Adverse Events in Peripheral Nerve Stimulation: A 10-Year MAUDE Database Analysis

Background and/or Objectives: The purpose of this study is to conduct a comprehensive analysis of adverse events (AEs) associated with peripheral nerve stimulation (PNS) devices, due to the attraction gained as a non-opioid treatment modality for chronic pain management. By systematically examining these reports, we aim to identify recurrent AEs, recognize trends over time, and establish potential risk factors linked to these events. This analysis aims to enhance our understanding of the safety profile of PNS devices and‬‭ enable the development of strategies to mitigate associated risks.‬

Design: Retrospective descriptive analysis.

Setting : The Manufacturer and User Facility Device‬‭ Experience (MAUDE) database.

Participants : Adverse event reports involving PNS devices submitted between January 2013 and March 2024, filtered by product code “GZF.”

Interventions: peripheral nerve stimulation (PNS).

Main Outcome Measures: Event type classification (injury, malfunction, death), device- and patient-related problem categories, and manufacturer/device frequency distributions.

Results: The MAUDE database contained 2,469 reports about PNS devices where 98.9% fell under the injury category. The most common device-related issues included nonspecific adverse events (n=1,609), lead migration (n=113), and device malfunction. The patient complaints that appeared most often included inadequate pain relief (n=730), infections (n=197), erosion (n=164) and discomfort (n=101).

Conclusions: The 10-year safety evaluation demonstrates that inadequate pain control, infections and hardware complications continue to be prevalent issues in PNS treatment. The results demonstrate the requirement for standardized AE reporting systems alongside operator training programs and long-term safety monitoring registries. The study provides important safety recommendations for PNS device implementation in pain management despite the constraints of passive surveillance data.