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The GRYPHON BR Anchor is intended for:
Shoulder: Rotator Cuff Repair, Bankart Repair, SLAP Lesion Repair, Biceps Tenodesis, Acromio-Clavicular Separation Repair, Deltoid Repair, Capsular Shift or Capsulolabral Reconstruction
Foot/Ankle: Lateral Stabilization, Medial Stabilization, Achilles Tendon Repair
Knee: Medial Collateral Ligament Repair, Lateral Collateral Ligament Repair, Posterior Oblique Ligament Repair, Iliotibial Band Tenodesis
Elbow: Biceps Tendon Reattachment, Ulnar or Radial Collateral Ligament Reconstruction
Hip: Capsular Repair, Acetabular Labral Repair

The GRYPHON PEEK Anchor is intended for:
Shoulder: Bankart Repair, SLAP Lesion Repair, Biceps Tenodesis, Acromio-Clavicular Separation Repair, Deltoid Repair, Capsular Shift or Capsulolabral Reconstruction
Foot/Ankle: Lateral Stabilization, Medial Stabilization
Knee: Medial Collateral Ligament Repair, Lateral Collateral Ligament Repair, Posterior Oblique Ligament Repair, Iliotibial Band Tenodesis
Elbow: Ulnar or Radial Collateral Ligament Reconstruction
Hip: Capsular Repair, Acetabular Labral Repair

The Gryphon™ Anchor with Permacord™ is a suture anchor preloaded on a disposable inserter assembly intended for fixation of suture to bone. Gryphon Anchors are available in absorbable BR and non-absorbable PEEK materials. Permacord suture is non-absorbable. The Gryphon Anchor with Permacord suture is supplied sterile and is for single use only.

This looks like a 510(k) submission for a medical device, specifically a suture anchor, and not an AI/ML device. Therefore, the typical acceptance criteria and study design for AI/ML performance evaluation do not apply here.

The document describes the Gryphon™ Anchor with Permacord™ as a suture anchor preloaded on a disposable inserter assembly, available in absorbable BR and non-absorbable PEEK materials with non-absorbable Permacord suture.

Here's an analysis based on the provided text, focusing on the information available and noting where AI/ML specific criteria are not applicable:

1. Table of Acceptance Criteria and Reported Device Performance:

Since this is not an AI/ML device, the "acceptance criteria" are not related to diagnostic accuracy metrics (e.g., sensitivity, specificity). Instead, they relate to safety and performance specifications for a medical implant like a suture anchor. The document states:

The study that "proves" the device meets the acceptance criteria is described as "Verification activities were performed on the implant and / or its predicates. Testing assessments include pull out testing and in-vitro testing." This non-clinical testing demonstrated that the device is "substantially equivalent" to predicate devices.

2. Sample Size for Test Set and Data Provenance:

This information is not applicable as the described testing is non-clinical performance and material testing for a physical medical device, not an AI/ML diagnostic or predictive model. There isn't a "test set" in the context of patient data.

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

This information is not applicable. Ground truth, in the context of AI/ML, refers to clinically verified labels or outcomes. For a physical device, testing involves engineering and materials science experts conducting physical tests, not clinical evaluations of patient data for ground truth.

4. Adjudication Method for the Test Set:

This information is not applicable for the same reasons as points 2 and 3.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done:

This information is not applicable. MRMC studies are used to evaluate the impact of AI on human reader performance, which isn't relevant for a physical implant device.

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

This information is not applicable. This device is a physical implant, not an algorithm.

7. The Type of Ground Truth Used:

For the performance testing, the "ground truth" would be the objective measurement of mechanical properties (e.g., maximum load at failure for pull-out strength) under controlled laboratory conditions, compared against pre-defined engineering specifications or predicate device performance. It is not expert consensus, pathology, or outcomes data in the AI/ML sense.

8. Sample Size for the Training Set:

This information is not applicable as there is no AI/ML algorithm being trained.

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

This information is not applicable as there is no AI/ML algorithm being trained.

In summary, the provided document describes a 510(k) submission for a physical medical device (suture anchor) and focuses on demonstrating substantial equivalence to predicate devices through non-clinical performance testing and material characterization. The concepts of acceptance criteria, test sets, ground truth, and studies as typically applied to AI/ML devices are not relevant to this submission.

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