice, guided by evidence-based protocols, can provide a safer and effective approach to chronic pain management.\u0000Keywords: Opioid Epidemic, Chronic Pain Management, Cannabinoids, Medical Cannabis, Pain Relief, Opioid-Sparing Effects, Endocannabinoid System, Clinical Practice, Analgesia, Alternative Therapies","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"194 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863805","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.1101/2024.07.25.24311008
Anna Ware, Terri Blumke, Peter J Hoover, Zachary P Veigulis, Jacqueline M Ferguson, Malvika Pillai, Thomas Osborne
Background: The intrauterine device (IUD) is a highly effective form of long-acting reversible contraception, widely recognized for its convenience and efficacy. Despite its benefits, many patients report moderate to severe pain during and after their IUD insertion procedure. Furthermore, reports suggest significant variability in pain control medications, including no adequate pain medication. The aim of this evaluation was to assess the pharmaceutical pain medication types, proportions, and trends related to IUD insertion procedures within the Veterans Health Administration (VHA). Methods: IUD insertion procedures documented in the VA electronic health record were assessed from 1/1/2018 to 10/13/2023. Descriptive statistics described patient and facility characteristics while annual trends were assessed using linear regression. Results: Out of the 28,717 procedures captured, only 11.4% had any form of prescribed pain medication identified. Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) were the most frequently prescribed pain medication category (8.3%), with ibuprofen being the most common pain medication overall (6.1%). Over the assessment period, there was an average annual increase of 0.52% (p=0.038) of procedures with prescribed pain medication, increasing from 10.3% in 2018 to 13.3% in 2023. Conclusions: Although IUD insertion procedures have been seeing an increase in prescribed pain medication, the overall proportion remains disproportionality low relative to the pain experienced. Additionally, when pain interventions were initiated, they disproportionally utilized medication that have been shown to be ineffective. The intent of the work is that the information will help guide data driven pain medication strategies for patients undergoing IUD insertion procedures within the VHA.
{"title":"National Assessment on the Frequency of Pain Medication Prescribed for Intrauterine Device Insertion Procedures within the Veterans Affairs Health Care System","authors":"Anna Ware, Terri Blumke, Peter J Hoover, Zachary P Veigulis, Jacqueline M Ferguson, Malvika Pillai, Thomas Osborne","doi":"10.1101/2024.07.25.24311008","DOIUrl":"https://doi.org/10.1101/2024.07.25.24311008","url":null,"abstract":"Background: The intrauterine device (IUD) is a highly effective form of long-acting reversible contraception, widely recognized for its convenience and efficacy. Despite its benefits, many patients report moderate to severe pain during and after their IUD insertion procedure. Furthermore, reports suggest significant variability in pain control medications, including no adequate pain medication. The aim of this evaluation was to assess the pharmaceutical pain medication types, proportions, and trends related to IUD insertion procedures within the Veterans Health Administration (VHA).\u0000Methods: IUD insertion procedures documented in the VA electronic health record were assessed from 1/1/2018 to 10/13/2023. Descriptive statistics described patient and facility characteristics while annual trends were assessed using linear regression.\u0000Results: Out of the 28,717 procedures captured, only 11.4% had any form of prescribed pain medication identified. Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) were the most frequently prescribed pain medication category (8.3%), with ibuprofen being the most common pain medication overall (6.1%). Over the assessment period, there was an average annual increase of 0.52% (p=0.038) of procedures with prescribed pain medication, increasing from 10.3% in 2018 to 13.3% in 2023.\u0000Conclusions: Although IUD insertion procedures have been seeing an increase in prescribed pain medication, the overall proportion remains disproportionality low relative to the pain experienced. Additionally, when pain interventions were initiated, they disproportionally utilized medication that have been shown to be ineffective. The intent of the work is that the information will help guide data driven pain medication strategies for patients undergoing IUD insertion procedures within the VHA.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141780838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1101/2024.07.10.24310234
Omar Khoja, Matthew Mulvey, Sarah Astill, Ai Lyn Tan, Manoj Sivan
Background: New-onset chronic musculoskeletal (MSK) pain (> 3 months duration) is one of the commonest persistent symptoms of Post-COVID syndrome (PCS). There is emerging evidence that the chronic MSK pain and associated symptoms in PCS have similarities to Fibromyalgia Syndrome (FMS). This study aimed to characterise PCS related new-onset chronic MSK pain and its overlap with Fibromyalgia Syndrome (FMS). Methods: Patients with new-onset chronic MSK pain following COVID-19 infection were enrolled and the nature of pain and associated symptoms captured using the C19-YRS (Yorkshire Rehabilitation Scale). FMS assessment was conducted as part of standard clinical examination using the American College of Rheumatology (ACR) 2010 criteria. Diagnosis of FMS was made when they meet the standard criteria of (1) Widespread Pain Index (WPI) ≥ 7 and Symptoms Severity (SS) score ≥ 5, or WPI is 3-6 and SS score ≥ 9, (2) symptoms have been present at a similar level for at least 3 months, and (3) the patient does not have a disorder that would otherwise explain the symptoms. Results: Eighteen patients, twelve of whom were female, with an average age of 49.6 (SD 11.8) years and a Body Mass Index of 31.7 (SD 8.6) were enrolled. The average duration of symptoms from COVID-19 infection to assessment was 27.9 (SD 6.97) months. The new-onset chronic pain was widespread, primarily manifesting as muscle pain. Thirteen (72.2%) patients met the diagnostic criteria for FMS, with an average WPI score of 8.8 and an average SS score of 8.2, indicating a high level of pain and significant adverse impact on their quality of life. Conclusion: The study found that 72.2% of the patients with new-onset chronic MSK pain following COVID-19 infection met the criteria for FMS. These findings support the hypothesis that FMS may develop as a long-term sequela of a viral infection, underscoring the need for further research into post-viral long-term conditions.
{"title":"New-onset chronic musculoskeletal pain following COVID-19 infection fulfil the Fibromyalgia clinical syndrome criteria","authors":"Omar Khoja, Matthew Mulvey, Sarah Astill, Ai Lyn Tan, Manoj Sivan","doi":"10.1101/2024.07.10.24310234","DOIUrl":"https://doi.org/10.1101/2024.07.10.24310234","url":null,"abstract":"Background: New-onset chronic musculoskeletal (MSK) pain (> 3 months duration) is one of the commonest persistent symptoms of Post-COVID syndrome (PCS). There is emerging evidence that the chronic MSK pain and associated symptoms in PCS have similarities to Fibromyalgia Syndrome (FMS). This study aimed to characterise PCS related new-onset chronic MSK pain and its overlap with Fibromyalgia Syndrome (FMS). Methods: Patients with new-onset chronic MSK pain following COVID-19 infection were enrolled and the nature of pain and associated symptoms captured using the C19-YRS (Yorkshire Rehabilitation Scale). FMS assessment was conducted as part of standard clinical examination using the American College of Rheumatology (ACR) 2010 criteria. Diagnosis of FMS was made when they meet the standard criteria of (1) Widespread Pain Index (WPI) ≥ 7 and Symptoms Severity (SS) score ≥ 5, or WPI is 3-6 and SS score ≥ 9, (2) symptoms have been present at a similar level for at least 3 months, and (3) the patient does not have a disorder that would otherwise explain the symptoms.\u0000Results: Eighteen patients, twelve of whom were female, with an average age of 49.6 (SD 11.8) years and a Body Mass Index of 31.7 (SD 8.6) were enrolled. The average duration of symptoms from COVID-19 infection to assessment was 27.9 (SD 6.97) months. The new-onset chronic pain was widespread, primarily manifesting as muscle pain. Thirteen (72.2%) patients met the diagnostic criteria for FMS, with an average WPI score of 8.8 and an average SS score of 8.2, indicating a high level of pain and significant adverse impact on their quality of life.\u0000Conclusion: The study found that 72.2% of the patients with new-onset chronic MSK pain following COVID-19 infection met the criteria for FMS. These findings support the hypothesis that FMS may develop as a long-term sequela of a viral infection, underscoring the need for further research into post-viral long-term conditions.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"36 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141610824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.1101/2024.07.04.24309933
Daniel Segelcke, Julia R Sondermann, Christin Kappert, Bruno Pradier, Dennis Goerlich, Manfred Fobker, Jan Vollert, Peter K. Zahn, Manuela Schmidt, Esther M. Pogatzki-Zahn
Personalized strategies in pain management and prevention should be based on individual risk factors as early as possible, but the factors most relevant are not yet known. An innovative approach would be to integrate multi-modal risk factors, including blood proteomics, in predicting high pain responders and using them as targets for personalized treatment options. Here, we determined and mapped multi-modal factors to prognosticate a phenotype with high risk of developing pain and hyperalgesia after an experimental incision in humans. We profiled unbiased blood plasma proteome signature of 26 male volunteers, assessed psychophysical and psychological aspects before incision injury. Outcome measures were pain intensity ratings and the extent of the area of hyperalgesia to mechanical stimuli surrounding the incision as a proxy for central sensitization. Phenotype-based stratification resulted in the identification of low- and high-responders for the two different outcome measures. Logistic regression analysis revealed prognostic potential for blood plasma proteins and for psychophysical and psychological parameters. The combination of certain parameters increased the prognostic accuracy for both outcome measures, exceeding 97%. In high-responders, term-term-interaction network analysis showed a proteome signature of a low-grade inflammation reaction. Intriguingly, in silico drug repurposing indicates a high potential for specific antidiabetic and anti-inflammatory drugs already available. In conclusion, we show an integrated pipeline that provides a valuable resource for patient stratification and the identification of (i) multi-feature prognostic models, (ii) treatment targets, and (iii) mechanistic correlates that may be relevant for individualized management of pain and its long-term consequences.
{"title":"BLOOD PROTEOMICS AND PAIN - A TRANSLATIONAL STUDY TO PROGNOSTICATE PAIN PHENOTYPES AND ASSESS NEW BIOMARKERS FOR PREVENTING PAIN IN HUMANS","authors":"Daniel Segelcke, Julia R Sondermann, Christin Kappert, Bruno Pradier, Dennis Goerlich, Manfred Fobker, Jan Vollert, Peter K. Zahn, Manuela Schmidt, Esther M. Pogatzki-Zahn","doi":"10.1101/2024.07.04.24309933","DOIUrl":"https://doi.org/10.1101/2024.07.04.24309933","url":null,"abstract":"Personalized strategies in pain management and prevention should be based on individual risk factors as early as possible, but the factors most relevant are not yet known. An innovative approach would be to integrate multi-modal risk factors, including blood proteomics, in predicting high pain responders and using them as targets for personalized treatment options. Here, we determined and mapped multi-modal factors to prognosticate a phenotype with high risk of developing pain and hyperalgesia after an experimental incision in humans. We profiled unbiased blood plasma proteome signature of 26 male volunteers, assessed psychophysical and psychological aspects before incision injury. Outcome measures were pain intensity ratings and the extent of the area of hyperalgesia to mechanical stimuli surrounding the incision as a proxy for central sensitization. Phenotype-based stratification resulted in the identification of low- and high-responders for the two different outcome measures. Logistic regression analysis revealed prognostic potential for blood plasma proteins and for psychophysical and psychological parameters. The combination of certain parameters increased the prognostic accuracy for both outcome measures, exceeding 97%. In high-responders, term-term-interaction network analysis showed a proteome signature of a low-grade inflammation reaction. Intriguingly, in silico drug repurposing indicates a high potential for specific antidiabetic and anti-inflammatory drugs already available. In conclusion, we show an integrated pipeline that provides a valuable resource for patient stratification and the identification of (i) multi-feature prognostic models, (ii) treatment targets, and (iii) mechanistic correlates that may be relevant for individualized management of pain and its long-term consequences.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"26 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.1101/2024.07.02.24309693
Chris Djurtoft, Edel O'Hagan, Monika Deleuran Laursen, Lars Lejbølle, Mia Bisgaard Jensen, Simon Kristoffer Johansen, Kristian Damgaard Lyng, Morten Hoegh, Negar Pourbordbari, Malene Kjær Bruun, Bettina Eiger, Jesper Bie Larsen, Michael Skovdal Rathleff
Introduction: Low back pain is a global health challenge with negative consequences for both individuals and healthcare systems. The 'Choosing Wisely' initiative aims to improve communication between patients and clinicians to promote informed healthcare decisions while avoiding unnecessary tests and treatments. The objective of this project is to co-create an information resource in the form of a leaflet, to be distributed in clinical settings, websites or social media targeting people with low back pain. Methods: This multi-method study was conducted in four stages: literature search, input from practice consultants, program theory development, and think-aloud interviews with people experiencing low back pain. Each stage was followed by a consensus meeting in which the steering group refined the leaflet based on the emerging knowledge. Results: The literature search highlighting patients' need for understandable information about diagnosis, treatment options, and self-management strategies. Practice consultants emphasized concise, relatable content. The program theory identified potential mechanisms and design targets for content creation, development, and implementation of the leaflet, such as addressing patient concerns, reducing diagnostic uncertainty, offering insights into management options, and validation. Think-aloud interviews with 18 people living with low back pain informed the iteration of the leaflet, enhancing language clarification and content comprehension. Conclusion: We co-created a new Choosing Wisely leaflet, created with end-users in mind, specifically focused on reducing unnecessary imaging for low back pain. Valuable feedback from end-users prompted significant revisions, underscoring the importance of involving multiple end-user viewpoints into the creation process.
{"title":"Co-creating a Choosing Wisely Leaflet Supporting the Reduction of Imaging Usage in Low Back Pain Management - A Multi-Method Study.","authors":"Chris Djurtoft, Edel O'Hagan, Monika Deleuran Laursen, Lars Lejbølle, Mia Bisgaard Jensen, Simon Kristoffer Johansen, Kristian Damgaard Lyng, Morten Hoegh, Negar Pourbordbari, Malene Kjær Bruun, Bettina Eiger, Jesper Bie Larsen, Michael Skovdal Rathleff","doi":"10.1101/2024.07.02.24309693","DOIUrl":"https://doi.org/10.1101/2024.07.02.24309693","url":null,"abstract":"Introduction: Low back pain is a global health challenge with negative consequences for both individuals and healthcare systems. The 'Choosing Wisely' initiative aims to improve communication between patients and clinicians to promote informed healthcare decisions while avoiding unnecessary tests and treatments. The objective of this project is to co-create an information resource in the form of a leaflet, to be distributed in clinical settings, websites or social media targeting people with low back pain. Methods: This multi-method study was conducted in four stages: literature search, input from practice consultants, program theory development, and think-aloud interviews with people experiencing low back pain. Each stage was followed by a consensus meeting in which the steering group refined the leaflet based on the emerging knowledge. Results: The literature search highlighting patients' need for understandable information about diagnosis, treatment options, and self-management strategies. Practice consultants emphasized concise, relatable content. The program theory identified potential mechanisms and design targets for content creation, development, and implementation of the leaflet, such as addressing patient concerns, reducing diagnostic uncertainty, offering insights into management options, and validation. Think-aloud interviews with 18 people living with low back pain informed the iteration of the leaflet, enhancing language clarification and content comprehension. Conclusion: We co-created a new Choosing Wisely leaflet, created with end-users in mind, specifically focused on reducing unnecessary imaging for low back pain. Valuable feedback from end-users prompted significant revisions, underscoring the importance of involving multiple end-user viewpoints into the creation process.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"87 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570106","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.1101/2024.07.03.24309700
Pradeep Suri, Yakov A Tsepilov, Elizaveta E. Elgaeva, Frances MK Williams, Maxim Freydin, Ian Stanaway
Objective: We conducted a Mendelian randomization (MR) study to examine causal associations of C-reactive protein (CRP) with (1) spinal pain; (2) extent of multisite chronic pain; and (3) chronic widespread musculoskeletal pain. Design: Two-sample MR study. Setting/Subjects: We used summary statistics from publicly available genome-wide association studies (GWAS) conducted in multiple cohorts and biobanks. Genetic instrumental variables were taken from an exposure GWAS of CRP (n=204,402). Outcome GWASs examined spinal pain (n=1,028,947), extent of multisite chronic pain defined as the number of locations with chronic pain (n=387,649), and chronic widespread pain (n=249,843). Methods: We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis and sensitivity analyses using other methods. We calculated odds ratios (ORs), 95% confidence intervals (95% CIs), and p-values, using a Bonferroni correction (p<0.0166) to account for 3 primary comparisons. Results: Greater serum CRP (mg/L) was not significantly causally associated with spinal pain (OR=1.04, 95% CI 1.00-1.08; p=0.07) in IVW analysis. Greater serum CRP also showed no significant causal association with extent of multisite chronic pain in IVW analysis (beta coefficient= 0.014, standard error=0.011; p=0.19). CRP also showed no significant causal association with chronic widespread pain in IVW analysis (OR=1.00, 95% CI 1.00-1.00; p=0.75). All secondary and sensitivity analyses also showed no significant associations. Conclusions: This MR study found no causal association of CRP on spinal pain, the extent of chronic pain, or chronic widespread pain. Future studies examining mechanistic biomarkers for pain conditions should consider other candidates besides CRP.
研究目的我们进行了一项孟德尔随机化（MR）研究，以探讨 C 反应蛋白（CRP）与（1）脊柱疼痛；（2）多部位慢性疼痛程度；以及（3）慢性广泛性肌肉骨骼疼痛之间的因果关系。设计：双样本 MR 研究。设置/受试者：我们使用了在多个队列和生物库中进行的公开全基因组关联研究（GWAS）的汇总统计数据。遗传工具变量来自 CRP 的暴露 GWAS（n=204,402）。结果 GWAS 研究了脊柱疼痛（n=1,028,947）、多部位慢性疼痛程度（定义为慢性疼痛部位的数量）（n=387,649）和慢性广泛性疼痛（n=249,843）。方法：我们使用逆方差加权（IVW）分析和其他方法进行敏感性分析，检查了 MR 的因果关系证据。我们计算了几率比（ORs）、95% 置信区间（95% CIs）和 p 值，并使用 Bonferroni 校正（p<0.0166）以考虑 3 个主要比较。结果在 IVW 分析中，较高的血清 CRP（毫克/升）与脊柱疼痛无明显因果关系（OR=1.04，95% CI 1.00-1.08；p=0.07）。在 IVW 分析中，更高的血清 CRP 与多部位慢性疼痛的程度也没有明显的因果关系（β 系数= 0.014，标准误差=0.011；P=0.19）。在 IVW 分析中，CRP 与慢性广泛性疼痛也没有明显的因果关系（OR=1.00，95% CI 1.00-1.00；P=0.75）。所有次级分析和敏感性分析也未显示出明显的关联性。结论：这项磁共振研究发现 CRP 与脊柱疼痛、慢性疼痛程度或慢性广泛性疼痛没有因果关系。未来研究疼痛状况的机理生物标志物时，应考虑 CRP 以外的其他候选指标。
{"title":"No evidence for causal effects of C-reactive protein (CRP) on chronic pain conditions: a Mendelian randomization study","authors":"Pradeep Suri, Yakov A Tsepilov, Elizaveta E. Elgaeva, Frances MK Williams, Maxim Freydin, Ian Stanaway","doi":"10.1101/2024.07.03.24309700","DOIUrl":"https://doi.org/10.1101/2024.07.03.24309700","url":null,"abstract":"Objective: We conducted a Mendelian randomization (MR) study to examine causal associations of C-reactive protein (CRP) with (1) spinal pain; (2) extent of multisite chronic pain; and (3) chronic widespread musculoskeletal pain. Design: Two-sample MR study. Setting/Subjects: We used summary statistics from publicly available genome-wide association studies (GWAS) conducted in multiple cohorts and biobanks. Genetic instrumental variables were taken from an exposure GWAS of CRP (n=204,402). Outcome GWASs examined spinal pain (n=1,028,947), extent of multisite chronic pain defined as the number of locations with chronic pain (n=387,649), and chronic widespread pain (n=249,843). Methods: We examined MR evidence for causal associations using inverse-variance weighted (IVW) analysis and sensitivity analyses using other methods. We calculated odds ratios (ORs), 95% confidence intervals (95% CIs), and p-values, using a Bonferroni correction (p<0.0166) to account for 3 primary comparisons. Results: Greater serum CRP (mg/L) was not significantly causally associated with spinal pain (OR=1.04, 95% CI 1.00-1.08; p=0.07) in IVW analysis. Greater serum CRP also showed no significant causal association with extent of multisite chronic pain in IVW analysis (beta coefficient= 0.014, standard error=0.011; p=0.19). CRP also showed no significant causal association with chronic widespread pain in IVW analysis (OR=1.00, 95% CI 1.00-1.00; p=0.75). All secondary and sensitivity analyses also showed no significant associations. Conclusions: This MR study found no causal association of CRP on spinal pain, the extent of chronic pain, or chronic widespread pain. Future studies examining mechanistic biomarkers for pain conditions should consider other candidates besides CRP.","PeriodicalId":501393,"journal":{"name":"medRxiv - Pain Medicine","volume":"64 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141570105","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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