Higher Preimplantation Opioid Doses Associated With Long‐Term Spinal Cord Stimulation Failure in 211 Patients With Failed Back Surgery Syndrome

ObjectiveSpinal cord stimulation (SCS) is an effective treatment in failed back surgery syndrome (FBSS). We studied the effect of preimplantation opioid use on SCS outcome and the effect of SCS on opioid use during a two-year follow-up period.Materials and methodsThe study cohort included 211 consecutive FBSS patients who underwent an SCS trial from January 1997 to March 2014. Participants were divided into groups, which were as follows: 1) SCS trial only (n = 47), 2) successful SCS (implanted and in use throughout the two-year follow-up period, n = 131), and 3) unsuccessful SCS (implanted but later explanted or revised due to inadequate pain relief, n = 29). Patients who underwent explantation for other reasons (n = 4) were excluded. Opioid purchase data from January 1995 to March 2016 were retrieved from national registries.ResultsHigher preimplantation opioid doses associated with unsuccessful SCS (ROC: AUC = 0.66, p = 0.009), with 35 morphine milligram equivalents (MME)/day as the optimal cutoff value. All opioids were discontinued in 23% of patients with successful SCS, but in none of the patients with unsuccessful SCS (p = 0.004). Strong opioids were discontinued in 39% of patients with successful SCS, but in none of the patients with unsuccessful SCS (p = 0.04). Mean opioid dose escalated from 18 ± 4 MME/day to 36 ± 6 MME/day with successful SCS and from 22 ± 8 MME/day to 82 ± 21 MME/day with unsuccessful SCS (p < 0.001).ConclusionsHigher preimplantation opioid doses were associated with SCS failure, suggesting the need for opioid tapering before implantation. With continuous SCS therapy and no explantation or revision due to inadequate pain relief, 39% of FBSS patients discontinued strong opioids, and 23% discontinued all opioids. This indicates that SCS should be considered before detrimental dose escalation.     

Überregionale Public-Health-Akteure in Deutschland – eine Bestandsaufnahme und Kategorisierung

Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz - Akteure der öffentlichen Gesundheit (Public Health) tragen wesentlich zu Gesundheitsschutz, -förderung und...     

Bone Microarchitecture Phenotypes Identified in Older Adults Are Associated With Different Levels of Osteoporotic Fracture Risk

Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).