Objectives: Spinal cord stimulation (SCS) has been challenged by the lack of neurophysiologic data to guide therapy optimization. Current SCS programming by trial-and-error results in suboptimal and variable therapeutic effects. A novel system with a physiologic closed-loop feedback mechanism using evoked-compound action potentials enables the optimization of physiologic neural dose by consistently and accurately activating spinal cord fibers. We aimed to identify neurophysiologic dose metrics and their ranges that resulted in clinically meaningful treatment responses.
Materials and methods: Subjects from 3 clinical studies (n = 180) with baseline back and leg pain ≥60 mm visual analog scale and physical function in the severe to crippled category were included. Maximal analgesic effect (MAE) was operationally defined as the greatest percent reduction in pain intensity or as the greatest cumulative responder score (minimal clinically important differences [MCIDs]) obtained within the first 3 months of SCS implant. The physiologic metrics that produced the MAE were analyzed.
Results: We showed that a neural dose regimen with a high neural dose accuracy of 2.8μV and dose ratio of 1.4 resulted in a profound clinical benefit to chronic pain patients (MAE of 79 ± 1% for pain reduction and 12.5 ± 0.4 MCIDs). No differences were observed for MAE or neurophysiological dose metrics between the trial phase and post-implant MAE visit.
Conclusion: For the first time, an evidence-based neural dose regimen is available for a neurostimulation intervention as a starting point to enable optimization of clinical benefit, monitoring of adherence, and management of the therapy.
Keywords: Maximal analgesic effect; neurophysiologic dose metrics; physiologic closed-loop feedback mechanism; spinal cord stimulation; therapy optimization.
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