Pain
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Factors contributing to development of complex regional pain syndrome (CRPS) are not fully understood. This study examined possible epigenetic mechanisms that may contribute to CRPS after traumatic injury. DNA methylation profiles were compared between individuals developing CRPS (n = 9) and those developing non-CRPS neuropathic pain (n = 38) after undergoing amputation following military trauma. ⋯ Analyses using PrediXcan methodology indicated differences in the genetically determined component of gene expression in 7 of 48 genes identified in methylation analyses (P's < 0.02). Results suggest that immune- and inflammatory-related factors might confer risk of developing CRPS after traumatic injury. Validation findings demonstrate the potential of using electronic health records linked to DNA for genomic studies of CRPS.
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Tobacco smoking is associated with adverse health effects, and its relationship to pain is complex. The longitudinal effect of smoking on patients attending a tertiary pain management center is not well established. Using the Collaborative Health Outcomes Information Registry of patients attending the Stanford Pain Management Center from 2013 to 2017, we conducted a propensity-weighted analysis to determine independent effects of smoking on patients with chronic pain. ⋯ Patients with chronic pain who smoke have worse pain, functional, sleep, and psychological and mood outcomes compared with nonsmokers. Smoking also has prognostic importance for poor recovery and improvement over time. Further research is needed on tailored therapies to assist people with chronic pain who smoke and to determine an optimal strategy to facilitate smoking cessation.
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In previous studies that examined the impact of attention biases (ABs) on later pain outcomes, reaction times (RTs) in response to brief stimulus presentations had been used as measures of attention. Consequently, little is known about effects of ABs assessed during presentations of cues or biases in prolonged attention towards pain stimuli as influences on subsequent functioning. ⋯ However, participants who gazed at injury images for longer durations during I-N trials reported significantly more pain and interference at follow-up than did peers who gazed at injury images for less time, even after the impact of other significant baseline predictors had been controlled. In sum, results provided initial evidence for gaze biases reflecting prolonged vigilance towards pain-related information as a potential risk factor for relative elevations in pain and interference from chronic pain.
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The incidence of persistent opioid use after lung surgery is high. Although adverse effects by opioids have been well described, it is unknown whether persistent opioid use is associated with worse survival. Patients who received a lobectomy for stage I NSCLC from 2007 to 2013 were identified from the Surveillance, Epidemiology and End Results-Medicare database. ⋯ However, the second and third quartiles of opioid use were associated with decreased overall survival (HR 1.53, 95% CI 1.14-2.03 and HR 1.39, 95% CI 1.04-1.86, respectively) that was nonetheless less severe than the highest quartile of opioid use (HR 2.50, 95% CI 1.95-3.21). Age, sex, marital status, comorbidity, tumor size, tumor grade, and radiation were also associated with worse overall survival, with chemotherapy use and video-assisted thoracoscopic surgery being associated with improved overall survival. Persistent opioid use 3 to 6 months after lobectomy is independently associated with worse overall survival and worse cancer-specific survival.
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Cancer and its surgical treatment are among the most important triggering events for persistent pain, but additional factors need to be present for the clinical manifestation, such as variants in pain-relevant genes. In a cohort of 140 women undergoing breast cancer surgery, assigned based on a 3-year follow-up to either a persistent or nonpersistent pain phenotype, next-generation sequencing was performed for 77 genes selected for known functional involvement in persistent pain. Applying machine-learning and item categorization techniques, 21 variants in 13 different genes were found to be relevant to the assignment of a patient to either the persistent pain or the nonpersistent pain phenotype group. ⋯ Supervised machine-learning-based classifiers, trained with 2/3 of the data, identified the correct pain phenotype group in the remaining 1/3 of the patients at accuracies and areas under the receiver operator characteristic curves of 65% to 72%. When using conservative classical statistical approaches, none of the variants passed α-corrected testing. The present data analysis approach, using machine learning and training artificial intelligences, provided biologically plausible results and outperformed classical approaches to genotype-phenotype association.