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.     

Subacute posttraumatic ascending myelopathy (SPAM): A potential complication of subarachnoid shunt for syringomyelia?

Context: Treatment of primary spinal syringomyelia is still controversial. Among others, shunting syrinx fluid to the subarachnoid, peritoneal or pleural space has been utilized with varying success. Shunt obstruction, migration, and infection represent the most common complications of these procedures.

Findings: The authors present the case of an 81-year-old woman who developed an unusual neurological deterioration resembling a subacute posttraumatic ascending myelopathy (SPAM) after the insertion of a syringosubarachnoid shunt for the treatment of slow-growing D10 syringomyelia.

Conclusion/Clinical Relevance: To date, no cases of SPAM secondary to the insertion of a syringosubarachnoid shunt for the treatment of syringomyelia have been reported. The potential pathogenesis related to this phenomenon is discussed.     

Impact of new technologies on diabetes care

Technologies for diabetes management, such as continuous subcutaneous insulin infusion (CSII) and continuous glucose monitoring (CGM) systems, have improved remarkably over the last decades. These developments are impacting the capacity to achieve recommended hemoglobin A1c levels and assisting in preventing the development and progression of micro- and macro vascular complications. While improvements in metabolic control and decreases in risk of severe and moderate hypoglycemia have been described with use of these technologies, large epidemiological international studies show that many patients are still unable to meet their glycemic goals, even when these technologies are used. This editorial will review the impact of technology on glycemic control, hypoglycemia and quality of life in children and youth with type 1 diabetes. Technologies reviewed include CSII, CGM systems and sensor-augmented insulin pumps. In addition, the usefulness of advanced functions such as bolus profiles, bolus calculators and threshold-suspend features will be also discussed. Moreover, the current editorial will explore the challenges of using these technologies. Indeed, despite the evidence currently available of the potential benefits of using advanced technologies in diabetes management, many patients still report barriers to using them. Finally this article will highlight the importance of future studies tailored toward overcome these barriers to optimizing glycemic control and avoiding severe hypoglycemia.     

The role of epsilon phenotype in brain glucose consumption in Alzheimer’s disease

The aim of our study was to investigate the impact of the epsilon phenotype in brain glucose consumption in a population with Alzheimer’s disease. Statistical Parametric Mapping (SPM8) was used to investigate differences in brain glucose consumption (as detectable by means of 18F FDG-PET/CT) in the population examined. A total of 129 patients (72 females and 57 males) with a diagnosis of probable AD according to the NINCDS-ADRDA criteria underwent the PET/CT examination. The mean (SD) age of the patients was 70 (± 7) years; the mean Mini-Mental State Examination was 19(± 5.6). 59 expressed epsilon 4 phenotype (E4) and 70 expressed the epsilon 3 phenotype (E3). Cerebral spinal fluid amyloid, tau, and t-tau have been measured resulting equal to 367.4 (± 149.1), 584.7 (± 312.1), and 79.2(± 45.9) pg/ml, respectively. Patients with confirmed amyloid and Tau changes were classified as AD. Patients with amyloid changes but negative Tau, considered as high risk of AD, were classified as IAD. Age, sex, MMSE, scholarship, and CSF parameters were used as a covariate in the SPM analyses. We did not find significant differences in age, gender, and MMSE and CSF parameters among groups. In the analysis of the AD group as compared to AD-E3, AD-E4 subjects show a significant reduction of brain glucose consumption in inferior frontal gyrus bilaterally (BA 45, BA 47). In the analysis of the IAD group as compared to IAD-E3, IAD-E4 subjects show a significant reduction of brain glucose consumption in right in medial, middle, and superior frontal gyrus (BA10, BA11), and in left medial and middle frontal gyrus (BA10, BA11). The differences between IAD-E3 and AD-E3 and between IAD-E4 and AD-E4 (and vice versa analysis) resulted not significant. APO-e4 is related to a major involvement of the frontal cortex confirming its role of risk factor in AD, while APO-3 seems not related to a specific pattern, supporting the hypothesis of neutral/protective role in AD.     

Reproducibility of Computerized Measurements of QT Interval from Multiple Leads at Rest and During Exercise

Background: Accurate measurement of the QT interval is important for diagnosing long QT syndrome (LQTS), and in research on determinants of ventricular repolarization time. We tested automatic analysis of QT intervals from multiple ECG leads on chest. Methods: Eleven healthy volunteers and 10 genotyped LQTS patients were tested at rest and during exercise with a bicycle ergometer twice 1–31 months apart. Electrocardiograms were recorded with the body surface potential mapping system, and 12 precordial channels were selected for analysis. Averaged QT peak and QT end intervals were determined with an automated algorithm, and the difference QT end minus QT peak (Tp‐e) was calculated. Repeatability was assessed by coefficient of variation (CV) between measurements. Results: Within one test at rest the QT end intervals were highly repeatable with CV 0.6%. In repeated tests CV was 4.4% for QT end interval and 3.5% when the QT interval was corrected for heart rate. In exercise test at specified heart rates, mean CV was 3.0% for QT end and 2.9% for QT peak interval. The CV of Tp‐e interval was 10.2% at rest, and 9.3% in exercise test. Reproducibility was comparable between healthy subjects and LQTS patients. Conclusions: The BSPM system with automated analysis produced accurate and highly repeatable QT interval measurements. Reproducibility was adequate also over prolonged time periods both at rest and in exercise stress test. The method can be applied in studying duration of ventricular repolarization time in different physiologic and pharmacologic interventions.