Articles: chronic.
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Observational Study
Prevalence, pain trajectories, and presurgical predictors for chronic postsurgical pain in a pediatric sample in Spain with a 24-month follow-up.
Pediatric chronic pain, particularly chronic postsurgical pain (CPSP), poses a significant public health challenge, impacting 20% of pediatric populations. While several presurgical predictors have been identified, there is a scarcity of data on long-term outcomes, especially beyond 1 to 2 years postsurgery. Previous research primarily focuses on North American children, creating gaps in understanding CPSP outcomes in diverse health systems, such as in Spain. ⋯ Group-based trajectory modeling revealed 3 postsurgical pain trajectories: Low Pain with Rapid Recovery Group (30.2%), Moderate Pain with Recovery Group (53.5%), and High Pain with Slow Recovery Group (16.3%), with group differences in presurgical predictors, excluding physical activity. This study contributes valuable insights into CPSP, emphasizing the need for long-term follow-up. The findings could inform the implementation of preventive programs for CPSP into diverse health systems.
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Chronic pain is a serious and prevalent condition that can affect many facets of life. However, uncertainty remains regarding the strength of the association between chronic pain and death and whether the association is causal. We investigate the pain-mortality relationship using data from 19,971 participants aged 51+ years in the 1998 wave of the U. ⋯ This attenuation highlights the role of confounders of the pain-mortality relationship as potentially modifiable upstream risk factors for mortality. Posing the depressive symptoms variable as a mediator rather than a confounder of the pain-mortality relationship resulted in stronger evidence of a modest causal effect of pain on mortality (eg, HR: 1.08, 95% CI: 1.01-1.15). Future work is required to model exposure-confounder feedback loops and investigate the potentially cumulative causal effect of chronic pain at multiple time points on mortality.
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Research has indicated that the default mode network (DMN) is perturbated in patients with chronic pain when compared with healthy controls, and this perturbation is correlated with the duration of pain during the chronic pain stage. It remains unclear whether DMN adaptations manifest during the subacute pain stage and progress over time because of the duration of pain experience, rather than being a specific correlate of the chronic pain stage. Furthermore, information regarding whether these adaptations are related to cognitive processes of adaptation is lacking. ⋯ This was significantly mediated by coping attitudes towards pain. Default mode network perturbation may thus reflect neural adaptation processes to pain experience rather than a single correlate of the chronic pain stage and be modulated by cognitive adaption. This points to potentially underinvestigated significant adaptation processes that could enable more fine-grained patient stratification.
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Using the Australiasian electronic Persistent Pain Outcomes Collaboration, a binational pain registry collecting standardized clinical data from paediatric ePPOC (PaedsePPOC) and adult pain services (AdultePPOC), we explored and characterized nationally representative chronic pain phenotypes and associations with clinical and sociodemographic factors, health care utilization, and medicine use of young people. Young people ≥15.0 and <25.0 years captured in PaedePPOC and AdultePPOC Australian data registry were included. Data from 68 adult and 12 paediatric pain services for a 5-year period January 2018 to December 2022 (first episode, including treatment information) were analysed. ⋯ From both services, 3 similar phenotypes emerged ("low," "moderate," "high"), characterized by an increasing symptom-severity gradient in multidimensional pain-related variables, showing meaningful differences across clinical and sociodemographic factors, health service utilization, and medicines use. Derived phenotypes point to the need for novel care models that differentially respond to the needs of distinct groups of young people, providing timely, targeted, age-appropriate care. To effectively scale such care, digital technologies can be leveraged to augment phenotype-informed clinical care.