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The Ross Creek Spin-Loc Suture Anchor System is intended to be used for soft tissue fixation to bone in the shoulder, foot and ankle, knee, and elbow. The anchor is intended for use in the following procedures:

Shoulder

• Rotator Cuff Repair
• Bankart Repair
• SLAP Lesion Repair
• Biceps Tenodesis
• Acromio-Clavicular Separation Repair
• Deltoid Repair
• Capsular Shift/Capsulolabral Reconstruction

Foot and Ankle

• Lateral Stabilization
• Medial Stabilization
• Achilles Tendon Repair
• Hallux Valgus Reconstruction
• Midfoot Reconstruction
• Metatarsal Ligament Repair

Knee

• Medial Collateral Ligament Repair
• Lateral Collateral Ligament Repair
• Patellar Tendon Repair
• Posterior Oblique Ligament Repair
• Illiotibial Band Tenodesis

Elbow

• Biceps Tendon Reattachment
  The Ross Creek Spin-Loc Suture Anchor System is intended for single-use only.

The Spin-Loc Suture Anchor System consists of a PEEK polymer and stainless steel or cobalt chromium alloy suture anchor loaded on an insertion handle. The Spin-Loc anchor is designed to facilitate fixation of soft tissue to bone. The design allows the surgeon to adjust the tension on the tissue after insertion of the anchor into bone. The Spin-Loc Suture Anchor System will be validated to a SAL of 10-6 using ethylene oxide. The ethylene oxide residuals will be tested according to ISO10993-7.

The information provided primarily describes a 510(k) premarket notification for a medical device, the "Spin-Loc Suture Anchor System," which asserts substantial equivalence to predicate devices based on in vitro studies of anchor pull-out strength. It does not contain information about clinical acceptance criteria, a clinical study on device performance in humans, or the details typically associated with AI/software performance evaluations.

Therefore, for aspects relevant to clinical device performance and AI/software, the information is largely absent in the provided text.

Here's an attempt to answer the questions based only on the provided text, highlighting what is not available:

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

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 for test set: Not specified. The study was "in vitro," implying laboratory testing, not human or patient data.
• Data provenance: "in vitro studies." This means the data was generated in a lab setting, not from human patients. Country of origin is not specified, but the applicant is a US company.
• Retrospective or prospective: Not applicable as these were in vitro studies.

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. The ground truth for the in vitro pull-out strength study would be based on mechanical testing measurements (e.g., force transducers) and material science principles, not expert human evaluation.

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

• Not applicable for in vitro mechanical testing.

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

• No. This is a physical medical device (suture anchor system), not an AI or imaging diagnostic device. Therefore, an MRMC study is not relevant here.

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

• No. This is a physical medical device. This question is not applicable.

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

• For the in vitro pull-out strength study, the "ground truth" would be the objectively measured mechanical forces at which anchor pull-out or failure occurred, as per standardized testing methods (e.g., ASTM standards or FDA guidance).

8. The sample size for the training set

• Not applicable. This is not an AI/ML device that requires a training set. For the in vitro mechanical testing, there would be no "training set."

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

• Not applicable. (See #8)

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