(185 days)
The Signia™ stapler, when used with the Signia™ circular adapters and Tri-Staple™ 2.0 circular single use reloads, has applications throughout the alimentary tract for the creation of end-to-end, end-to-side, and side-to-side anastomoses in both open and laparoscopic surgeries.
The Signia™ stapler, when used with the Signia™ circular adapters and Tri-Staple™ 2.0 circular single use reloads, is a battery powered microprocessor controlled stapler that provides push-button powered maneuverability and firing of compatible reloads. The Signia™ Stapler is intended to be used by medical professionals qualified in the transportation, cleaning, sterilization, and use of surgical devices. The Signia™ stapler is intended for use in a sterile operating room environment in surgical procedures where surgical stapling is indicated.
The Signia™ circular adapters are reusable instruments that connect with the assembled Signia™ Power Handle and the Signia™ Power Shell to make up the Signia™ stapler. The circular adapters are composed of motor-mating connectors, sensor gauge, and device communications interfaces to provide functionality and communications between compatible reloads and the Signia™ Power Handle. The user can manually rotate the handle in 0, 90, 180 degrees to position the device if required, and the user can fire within these locked and rotated positions. The circular adapters are available in two shaft lengths, standard and extra-long, and both sizes are compatible with the new Tri-Staple™ 2.0 circular reloads.
The Tri-Staple™ 2.0 circular reloads place a circular triple staggered row of titanium staples. After staple formation, the knife blade resects the excess tissue, creating a circular anastomosis such as end-to-end, end-to-side, or side-to-side anastomosis as the user sees fit. The new circular reloads will be offered for a medium/thick tissue thickness range, which is identified by the purple staple guide. The circular reloads deploy three height-progressive rows of 3.0 mm. 3.5 mm and 4.0 mm titanium staples. The Tri-Stable™ 2.0 technology incorporated in the reloads is essentially the same as the legally-marketed predicate K172361 in terms of reload design. The circular reloads are provided sterile for single use, and available in five lumen sizes: 21, 25, 28, 31, and 33 mm. The Tilt-Top™ anvil is available with all circular reloads.
To create a circular anastomosis, the Signia™ Stapler consists of the Signia™ Power Handle, Signia™ Power Shell, Signia™ Circular Adapter, and Tri-Staple™ 2.0 circular reload. The existing system accessories such as Signia™ Reusable Insertion Guide, Signia™ Manual Retraction Tool, Signia™ Single Bay Charger, Signia™ Sterilization Tray (optional), and Signia™ Four-Bay Smart Charger (optional) can be also used.
The provided document is a 510(k) Summary for a medical device (Signia Circular Adapters and Tri-Staple 2.0 Circular Reloads for use with the Signia Stapler). It describes the device, its intended use, and substantial equivalence to a predicate device, supported by non-clinical studies. However, it does not contain a machine learning/AI component or corresponding studies.
Therefore, I cannot extract the information required in the prompt regarding acceptance criteria and studies that prove a device meets those criteria through AI/ML performance. The document focuses on showing substantial equivalence based on engineering and performance tests relevant to a traditional medical device, not an AI-powered one.
If there were a section describing an AI/ML component, I would look for information such as:
- Acceptance Criteria Table: A table outlining specific performance metrics (e.g., sensitivity, specificity, accuracy, F1-score) and their target values.
- Reported Device Performance: The actual measured performance of the AI device against those metrics.
- Sample Size and Data Provenance: Details about the dataset used for testing, including its size, origin (e.g., country, institution), and whether it was prospective or retrospective.
- Ground Truth Experts: The number and qualifications of experts involved in establishing the ground truth labels for the test data.
- Adjudication Method: How disagreements among experts were resolved to establish the final ground truth.
- MRMC Study: Information on multi-reader multi-case studies, including the effect size (improvement in human performance with AI assistance).
- Standalone Performance: Details of any study evaluating the algorithm's performance without human intervention.
- Type of Ground Truth: The method used to determine the true labels (e.g., pathology, long-term follow-up, expert consensus).
- Training Set Sample Size: The amount of data used to train the AI model.
- Training Set Ground Truth: How the ground truth for the training data was established.
Since this information is not present in the provided document, I cannot fulfill the request as it relates to AI/ML device performance.
§ 878.4750 Implantable staple.
(a)
Identification. An implantable staple is a staple-like device intended to connect internal tissues to aid healing. It is not absorbable.(b)
Classification. Class II.