Search Results

The devices are intended for transection, and/or creation of anastomoses. The instruments have application in multiple open or minimally invasive general abdominal, gynecologic, thoracic, and pediatric surgical procedures.

The proposed device places two, triple-staggered rows of titanium staples and simultaneously divides the tissue from central line. The device is available in 70mm, 160mm three lengths. Reloads of easyEndoTM Linear Cutting Stapler and Loading Units for Single Use are available in three staple sizes to accommodate various tissue thickness: 2.5mm, 3.5mm and 4.8mm. Reloads of easyEndoTM Universal Linear Cutting Stapler and Loading Units for Single Use are available in four staple sizes to accommodate various tissue thickness: 2.5mm, 3.8mm and 4.1mm. The device may be reloaded and fired up to 25 times for 1 firing in a single procedure.

The provided text is a 510(k) summary for the easyEndo™ Linear Cutting Stapler and Loading Units, a medical device. This document focuses on demonstrating substantial equivalence to existing predicate devices, primarily through non-clinical performance and design comparisons. It does not present a study with specific acceptance criteria that the device meets numerically, as would be expected for an AI/ML device.

Therefore, I cannot fully answer your request by filling out the table and detailed points as it's designed for an AI/ML device evaluation. The information provided is a premarket notification for a traditional medical device, where "acceptance criteria" are typically met through adherence to recognized standards (e.g., ISO, ASTM, USP) and direct comparison to predicates.

Here's a breakdown of why and what information can be extracted/inferred:

Why the Request Cannot Be Fully Answered as Posed:

• No AI/ML Component: The device is a mechanical stapler, not an AI/ML system. Therefore, concepts like "algorithm only without human-in-the-loop performance," "effect size of human readers improving with AI," "training set," "ground truth for training set," "number of experts for ground truth," and "adjudication method" are not applicable.
• "Acceptance Criteria" Different: For a traditional device like this, "acceptance criteria" are implied by compliance with performance standards and the demonstration of equivalence to legally marketed predicate devices. There isn't a specific quantitative "accuracy" or "performance metric" with a numerical threshold tied to the device's function that is then measured in a study. The "performance test" section describes what was tested, but not the specific thresholds for "acceptance."
• No "Study" as Defined for AI/ML: The document describes "non-clinical tests" (bench testing) and states "No clinical study is included in this submission." This means there wasn't a comparative clinical trial to measure human-in-the-loop performance or standalone performance in a real-world setting against a defined ground truth.

Extracted Information (and why some points are N/A):

Based on the provided text, here's what can be addressed:

• Device Name: easyEndo™ Linear Cutting Stapler and Loading Units for Single Use, easyEndo™ Universal Linear Cutting Stapler and Loading Units for Single Use

1. A table of acceptance criteria and the reported device performance

Note: The document states "test results demonstrated that the proposed device complies with the following standards" and that it was "determined to be Substantially Equivalent (SE) to the predicate devices." For a 510(k), this general statement implies that the specific acceptance criteria for each test (e.g., max firing force, specific staple height range) were met, even if the exact numerical values aren't provided in this summary.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample Size: Not explicitly stated for each test. The text mentions "performance test performed on both proposed device and predicate device" but not the number of units/tests.
• Data Provenance: The tests were conducted internally by Ezisurg Medical Co., Inc. (China). The data would be considered retrospective in the sense that it was collected as part of the development and submission process.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

• N/A. This applies to AI/ML devices where human expert annotations create a 'ground truth' dataset. For this mechanical stapler, the "ground truth" is defined by engineering specifications and objective test methods (e.g., Firing Force measurements, visual staple formation checks).

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

• N/A. Not applicable to objective mechanical bench testing. Adjudication methods are typically used for expert consensus in image interpretation for AI/ML.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

• N/A. This is a mechanical device, not an AI/ML system assisting human readers. The document explicitly states "No clinical study is included in this submission."

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

• N/A. No algorithm involved. The "standalone" performance here refers to the device's mechanical function, which was assessed via the non-clinical tests (e.g., Firing Force, Staple Formation).

7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)

• The "ground truth" for this device's performance is based on engineering specifications, established industry standards (ISO, ASTM, USP), and direct comparability to the performance parameters of legally marketed predicate devices. It is not expert consensus, pathology, or outcomes data.

8. The sample size for the training set

• N/A. There is no "training set" as this is not an AI/ML device.

9. How the ground truth for the training set was established

• N/A. There is no "training set" or "ground truth for training set."

Ask a specific question about this device