Following the publication of the original article [1], we were notified that the name of the 10 ^th author was incorrectly tagged in the article’s XML. <GivenName>Perla</GivenName> <GivenName>J.</GivenName> <GivenName>Marang-van</GivenName> <Particle>de</Particle> <FamilyName>Mheen</FamilyName> <GivenName>Perla</GivenName> <GivenName>J.</GivenName> <FamilyName>Marang-van de Mheen</FamilyName> The original article has now been corrected.

Randomized controlled trials (RCTs) are the cornerstone of modern evidence-based medicine. They are considered essential to establish definitive evidence of efficacy and safety for new drugs, and whenever possible they should also be the preferred method for investigating new high-risk medical devices. Well-designed studies robustly inform clinical practice guidelines and decision-making, but administrative obstacles have made it increasingly difficult to conduct informative RCTs. The obstacles are compounded for RCTs of high-risk medical devices by extra costs related to the interventional procedure that is needed to implant the device, challenges with willingness to randomize patients throughout a trial, and difficulties in ensuring proper blinding even with sham procedures. One strategy that may help is to promote the wider use of simpler and more streamlined RCTs using data that are collected routinely during healthcare delivery. Recent large simple RCTs have successfully compared the performance of drugs and of high-risk medical devices, against alternative treatments; they enrolled many patients in a short time, limited costs, and improved efficiency, while also achieving major impact. From a task conducted within the CORE-MD project, we report from our combined experience of designing and conducting large pharmaceutical trials during the COVID-19 pandemic, and of planning and coordinating large registry-based RCTs of cardiovascular devices. We summarize the essential principles and utility of large simple RCTs, likely applicable to all interventions but especially in order to promote their wider adoption to evaluate new medical devices.

Background and purpose — Safety notices for medical devices such as total knee arthroplasty (TKA) implants may indicate problems in their design or performance that require corrective action to prevent patient harm. Safety notices are often published on national Ministries of Health or regulatory agencies websites. It is unknown whether problems triggering safety notices identify the same implants as those identified by registries as “outlier.” We aimed to assess the extent to which safety notices and outlier identification in registries signal the same or different TKA implants. Methods — The CORE-MD tool, an automated web scraper tool, was used to collect safety notices related to TKA implants on 13 national Ministries of Health websites and regulatory agencies. Safety notices were defined accord-ing to the Medical Device Regulation (MDR) as “a com-munication sent by a manufacturer to users or customers in relation to a field safety corrective action.” Identified TKA outliers, defined as having a significantly higher revision risk than other comparable TKA implants, were extracted from registry reports. Results — 787 safety notices for 38 TKA implants and 35 TKA outliers were identified, together identifying 47 unique TKA implants. 26 (55%) TKA implants had safety notices and were also outliers, 12 (26%) TKA implants had only safety notices, and 9 (19%) were outliers only. TKA implants with safety notices only had similar types of problems to TKA outliers with safety notices, with “Manufac-turing/Packaging/Shipping” problems being most frequent (44%). Cumulative revision risks (1/5/10 years) were lower for TKA implants with safety notices only than for TKA out-liers with safety notices. Conclusion — 55% of the TKA with a safety notice were identified as outliers in the registry, whereas around 25% of TKA outliers are not the subject of publicly released safety notices, with safety notices pointing to TKA implants not identified by registries as potentially having a higher risk of failure. This suggests that safety notices and registry outlier data measure different aspects of safety and performance.