Pain Medicine最新文献

Objective: To identify common opioid tapering trajectories among patients commencing opioid taper from long-term opioid therapy for chronic non-cancer pain and to examine patient-level characteristics associated with these different trajectories.

Design: A retrospective cohort study.

Setting: Australian primary care.

Subjects: Patients prescribed opioid analgesics between 2015 and 2020.

Methods: Group-based trajectory modeling and multinomial logistic regression analysis were conducted to determine tapering trajectories and to examine demographic and clinical factors associated with the different trajectories.

Results: A total of 3369 patients commenced a taper from long-term opioid therapy. Six distinct opioid tapering trajectories were identified: low dose / completed taper (12.9%), medium dose / faster taper (12.2%), medium dose / gradual taper (6.5%), low dose / noncompleted taper (21.3%), medium dose / noncompleted taper (30.4%), and high dose / noncompleted taper (16.7%). A completed tapering trajectory from a high opioid dose was not identified. Among patients prescribed medium opioid doses, those who completed their taper were more likely to have higher geographically derived socioeconomic status (relative risk ratio [RRR], 1.067; 95% confidence interval [CI], 1.001-1.137) and less likely to have sleep disorders (RRR, 0.661; 95% CI, 0.463-0.945) than were those who didn't complete their taper. Patients who didn't complete their taper were more likely to be prescribed strong opioids (eg, morphine, oxycodone), regardless of whether they were tapered from low (RRR, 1.444; 95% CI, 1.138-1.831) or high (RRR, 1.344; 95% CI, 1.027-1.760) doses.

Conclusions: Those prescribed strong opioids and high doses appear to be less likely to complete tapering. Further studies are needed to evaluate the clinical outcomes associated with the identified trajectories.

Objective: Digital self-management programs are increasingly used in the management of osteoarthritis (OA). Little is known about heterogeneous patterns in response to these programs. We describe weekly pain trajectories of people with knee or hip OA over up to 52-week participation in a digital self-management program.

Methods: Observational cohort study among participants enrolled between January 2019 and September 2021 who participated at least 4 and up to 52 weeks in the program (n = 16 274). We measured pain using Numeric Rating Scale (NRS 0-10) and applied latent class growth analysis to identify classes with similar trajectories. Associations between baseline characteristics and trajectory classes were examined using multinomial logistic regression and dominance analysis.

Results: We identified 4 pain trajectory classes: "mild-largely improved" (30%), "low moderate-largely improved" (34%), "upper moderate-improved" (24%), and "severe-persistent" (12%). For classes with decreasing pain, the most pain reduction occurred during first 20 weeks and was stable thereafter. Male sex, older age, lower body mass index (BMI), better physical function, lower activity impairment, less anxiety/depression, higher education, knee OA, no walking difficulties, no wish for surgery and higher physical activity, all measured at enrolment, were associated with greater probabilities of membership in "mild-largely improved" class than other classes. Dominance analysis suggested that activity impairment followed by wish for surgery and walking difficulties were the most important predictors of trajectory class membership.

Conclusions: Our results highlight the importance of reaching people with OA for first-line treatment prior to developing severe pain, poor health status and a wish for surgery.