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The FOOTPRINT® MINI PK, 3.5mm Suture Anchor is only intended for the reattachment of soft tissue to bone for the following indications:

Foot and Ankle:

• · Medial or lateral instability repairs/reconstructions
• · Achilles tendon repairs/reconstructions
  Knee:
• · Extra-capsular repairs
• -Medial collateral ligament
• -Lateral collateral ligament
• -Posterior oblique ligament

The Smith & Nephew FOOTPRINT? MINI PK, 3.5mm Suture Anchor is a fixation device intended to provide reattachment of soft tissue to bone. The device consists of a two-piece suture anchor comprised of an anchor body and inner plug, preassembled onto an insertion device. The device is sold with a disposable suture threader.

This response pertains to a medical device submission, specifically a 510(k) for the "FOOTPRINT® MINI PK, 3.5mm Suture Anchor". The provided text describes a physical medical device and not a software algorithm or AI-powered device. Therefore, many of the requested categories related to AI/software performance evaluation (like test set data provenance, expert ground truth, MRMC studies, training set details, etc.) are not applicable to this type of submission.

The provided document details the regulatory clearance of a physical medical device, not a diagnostic AI or imaging analysis software. Thus, the information requested about acceptance criteria for AI algorithms, training sets, ground truth establishment methods typical for AI, multi-reader multi-case studies, and human-in-the-loop performance is not found in the provided text as it pertains to a different type of medical product.

However, I can extract information regarding the device's performance testing and acceptance, which are analogous to "acceptance criteria" for a physical device.

Here's the relevant information based on the provided text:

Acceptance Criteria and Device Performance (for a physical medical device)

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

Note: The document states, "Non-clinical bench testing was completed on the subject device, and the device met all required specifications for each test. ... Results for all tests passed." It implies that specific predefined criteria for each test type were met, but the precise numerical or qualitative thresholds for these criteria are not detailed in this publicly available summary.

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

• Sample Size: The document does not specify the exact sample size (number of devices/implants) used for each non-clinical bench test.
• Data Provenance: Not applicable as this is bench testing of physical devices, not clinical data or imaging. The tests were performed in a lab setting, likely by Smith & Nephew.

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)

• Not Applicable: "Ground truth" in the context of expert review for medical imaging or AI models is not relevant here. The "ground truth" for the performance of a physical medical device is established through its physical and mechanical properties as measured in bench testing against defined engineering specifications.

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

• Not Applicable: Adjudication methods like 2+1 or 3+1 are used for human review of medical images or data, typically in the context of clinical studies or establishing ground truth for AI. For physical device bench testing, engineering standards and protocols dictate the evaluation, not human adjudication in this sense.

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

• Not Applicable: MRMC studies are specific to the evaluation of diagnostic imaging devices, often involving human readers and potentially AI assistance. This submission is for a physical orthopedic implant.

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

• Not Applicable: This question refers to the performance of an independent AI algorithm. The device is a physical suture anchor, not an algorithm.

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

• Engineering Specifications/Standards: The "ground truth" for this device's performance is based on established engineering specifications and industry standards for mechanical strength, insertion force, and durability under various loading conditions relevant to its intended use in soft tissue to bone reattachment. The document states, "the device met all required specifications for each test."

8. The sample size for the training set

• Not Applicable: There is no "training set" in the context of a physical device. This term is used for machine learning algorithms.

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

• Not Applicable: As there is no training set for a physical device, this question is not relevant.

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