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The Ventix Suture Anchors are indicated for use in soft tissue reattachment procedures in the shoulder, wrist/hand, ankle/foot, elbow, knee, and hip. Specific indications are:

Shoulder: Bankart repair, SLAP lesion repair, acromio- clavicular separation, rotator cuff repair, capsule repair or capsulolabral reconstruction, biceps tenodesis, deltoid repair, pectoralis major repair.

Wrist/Hand: Scapholunate ligament reconstruction, ulnar/radial collateral ligament reconstruction.

Ankle/Foot: Lateral stabilization, medial stabilization, Achilles tendon repair/reconstruction, hallux valgus reconstruction, mid- and forefoot reconstruction.

Elbow: Ulnar or radial collateral ligament reconstruction, biceps tendon reconstruction, Lateral epicondylitis repair

Knee: Medial collateral ligament repair, lateral ligament repair, posterior oblique ligament repair, joint capsule closure, iliotibial band tenodesis, and patellar ligament/tendon repair, medial patellofemoral ligament (MPFL) repair or reconstruction, quadriceps tendon repair.

Hip: Proximal hamstring repair

The Ventix Suture Anchor is a two-piece design consisting of the vented body and the threaded tip preloaded with suture. The anchor will be offered in three sizes: 3.5mm, 4.75mm, and 5.5mm and is manufactured from polyetheretherketone (PEEK). The Ventix Suture Anchor will be loaded onto a disposable inserter and will be available with #2 MaxBraid or 1.5mm ForceFiber OrthoTape suture.

The provided document is a 510(k) premarket notification for the Ventix Suture Anchor. It primarily focuses on demonstrating substantial equivalence to legally marketed predicate devices, rather than establishing acceptance criteria and detailed study results for the device's performance against specific metrics.

Therefore, much of the requested information about acceptance criteria, detailed study results, sample sizes for test and training sets, ground truth establishment, expert qualifications, adjudication methods, and MRMC studies cannot be extracted from this document.

However, I can provide the limited information available regarding performance testing:

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

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

This information is not provided in the document. The document only mentions that non-clinical laboratory testing was performed using the Ventix Suture Anchors and predicate devices for comparison.

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)

This information is not applicable as the document describes non-clinical mechanical testing, not a study involving expert assessment of medical images or patient outcomes.

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

This information is not applicable as the document describes non-clinical mechanical testing, not a study involving human readers or subjective assessments.

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

There was no MRMC comparative effectiveness study done. The document explicitly states "Clinical Tests - None provided as a basis for substantial equivalence." The testing described is non-clinical mechanical testing.

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

This information is not applicable. The device is a physical suture anchor, not an algorithm or AI system. The testing described is mechanical performance.

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

For the non-clinical pull-out strength testing, the "ground truth" would be the measured mechanical pull-out strength values obtained directly from the testing equipment. This is objective data.

8. The sample size for the training set

This information is not applicable. The device is a physical product, not an AI or machine learning algorithm that requires a training set.

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

This information is not applicable as there is no training set for a physical device.

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