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The Arthrex SutureTak Suture Anchors are intended to be used for suture (soft tissue) fixation to bone in the foot, ankle, knee, hand, wrist, elbow, shoulder, and hip.

Shoulder: Rotator Cuff Repair, Bankart Repair, SLAP Lesion Repair, Biceps Tenodesis, Acromio-Clabicular Separation Repair, Deltoid Repair, Capsular Shift or Capsulolabral Reconstruction

Foot/Ankle: Lateral Stabilization, Medial Stabilization, Achilles Tendon Repair, Metatarsal Ligament Repair, Hallux Valgus reconstruction, digital tendon transfers, Mid-foot reconstruction

Knee: Medial Collateral Ligament Repair, Lateral Ligament Repair, Patellar Tendon Repair, Posterior Oblique Ligament Repair, Iliotibial Band Tenodesis

Hand/Wrist: Scapholunate Ligament Reconstruction, Carpal Ligament Reconstruction of collateral ligaments, Repair of Flexor and Extensor Tendons at the PIP, DIP, and MCP joints for all digits, digital tendon transfers

Elbow: Biceps Tendon Reattachment, Ulnar or Radial Collateral Ligament Reconstruction

Hip: Capsular repair, Acetabular Labral repair

The Arthrex SutureTak Suture Anchors share the same design features, materials, and intended use as the predicates. The anchors are composed of Polyetheretherketone (PEEK), or PLDLA/βTCP and are preloaded on a driver with nonabsorbable suture. The anchors range from 2.0mm – 3.0mm in diameter and 4.9mm – 14.5mm in length.

The provided document is a 510(k) summary for the Arthrex SutureTak Suture Anchors. This document describes the device, its intended use, and claims substantial equivalence to predicate devices based on design, materials, and intended use. It also mentions testing data to support performance.

However, the document does not contain the detailed acceptance criteria and the study results in the format requested, particularly for an AI/ML powered device. The "acceptance criteria" discussed in this document refer to the criteria for demonstrating substantial equivalence to predicate medical devices, rather than performance metrics for an AI/ML algorithm.

Specifically, the document lacks the following information for an AI/ML device study:

1. A table of acceptance criteria and reported device performance: While the document states "the submitted tensile testing, fatigue testing, and degradation testing data demonstrates that the performance of the proposed devices meets or exceeds the predicate device for the desired indications," it does not provide a table with specific acceptance criteria and detailed performance metrics. The device in question is a physical suture anchor, not an AI/ML algorithm, so typical AI performance metrics like sensitivity, specificity, AUC, etc., are not applicable here.
2. Sample size used for the test set and data provenance: No such information is provided as this is not an AI/ML study.
3. Number of experts used to establish ground truth and their qualifications: Not applicable for this type of device submission.
4. Adjudication method: Not applicable.
5. MRMC comparative effectiveness study: Not applicable.
6. Standalone performance study: Not applicable in the context of an AI/ML algorithm's standalone performance. The document describes pre-market testing for a physical device.
7. Type of ground truth used: Not applicable in the AI/ML context. Performance is based on physical property testing (tensile, fatigue, degradation).
8. Sample size for the training set: Not applicable.
9. How ground truth for the training set was established: Not applicable.

In summary, the provided document is a regulatory submission for a physical medical device (suture anchors) and therefore does not contain the information requested for describing the acceptance criteria and study proving an AI/ML device meets those criteria.

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