MAUDE data represents reports of adverse events involving medical devices. The data consists of all voluntary reports since June, 1993, user facility reports since 1991, distributor reports since 1993, and manufacturer reports since August, 1996.

The adverse events reports related to robotic surgical systems and instruments, submitted to the publicly available FDA MAUDE database between January 2000 and December 2013.We extracted this data by searching the MAUDE records which are available on the FDA website at: http://www.fda.gov/MedicalDevices/DeviceRegulationandGuidance/PostmarketRequirements/ReportingAdverseEvents/ucm127891.htmThe structured data generated by our natural language parsing tool, after analysis of unstructured fields in the FDA MAUDE records. The new information (fields) extracted from the data include: • Patient injury (such as burns, cuts, or damage to organs) and death events that were reported under another Event Type, such as “Malfunction” or “Other”. • Surgical specialty and type of robotic procedure during which the adverse events occurred. • Major types of device or instrument malfunctions (e.g., falling of burnt/broken pieces of instruments into patients’ bodies or electrical arcing of instruments) • Adverse events that caused an interruption in the progress of surgery, by leading the surgical team to troubleshoot technical problems (e.g., restarting the system), convert the procedure to non-robotic surgical approaches (e.g., laparoscopy or open surgery), or abort the procedure and reschedule it to a later time.

(Note that the malfunction and surgical team action categories are not mutually exclusive, i.e., in many cases more than one malfunction or action were reported in a single event.)

BackgroundUse of robotic systems for minimally invasive surgery has rapidly increased during the last decade. Understanding the causes of adverse events and their impact on patients in robot-assisted surgery will help improve systems and operational practices to avoid incidents in the future.MethodsBy developing an automated natural language processing tool, we performed a comprehensive analysis of the adverse events reported to the publicly available MAUDE database (maintained by the U.S. Food and Drug Administration) from 2000 to 2013. We determined the number of events reported per procedure and per surgical specialty, the most common types of device malfunctions and their impact on patients, and the potential causes for catastrophic events such as patient injuries and deaths.ResultsDuring the study period, 144 deaths (1.4% of the 10,624 reports), 1,391 patient injuries (13.1%), and 8,061 device malfunctions (75.9%) were reported. The numbers of injury and death events per procedure have stayed relatively constant (mean = 83.4, 95% confidence interval (CI), 74.2–92.7 per 100,000 procedures) over the years. Surgical specialties for which robots are extensively used, such as gynecology and urology, had lower numbers of injuries, deaths, and conversions per procedure than more complex surgeries, such as cardiothoracic and head and neck (106.3 vs. 232.9 per 100,000 procedures, Risk Ratio = 2.2, 95% CI, 1.9–2.6). Device and instrument malfunctions, such as falling of burnt/broken pieces of instruments into the patient (14.7%), electrical arcing of instruments (10.5%), unintended operation of instruments (8.6%), system errors (5%), and video/imaging problems (2.6%), constituted a major part of the reports. Device malfunctions impacted patients in terms of injuries or procedure interruptions. In 1,104 (10.4%) of all the events, the procedure was interrupted to restart the system (3.1%), to convert the procedure to non-robotic techniques (7.3%), or to reschedule it (2.5%).ConclusionsDespite widespread adoption of robotic systems for minimally invasive surgery in the U.S., a non-negligible number of technical difficulties and complications are still being experienced during procedures. Adoption of advanced techniques in design and operation of robotic surgical systems and enhanced mechanisms for adverse event reporting may reduce these preventable incidents in the future.

Related work on analysis of the FDA adverse event reports on robotic surgical systems.

This dataset tracks the updates made on the dataset "MAUDE (Manufacturer and User Facility Device Experience)" as a repository for previous versions of the data and metadata.

PurposeImplantable Collamer Lens (ICL) implantation is rising globally, yet real-world studies on adverse events (AEs) remain scarce. This study analyses ICL-related complications using the MAUDE database.MethodsData on ICL-related AEs were extracted from the MAUDE database. Cases were categorized into spherical and toric ICLs based on lens diopter. Descriptive statistics summarized device-related issues and complications, and Cramér’s V assessed their associations. Management strategies and resolution rates for common complications were also evaluated.ResultsAmong 25,001 ICL-related AEs, 43.8% involved spherical ICLs and 56.2% toric ICLs. Common device-related issues included “Shape and/or size problems” (nearly half of annual AEs) and “Off-label use” (around 20%, rising since 2019 and stabilizing). “Operation and control issues” declined steadily since 2019, stabilizing below 3%. Spherical ICL cases with “Activation, positioning, or separation problems” dropped below 1% post-2019, while toric cases remained at 6.9–9.0%. The top three complications—"Vision issues,” “Intraocular pressure issues” and “Lens-related issues”—were most frequent, with “No patient impact” in most cases. Moderate correlations were found between complications and ICL-related AEs (p = 9.999 × 10−5, Cramér’s V: 0.47 for spherical, 0.45 for toric). Management strategies, including lens exchange and lens extraction followed by surgery, demonstrated high resolution rates.ConclusionWhile ICL implantation is generally safe, concerns about inappropriate sizing and off-label use persist. This study suggests that improving lens sizing accuracy and adhering to guidelines may reduce AEs.

This data is publically available in the FDA MAUDE database from 2012 to 2015

Original raw data extracted from MAUDE using product code KZH for period of January 1, 2008, to September 30, 2023.

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Subscribers can find out export and import data of 23 countries by HS code or product’s name. This demo is helpful for market analysis.

Hay and Maude Flood Risk Management Study and Plan - Flood Damages Database

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This dataset contains annual sales trends history for Maude, 2711 covering median prices, sales volumes, resales capital growth and more. Based on sales data from the NSW Valuer General analysed by AreaSearch.

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This dataset provides information about the number of properties, residents, and average property values for Maude Road cross streets in Rocky Mount, NC.

This database is related to the following article : "A preliminary study exploring the mechanical properties of normal and Mgp-deficient mouse femurs during early growth", Proceedings of the iMeche, Part H: Journal of Engineering in Medecine (2022) The database contains raw data of the bending response of 32 samples (8 groups of 4 samples), one summary file containing information associated with the tested samples, and 16 vtk files corresponding to reconstructed meshes prepared for Finite Element analysis, containing Hounsfield Unit (HU) issued from the CT image as well as Bone Mineral Desnity (BMD) issued from calibration. It also contains the python script required to read and plot the data The name of the file corresponding to the postnatal age (e.g. P14 for 14 days postnatal) as well as the MGP gene expression (MM for -/- and PP for +/+)

This report comprises notes on the geology, ores reserves, and exploration of the Maude and Yellow Girl Gold Mining Company.

Maude Levee - Levee Owners Manual December 2019