ArticlePloS one2023
Identification of predicate creep under the 510(k) process: A case study of a robotic surgical device.
Article in PloS one, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
8 citing papers in PubMed.
- Innovating global regulatory frameworks for generative AI in medical devices is an urgent priority.NPJ digital medicine · 2026Review
- The history of state preemption and medical device regulation: lessons for artificial intelligence oversight.Health affairs scholar · 2026Article
- Scaling medical device regulatory science using large language models.NPJ digital medicine · 2026Article
- Where are all the neurosurgery robots?Journal of robotic surgery · 2025Review
- Review
- Robotic technology in surgery; a classification system of soft tissue surgical robotic devices.Surgical endoscopy · 2024Review
- Levels of autonomy in FDA-cleared surgical robots: a systematic review.NPJ digital medicine · 2024Review
- Analysis of Trends in FDA-Recalled Hip Arthroplasty Devices: A Retrospective Review.JB & JS open accessArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The FDA's 510(k) process for medical devices is based on "substantial equivalence" to devices clearedpre-1976 or legally marketed thereafter, known as predicate devices. In the last decade, several high-profile device recalls have drawn attention to this regulatory clearance process and researchers have raised questions about the validity of the 510(k) process as a broad clearance mechanism. One of the issues raised is the risk of predicate creep, a cycle of technology change through repeated clearance of devices based on predicates with slightly different technological characteristics, such as materials and power sources, or have indications for different anatomical sites. This paper proposes a new way to identify potential "predicate creep" through the use of product codes and regulatory classifications. We test this method by applying it to a case study of a Robotic Assisted Surgery (RAS) device, the Intuitive Surgical Da Vinci Si Surgical System. We find that there is evidence of predicate creep using our method, and discuss implications of this method for research and policy.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.