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The Arthrex RetroFusion Screw is intended to fix small bony or apical chondral fragments in the foot, ankle, upper extremities, hand, and wrist, where such fragments are not under tension or load-bearing. These devices are used in cases of osteochondritis dissecans and osteochondral fragments, fixation of fractures, 1st metatarsal (bunionectomy osteotomies), cuneiform bones, inherently stable osteotomies, and fusions of the phalanges, metatarsals, metacarpals, carpal bones, tarsal bones, ankle, and wrist. The devices can be used for inherently stable intramedullary stabilization of joint arthroplasty (resection) or fusion for the treatment of digital deformities of the foot or hand. This device is also used in inherently stable long bone fractures such as the femur, fibula, tibia, radius and ulna, including the diaphyseal, epiphyseal, and metaphyseal areas.

The Arthrex RetroFusion Screw is an implant with a dual threaded design and ranges in size from 20 to 32mm in length. The RetroFusion screw is inserted between the proximal and middle phalanges, so the opposing threads fixate on the phalangeal canal of the toe and compress the joint.

This document is a 510(k) premarket notification for a medical device called the "Arthrex RetroFusion Screw." It is a regulatory submission to the FDA (Food and Drug Administration) and contains information about the device's intended use, design, and a summary of performance testing to demonstrate substantial equivalence to a predicate device.

Here's an analysis to extract the requested information, while noting that this document does not describe an AI/ML device, but rather a physical surgical screw. Therefore, many of the requested fields related to AI/ML device studies (like sample sizes for test/training sets, expert consensus for ground truth, MRMC studies, etc.) will not be applicable or present in this type of submission.

The document primarily focuses on demonstrating that the new device (Arthrex RetroFusion Screw) is substantially equivalent to a previously cleared predicate device (K050259: Arthrex Bio-Pin). This is typically done through non-clinical performance testing (e.g., mechanical testing, biomaterial testing) and comparison of design and intended use, rather than clinical studies with human readers or AI algorithms.

Acceptance Criteria and Study for Arthrex RetroFusion Screw (as derived from a 510(k) submission for a non-AI/ML device)

(Note: This device is a physical surgical screw, not an AI/ML device. Therefore, many of the requested fields related to AI/ML performance testing, such as expert ground truth, MRMC studies, and separate training/test sets for AI, are not applicable to this document. The information provided below is extracted from the 510(k) summary and reflects the type of testing performed for a physical implant.)

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size for Test Set: Not explicitly stated in the provided 510(k) summary. For mechanical testing like pull-out strength, typically several samples of the device and predicate would be tested according to a validated test method. These are physical samples of the screw, not patient data or images.
• Data Provenance: The document describes non-clinical laboratory testing performed by the manufacturer, Arthrex, Inc., located in Naples, FL, USA. This is an in-vitro (benchtop) study comparing mechanical properties.

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

• Not Applicable (N/A). This is a mechanical device, not an AI/ML diagnostic or image analysis device. "Ground truth" in this context would be objective physical measurements from laboratory equipment, not expert human interpretation.

4. Adjudication Method for the Test Set

• N/A. As this is mechanical testing of a physical device, there is no expert adjudication process. The results are quantitative measurements interpreted against engineering specifications and predicate data.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

• No. This is not an AI/ML device, and therefore, an MRMC study is not relevant or performed for this type of submission.

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

• N/A. This applies to AI/ML algorithms. The device is a physical screw. Its "standalone" performance is assessed through its mechanical properties.

7. The Type of Ground Truth Used

• Objective Mechanical Measurements. For "pull-out testing," the ground truth is the measured force required to extract the screw, obtained using materials testing equipment (e.g., a universal testing machine). This is a direct physical measurement.

8. The Sample Size for the Training Set

• N/A. This concept is for AI/ML models. For a physical device, there isn't a "training set" in the AI sense. Design iterations and prototyping would involve testing many physical samples, but this is part of the product development and verification process, not an AI training phase.

9. How the Ground Truth for the Training Set was Established

• N/A. Not applicable, as there is no "training set" for an AI algorithm.

Summary of what the document does indicate about performance:

The core of the performance evaluation for this physical device is the demonstration of substantial equivalence to an existing legally marketed predicate device (Arthrex Bio-Pin, K050259).

The key performance data explicitly mentioned is:

• "Pull-out testing demonstrates that the pull-out strength of the Arthrex RetroFusion Screw is significantly greater than the predicate."

This statement highlights that at least one critical mechanical property (pull-out strength, important for bone fixation) was tested, and the new device performed better than the predicate, thus supporting its safety and effectiveness for its intended use. The 510(k) process relies on demonstrating that the new device is as safe and effective as a predicate device, and often, this involves showing comparable or superior performance in relevant non-clinical tests.

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