Increased Spinal Cord Stimulator Use and Continued Opioid Treatment Among Injured Workers

The Evolution of Surgical Technique in Spinal Cord Stimulation: A Scoping Review

Since the advent of spinal cord stimulation (SCS), its operative technique has consistently advanced. We performed a scoping review of the literature regarding SCS operative techniques to highlight key advancements. To review, summarize, and highlight key changes in SCS implantation techniques since their inception. The authors performed a MEDLINE search inclusive of articles from 1967 to June 2023 including human and modeling studies written in English examining the role of trialing, intraoperative neuromonitoring, and surgical adaptations. Using the Rayyan platform, two reviewers performed a blinded title screen. Of the 960 articles, 197 were included in the title screen, 107 were included in the abstract review, and ultimately 69 articles met inclusion criteria. We examined the utility of trialing and found that historical controls showed significant efficacy, whereas recent results are more equivocal. We discuss the significant improvement in outcomes with intraoperative neuromonitoring for asleep SCS placement. We highlight technique improvements that led to significant reductions in infection, lead migration, and inadequate pain relief. Physicians implanting SCS systems for chronic pain management must continually refine their surgical techniques to keep up with this rapidly evolving therapy. In addition, through collaborative efforts of neuromodulators and industry, SCS is safer and more effective for patients suffering from chronic pain.

Long-term Outcomes in Use of Opioids, Nonpharmacologic Pain Interventions, and Total Costs of Spinal Cord Stimulators Compared With Conventional Medical Therapy for Chronic Pain

Importance

Spinal cord stimulators (SCSs) are increasingly used for the treatment of chronic pain. There is a need for studies with long-term follow-up.

Objective

To determine the comparative effectiveness and costs of SCSs compared with conventional medical management (CMM) in a large cohort of patients with chronic pain.

Design, Setting, and Participants

This was a 1:5 propensity-matched retrospective comparative effectiveness research analysis of insured individuals from April 1, 2016, to August 31, 2018. This study used administrative claims data, including longitudinal medical and pharmacy claims, from US commercial and Medicare Advantage enrollees 18 years or older in Optum Labs Data Warehouse. Patients with incident diagnosis codes for failed back surgery syndrome, complex regional pain syndrome, chronic pain syndrome, and other chronic postsurgical back and extremity pain were included in this study. Data were analyzed from February 1, 2021, to August 31, 2022.

Exposures

SCSs or CMM.

Main Outcomes and Measures

Surrogate measures for primary chronic pain treatment modalities, including pharmacologic and nonpharmacologic pain interventions (epidural and facet corticosteroid injections, radiofrequency ablation, and spine surgery), as well as total costs.

Results

In the propensity-matched population of 7560 patients, mean (SD) age was 63.5 (12.5) years, 3080 (40.7%) were male, and 4480 (59.3%) were female. Among matched patients, during the first 12 months, patients treated with SCSs had higher odds of chronic opioid use (adjusted odds ratio [aOR], 1.14; 95% CI, 1.01-1.29) compared with patients treated with CMM but lower odds of epidural and facet corticosteroid injections (aOR, 0.44; 95% CI, 0.39-0.51), radiofrequency ablation (aOR, 0.57; 95% CI, 0.44-0.72), and spine surgery (aOR, 0.72; 95% CI, 0.61-0.85). During months 13 to 24, there was no significant difference in chronic opioid use (aOR, 1.06; 95% CI, 0.94-1.20), epidural and facet corticosteroid injections (aOR, 1.00; 95% CI, 0.87-1.14), radiofrequency ablation (aOR, 0.84; 95% CI, 0.66-1.09), or spine surgery (aOR, 0.91; 95% CI, 0.75-1.09) with SCS use compared with CMM. Overall, 226 of 1260 patients (17.9%) treated with SCS experienced SCS-related complications within 2 years, and 279 of 1260 patients (22.1%) had device revisions and/or removals, which were not always for complications. Total costs of care in the first year were $39 000 higher with SCS than CMM and similar between SCS and CMM in the second year.

Conclusions and Relevance

In this large, real-world, comparative effectiveness research study comparing SCS and CMM for chronic pain, SCS placement was not associated with a reduction in opioid use or nonpharmacologic pain interventions at 2 years. SCS was associated with higher costs, and SCS-related complications were common.

Development of Machine Learning-Based Models to Predict Treatment Response to Spinal Cord Stimulation

BACKGROUND

Despite spinal cord stimulation's (SCS) proven efficacy, failure rates are high with no clear understanding of which patients benefit long term. Currently, patient selection for SCS is based on the subjective experience of the implanting physician.

OBJECTIVE

To develop machine learning (ML)-based predictive models of long-term SCS response.

METHODS

A combined unsupervised (clustering) and supervised (classification) ML technique was applied on a prospectively collected cohort of 151 patients, which included 31 features. Clusters identified using unsupervised K-means clustering were fitted with individualized predictive models of logistic regression, random forest, and XGBoost.

RESULTS

Two distinct clusters were found, and patients in the cohorts significantly differed in age, duration of chronic pain, preoperative numeric rating scale, and preoperative pain catastrophizing scale scores. Using the 10 most influential features, logistic regression predictive models with a nested cross-validation demonstrated the highest overall performance with the area under the curve of 0.757 and 0.708 for each respective cluster.

CONCLUSION

This combined unsupervised-supervised learning approach yielded high predictive performance, suggesting that advanced ML-derived approaches have potential to be used as a functional clinical tool to improve long-term SCS outcomes. Further studies are needed for optimization and external validation of these models.