Single-Center Retrospective Analysis of Device-Related Complications Related to Dorsal Root Ganglion Stimulation for Pain Relief in 31 Patients.

Dorsal root ganglion (DRG) stimulation is a form of neuromodulation used to treat neuropathic pain due to a myriad of etiologies. Though this relatively new therapy has been shown to be quite effective, complications associated with the implantation of this therapy have not been well documented. The primary objective of this study was to describe the device-related complications associated with DRG stimulator implantations. This was a single-center retrospective analysis of 31 patients who underwent full implantation of neuromodulation hardware marketed for DRG stimulation. The predefined endpoints included device-related complications associated with DRG implantations, such as hardware failure, explantation procedures, and revision surgery. Additional endpoints included percentage of patients receiving therapy and pain as measured using the visual analog scale (VAS) pain scale at initial, six-month, and 12-month follow-up after hardware implantation. Thirty-one patients were included out of 42 patients trialed. Baseline VAS in patients was 7.7 (31 patients). At initial follow-up, six-month follow-up, and one-year follow-up, VAS scores were 4.7 (31 patients), 5.3 (20 patients), and 5.5 (13 patients), respectively. Paired t-test between preoperative VAS (mean 7.3) and one-year follow-up VAS (5.5) demonstrated statistical significance (p = 0.027). At initial, six-month, and one-year follow-up, 30/31 (97%), 19/24 (79%), and 18/23 (78%) patients were confirmed to be receiving DRG stimulation therapy after permanent implant. Of the 31 patients who were implanted with a permanent system, 8 (26%) were explanted and an additional 10 (29%) required revision surgery. In this study, we examine the various device-related complications associated with DRG stimulation requiring repeat surgery. High rates of hardware failure, revision surgery, and explantation of stimulators illustrate the need for hardware optimization to improve patient outcomes.

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