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510(k) Data Aggregation
(105 days)
Aesculap's AdTec® is indicated for use in adult and pediatric (3.5mm instruments only) diagnostic and therapeutic general endoscopy and laparoscopy surgery.
AdTec® is indicated for use in adult and pediatric diagnostic and therapeutic general endoscopy and laparoscopy surgery. The system consists of single-use and reusable forceps, clamps, and scissors made of Stainless Steel with monopolar or bipolar capabilities. They facilitate in the grasping, cutting, and manipulation of soft tissue and blood vessels during laparoscopic procedures. The single-use instruments come completely assembled in one single piece, and are available in various lengths ranging from 220mm - 420mm. The reusable instruments are modular and consist of a jaw insert and an insulated outer tube with interchangeable ratcheting and non-ratcheting handles. They are also available in lengths ranging from 220mm - 420mm. The system also includes a single use trocar sleeve and a reusable trocar pin. The trocar sleeve is made of Grilon, and the trocar pin is made of Stainless Steel and PEEK. The trocar sleeve and trocar pin are available in a 3.5mm diameter and a 70mm length. They are accessories for the 3.5mm trocars cleared under K123102.
This document does not contain information about the acceptance criteria and study that proves the device meets the acceptance criteria (commonly seen for AI/ML devices). This is an FDA 510(k) clearance letter for the AdTec® surgical instruments, which are physical medical devices, not an AI/ML diagnostic or therapeutic device. As such, the types of performance studies and criteria you've asked about (e.g., sample size for test/training set, expert ground truth, MRMC studies, standalone performance) are not applicable to this submission.
The document discusses substantial equivalence to predicate devices based on design, intended use, material composition, function, and range of sizes. It also briefly mentions a "failure mode and effects (FMEA) risk analysis" which identified no new risks, but this is not a study in the context of AI/ML device performance.
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