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The circular stapler with DST Series™ Technology has application throughout the alimentary tract for the creation of endto-end, end-to-side, and side-to-side anastomoses in both open and laparoscopic surgeries.

The Autosuture™ EEA™ Stapler is a manual, single-use device that places a circular. double staggered row of titanium staples and resects excess tissue. It has application 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.

Here's an analysis of the provided FDA 510(k) submission regarding the acceptance criteria and study information for the Autosuture™ EEA™ Stapler.

It's important to note that this document is a 510(k) summary, which often does not include detailed study results or raw data. Instead, it summarizes the equivalence claims based on testing.

Acceptance Criteria and Device Performance (Based on Non-Clinical Testing Summary)

The provided document does not explicitly list quantitative acceptance criteria in a table format with corresponding reported performance values for each criterion. The non-clinical testing section lists various tests performed to demonstrate substantial equivalence, implying that the device met the internal acceptance criteria for these tests.

Implied Acceptance Criteria and Performance (Extracted from Non-Clinical Testing List):

Study Proving Acceptance Criteria:

The studies proving the device meets these implied acceptance criteria are the non-clinical tests listed, which were performed by Covidien. The document states:
"Testing demonstrated that the subject device, Autosuture™ EEA™ Stapler, is substantially equivalent to the predicate devices..."

Detailed Study Information:

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

   • The document does not specify sample sizes or data provenance (country of origin, retrospective/prospective) for the non-clinical tests conducted. These details are typically found in the full test reports, not the 510(k) summary. Given the nature of these engineering and materials tests, they are inherently "prospective" as new tests were conducted on the subject device.

2. 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)

   • This question is not applicable to the type of non-clinical testing described. These tests involve engineering measurements (e.g., force, material properties, sterility, biocompatibility) rather than expert interpretation of medical data (like radiology images). The "ground truth" for these types of tests is established by industry standards (ASTM, ISO, IEC) and the test methodologies themselves.

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

   • This question is not applicable to the non-clinical testing described. Adjudication methods like 2+1 are used for expert consensus on subjective medical assessments, which is not the nature of these engineering tests.

4. 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

   • No, an MRMC comparative effectiveness study was not done. This device is a manual surgical stapler, not an AI-powered diagnostic or assistive tool for human readers.

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

   • No, a standalone algorithm performance study was not done. This device is a mechanical surgical stapler and does not involve an algorithm.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

   • For the non-clinical tests, the "ground truth" is defined by established engineering and biological standards and specifications (e.g., ASTM F2182-19 for RF heating, ISO 10993-1 for biocompatibility). The device performance is measured against these objective, predefined criteria.

7. The sample size for the training set

   • This question is not applicable. There is no "training set" as this is a mechanical medical device, not a machine learning or AI model.

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

   • This question is not applicable for the same reason as above; there is no training set for this type of device.

Summary of Device and Evidence Strategy:

The Autosuture™ EEA™ Stapler is a traditional mechanical surgical device. The submission strategy for its 510(k) clearance is based on substantial equivalence to previously cleared predicate devices (Autosuture™ Circular EEA Surgical Stapler K062850 and EEA Circular Stapler with Tri-Staple Technology K221005).

The primary evidence provided focuses on non-clinical performance testing to demonstrate that the subject device performs as safely and effectively as the predicate devices and meets relevant engineering, material, and safety standards. The document explicitly states, "This submission does not require clinical testing," reinforcing that the equivalence is established through physical and mechanical characteristic comparisons and associated test results, rather than clinical trials comparing patient outcomes.

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