Post-market safety signals of energy-based surgical devices: a cross-specialty disproportionality analysis of the FDA MAUDE database with robotic-platform validation and regulatory triangulation, 2015-2025.

IF 4.2 3区 医学 Q2 SURGERY
Ruifeng Shi
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引用次数: 0

Abstract

Post-market safety evidence for energy-based surgical devices is fragmented. We characterized adverse-event signals in the FDA MAUDE database, validated them on a third (robotic) platform, and triangulated across regulatory and international sources. Medical Device Reports (2015-2025) under electrosurgical and ultrasonic product codes were analyzed with reporting odds ratios (RORs), stratified by specialty and procedure, with robustness checks. All reports under the robotic-system code were retrieved as a third-platform validation cohort. Signals were triangulated with FDA recalls, 510(k) clearances, the Health Canada and Australian TGA databases, exposure descriptors, and a retrospectively applied Poisson CUSUM feasibility analysis. Among 110,183 deduplicated reports (65.8% electrosurgical, 34.2% ultrasonic), electrosurgical devices showed an electrical-thermal fingerprint (burns ROR 3.84; electric shock ROR 15.34) and ultrasonic devices a mechanical-integrity fingerprint (foreign-body removal ROR 92.74), replicated directionally in Canada and Australia. The fingerprint localized to generator/monopolar components and varied by specialty and procedure. Within the robotic validation cohort, component-stratified analysis partly reproduced these signatures-robot-mounted monopolar instruments retained a burn signal, and robot-mounted ultrasonic instruments carried the highest injury-report share-while cross-platform, same-modality contrasts are reported strictly as report-composition (share-level) comparisons. Reporting artifacts (19.5% placeholder narratives; a 2025 robotic mass-reporting episode comprising 55.8% of the robotic cohort) left fingerprint RORs materially unchanged. A retrospectively applied CUSUM flagged the burn theme more than five years before the 2023-2024 Class I recalls, illustrating-without establishing prospective lead time-the potential of automated monitoring. Energy-modality failure-injury fingerprints were consistent across specialties, delivery platforms, three national databases, and regulatory actions. Automated, artifact-aware surveillance of vigilance databases is a promising complement to pre-market review and warrants prospective evaluation.

基于能量的手术器械上市后安全信号:基于机器人平台验证和监管三角测量的FDA MAUDE数据库的跨专业歧化分析,2015-2025。
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来源期刊
CiteScore
4.20
自引率
8.70%
发文量
145
期刊介绍: The aim of the Journal of Robotic Surgery is to become the leading worldwide journal for publication of articles related to robotic surgery, encompassing surgical simulation and integrated imaging techniques. The journal provides a centralized, focused resource for physicians wishing to publish their experience or those wishing to avail themselves of the most up-to-date findings.The journal reports on advance in a wide range of surgical specialties including adult and pediatric urology, general surgery, cardiac surgery, gynecology, ENT, orthopedics and neurosurgery.The use of robotics in surgery is broad-based and will undoubtedly expand over the next decade as new technical innovations and techniques increase the applicability of its use. The journal intends to capture this trend as it develops.
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