Pain
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Spinal cord stimulation (SCS) has been suggested as a treatment option for patients with painful diabetic neuropathy (PDN). We conducted a systematic review and undertook a meta-analysis on individual patient data from randomised controlled trials (RCTs) to assess the effectiveness of SCS for the management of PDN. Electronic databases were searched from inception to May 2020 for RCTs of SCS for PDN. ⋯ Increases were observed for health-related quality of life assessed as EQ-5D utility score (pooled MD 0.16, 95% CI: 0.02-0.30) and visual analogue scale (pooled MD 11.21, 95% CI: 2.26-20.16). Our findings demonstrate that SCS is an effective therapeutic adjunct to best medical therapy in reducing pain intensity and improving health-related quality of life in patients with PDN. Large well-reported RCTs with long-term follow-up are required to confirm these results.
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Poor access to pediatric chronic pain care is a longstanding concern. The COVID-19 pandemic has necessitated virtual care delivery at an unprecedented pace and scale. We conducted a scoping review to create an interactive Evidence and Gap Map of virtual care solutions across a stepped care continuum (ie, from self-directed to specialist care) for youth with chronic pain and their families. ⋯ Evidence and Gap Maps are a novel visual knowledge synthesis tool, which enable rapid evidence-informed decision-making by patients and families, health professionals, and policymakers. This evidence and gap map identified high-quality virtual care solutions for immediate scale and spread and areas with no evidence in need of prioritization. Virtual care should address priorities identified by youth with chronic pain and their families.
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Chronic postsurgical pain (CPSP) affects an estimated 10% to 50% of adults depending on the type of surgical procedure. Clinical prediction models can help clinicians target preventive strategies towards patients at high risk for CPSP. Therefore, the objective of this systematic review was to identify and describe existing prediction models for CPSP in adults. ⋯ The most common predictors identified in final prediction models included preoperative pain in the surgical area, preoperative pain in other areas, age, sex or gender, and acute postsurgical pain. Clinical prediction models may support prevention and management of CPSP, but existing models are at high risk of bias that affects their reliability to inform practice and generalizability to wider populations. Adherence to standardized guidelines for clinical prediction model development is necessary to derive a prediction model of value to clinicians.