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The Tigon Medical Tissue Anchor System is intended for use for the reattachment of soft tissue to bone for the following indications:

Shoulder: Capsular stabilization (Bankart repair, Anterior shoulder instability, SLAP lesion repairs, Capsular shift or capsulolabral reconstructions). Acromnioclavicular separation repairs, Rotator cuff repairs, Bicep tenodesis;

Elbow, Wrist, and Hand: Biceps tendon reattachmnent, Ulnar or radial collateral ligament reconstruction, Lateral epicondylitis repair;

Knee: Extra-capsular repairs (Medial collateral ligament, Lateral ligament, Posterior oblique ligament), Patellar realignment and tendon repairs (Vastus medials obliquous advancement), Illiotibial band tenodesis;

Foot and Ankle: Hallux valgus repairs. Medial or Lateral instability repairs/reconstructions. Achilles tendon repairs/ reconstructions, Midfoot reconstructions, Metatarsal ligament/tendon repairs/reconstructions, Bunionectomy

The Tigon Medical Tissue Anchor System consists of multiple-sized medial, lateral tissue anchors, and a single sized labral anchor. The medial anchors are threaded and are offered in 5.5 and 6.5 mm outer diameter sizes. The lateral anchors are conically barbed and are offered in 4.8 and 6 mm outer diameter sizes. The lateral anchors also offer unique angled locking slits to eliminate the need for knotting to secure the suture. The labral anchors are also barbed, and are offered in a 2.9 mm outer diameter, and are available with grooves, and two groove-less, knotless varieties (with and without locking slit). Tigon Tissue Anchors can be used with Tigon 2mm CuffTape and Tigon #2CuffCable (sold separately). Each tissue anchor will have a similar inserter.

The provided text describes the 510(k) summary for the Tigon Medical Tissue Anchors, specifically addressing its substantial equivalence to predicate devices. It outlines the device's indications for use, description, and technological characteristics. Crucially, it details the non-clinical and clinical performance data, but does not describe a study that uses AI/algorithm-based outcomes or human-in-the-loop performance.

The document discusses acceptance criteria and device performance in the context of mechanical, material, and sterilization testing for a medical device (tissue anchors), not a software or AI-based diagnostic/assessment tool. Therefore, many of the specific questions related to AI/algorithm performance (e.g., sample size for test set, data provenance, number of experts, adjudication method, MRMC studies, standalone performance, ground truth for training set) are not applicable to this submission.

However, based on the provided text, I can infer the following about the acceptance criteria and proof of substantial equivalence for this mechanical device:

Acceptance Criteria and Device Performance (for Tigon Medical Tissue Anchors - a physical medical device)

This submission focuses on demonstrating substantial equivalence to predicate devices through physical and material testing, rather than an AI/algorithm-based performance study.

1. Table of Acceptance Criteria and Reported Device Performance:

The document states that tests were completed and results concluded that the device "passed all pre-determined acceptance criteria." It implies that the acceptance criteria were defined by relevant ASTM and ISO standards for medical devices.

2. Sample Size Used for the Test Set and the Data Provenance:

• The document does not specify a "test set" in the context of an AI/algorithm.
• For the non-clinical performance data (mechanical, material, packaging, sterilization), typical sample sizes are used as defined by the respective ASTM/ISO standards. This is not explicitly stated but is an industry standard.
• The data provenance is from in-vitro laboratory testing conducted by the manufacturer (Tigon Medical and/or its testing partners) to meet regulatory requirements for a physical medical device. This is prospective testing of the manufactured device.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts:

• This is not applicable. Ground truth, in the context of AI/algorithm performance, refers to expertly labeled data. For a physical medical device, "ground truth" is established by the physical and chemical properties of the device and its performance against established engineering and safety standards. The "experts" would be the engineers, material scientists, and quality assurance personnel conducting and verifying the tests according to the standards.

4. Adjudication Method for the Test Set:

• This is not applicable. Adjudication is relevant for resolving discrepancies in expert labeling of data for AI. For physical device testing, results are quantitative and compared directly to predetermined acceptance criteria defined by standards.

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:

• This is not applicable. This submission is for a physical tissue anchor, not an AI-assisted diagnostic or treatment planning system. There are no "human readers" to assist or improve.

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

• This is not applicable. The device is a physical tissue anchor, not an algorithm.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.):

• The "ground truth" for this device's performance is based on established engineering standards, material science principles, and regulatory requirements for the physical properties, mechanical strength, biocompatibility, and sterility of medical implants. Performance is validated against these objective standards.

8. The Sample Size for the Training Set:

• This is not applicable. There is no AI/algorithm training set for this physical device.

9. How the Ground Truth for the Training Set Was Established:

• This is not applicable.

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