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Intended Use
The non-absorbable suture anchors are intended to reattach soft tissue to bone in orthopedic surgical procedures.

Indications for Use
The device may be used in either arthroscopic or open surgical procedures. After the suture is anchored to the bone, it may be used to reattach soft tissue, such as ligaments, tendons, or joint capsules to the bone. The suture anchor systems thereby stabilize the damaged soft tissue, in conjunction with appropriate postoperative immobilization, throughout the healing period.

The CONMED TruShot™ with Y-Knot® Shallow All-Suture Anchor is manufactured from High Strength Flat Braided Suture threaded with either one #0 (3.5 metric) or one #2-0 (3 metric) Hi-Fi® suture strand with needles. Each All-Suture Anchor is preloaded on a disposable inserter, and pre-assembled with a disposable drill bit and guide handle. The anchor, suture(s) with needles, inserter, drill bit, and guide handle are pre-assembled and provided sterile, intended for single-use. The device is EO Sterilized.

The provided document is a 510(k) Summary for a medical device (TruShot™ with Y-Knot® Shallow All-Suture Anchor) and describes performance data to demonstrate substantial equivalence to a predicate device, rather than defining acceptance criteria and a study to prove a device meets those acceptance criteria.

Therefore, many of the requested details about acceptance criteria, study design for proving it, and specifics related to AI/algorithm performance (like effect size with AI assistance, standalone performance, training set details) are not applicable or extractable from this type of regulatory submission.

However, I can extract information about the types of performance testing conducted to support the device's clearance.

Here's what can be extracted:

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

The document does not provide specific quantitative acceptance criteria or detailed reported device performance values. It states that "Testing has been completed to demonstrate that the TruShot™ with Y-Knot® Shallow All-Suture Anchor performs as intended and is substantially equivalent to the predicate device." It also mentions "met the endotoxin limits" without specifying the limit itself.

2. Sample size used for the test set and the data provenance

The document does not specify sample sizes for any of the tests. It also does not discuss data provenance in terms of country of origin or retrospective/prospective nature, as these tests are typically bench or lab-based for medical devices like suture anchors.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

This information is not applicable. The device is a physical medical implant, not an AI or diagnostic tool requiring expert interpretation for ground truth.

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

This information is not applicable for this type of device 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 such study was done or is relevant to this physical medical device. This is typically applicable to diagnostic AI devices.

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

No standalone algorithm performance was done. This is not an AI device.

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

For mechanical and material properties (e.g., Ultimate Fixation Strength, Cyclic testing), the "ground truth" would be established by validated test methods and physical measurements, compared against established standards or performance of the predicate device. For biological tests (e.g., pyrogen, biocompatibility, sterilization), it would be against regulatory limits and specified testing standards.

8. The sample size for the training set

This information is not applicable as this is not an AI/machine learning device.

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

This information is not applicable as this is not an AI/machine learning device.

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