Impact of Spinal Cord Stimulation on Opioid Dose Reduction: A Nationwide Analysis

Neurosurgery ◽  
2021 ◽  
Vol 89 (Supplement_2) ◽  
pp. S73-S73
Author(s):  
Syed M Adil ◽  
Lefko T Charalambous ◽  
Charis A Spears ◽  
Musa Kiyani ◽  
Sarah E Hodges ◽  
...  
Neurosurgery ◽  
2020 ◽  
Vol 67 (Supplement_1) ◽  
Author(s):  
Syed M Adil ◽  
Lefko T Charalambous ◽  
Kelly R Murphy ◽  
Shervin Rahimpour ◽  
Stephen C Harward ◽  
...  

Abstract INTRODUCTION Opioid misuse persists as a public health crisis affecting approximately one in four Americans.1 Spinal cord stimulation (SCS) is a neuromodulation strategy to treat chronic pain, with one goal being decreased opioid consumption. Accurate prognostication about SCS success is key in optimizing surgical decision making for both physicians and patients. Deep learning, using neural network models such as the multilayer perceptron (MLP), enables accurate prediction of non-linear patterns and has widespread applications in healthcare. METHODS The IBM MarketScan® (IBM) database was queried for all patients ≥ 18 years old undergoing SCS from January 2010 to December 2015. Patients were categorized into opioid dose groups as follows: No Use, ≤ 20 morphine milligram equivalents (MME), 20–50 MME, 50–90 MME, and >90 MME. We defined “opiate weaning” as moving into a lower opioid dose group (or remaining in the No Use group) during the 12 months following permanent SCS implantation. After pre-processing, there were 62 predictors spanning demographics, comorbidities, and pain medication history. We compared an MLP with four hidden layers to the LR model with L1 regularization. Model performance was assessed using area under the receiver operating characteristic curve (AUC) with 5-fold nested cross-validation. RESULTS Ultimately, 6,124 patients were included, of which 77% had used opioids for >90 days within the 1-year pre-SCS and 72% had used >5 types of medications during the 90 days prior to SCS. The mean age was 56 ± 13 years old. Collectively, 2,037 (33%) patients experienced opiate weaning. The AUC was 0.74 for the MLP and 0.73 for the LR model. CONCLUSION To our knowledge, we present the first use of deep learning to predict opioid weaning after SCS. Model performance was slightly better than regularized LR. Future efforts should focus on optimization of neural network architecture and hyperparameters to further improve model performance. Models should also be calibrated and externally validated on an independent dataset. Ultimately, such tools may assist both physicians and patients in predicting opioid dose reduction after SCS.


Neurosurgery ◽  
2020 ◽  
Vol 88 (1) ◽  
pp. 193-201
Author(s):  
Syed M Adil ◽  
Lefko T Charalambous ◽  
Charis A Spears ◽  
Musa Kiyani ◽  
Sarah E Hodges ◽  
...  

Abstract BACKGROUND Opioid misuse in the USA is an epidemic. Utilization of neuromodulation for refractory chronic pain may reduce opioid-related morbidity and mortality, and associated economic costs. OBJECTIVE To assess the impact of spinal cord stimulation (SCS) on opioid dose reduction. METHODS The IBM MarketScan® database was retrospectively queried for all US patients with a chronic pain diagnosis undergoing SCS between 2010 and 2015. Opioid usage before and after the procedure was quantified as morphine milligram equivalents (MME). RESULTS A total of 8497 adult patients undergoing SCS were included. Within 1 yr of the procedure, 60.4% had some reduction in their opioid use, 34.2% moved to a clinically important lower dosage group, and 17.0% weaned off opioids entirely. The proportion of patients who completely weaned off opioids increased with decreasing preprocedure dose, ranging from 5.1% in the >90 MME group to 34.2% in the ≤20 MME group. The following variables were associated with reduced odds of weaning off opioids post procedure: long-term opioid use (odds ratio [OR]: 0.26; 95% CI: 0.21-0.30; P < .001), use of other pain medications (OR: 0.75; 95% CI: 0.65-0.87; P < .001), and obesity (OR: 0.75; 95% CI: 0.60-0.94; P = .01). CONCLUSION Patients undergoing SCS were able to reduce opioid usage. Given the potential to reduce the risks of long-term opioid therapy, this study lays the groundwork for efforts that may ultimately push stakeholders to reduce payment and policy barriers to SCS as part of an evidence-based, patient-centered approach to nonopioid solutions for chronic pain.


Pain Practice ◽  
2019 ◽  
Vol 19 (8) ◽  
pp. 794-799 ◽  
Author(s):  
Thomas Simopoulos ◽  
Sanjiv Sharma ◽  
Raymond Joshua Wootton ◽  
Vwaire Orhurhu ◽  
Moris Aner ◽  
...  

2020 ◽  
Author(s):  
A Kasapovic ◽  
D Schwetje ◽  
D Cucchi ◽  
M Gathen ◽  
M Jaenisch ◽  
...  

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