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Metal Bone Screw is indicated for the fixation of clavicle, scapula, pelvis, humerus, ulna, radius, femur, tibia, fibula, metacarpals, metatarsals and phalanges fractures.

Metal Bone Screw are used to fasten plates onto bones, or, as lag screws, to hold bone fragments together. The screws are differentiated by the manner in which they are inserted into bone, their function, their size, and the type of bone they are intended for. Metal Bone Screw consists of a series of screws with different sizes and structures, which is designed according to the anatomical characteristics of human bones. In clinical practice, the bone screw can be used alone or in combination with the bone plate, which acts as a temporary internal support, provides a stable local environment for the fractured end, and creates conditions for the healing of the fractured end. Metal Bone Screw are made of Ti-6A1-4V ELI following ASTM F136. Metal Bone Screw is provided as non-sterile. The implants are intended for single-use only, while the instruments are reusable.

This document is a 510(k) premarket notification for a medical device called "Metal Bone Screw." It is a regulatory filing with the FDA to demonstrate substantial equivalence to a legally marketed predicate device, not a study evaluating AI or software performance. Therefore, most of the requested information regarding acceptance criteria, AI study design, human-in-the-loop performance, and training/test set details is not applicable to this document.

However, I can extract the relevant information from this document:

Device Description and Purpose:

The "Metal Bone Screw" is a medical device used for the fixation of various bone fractures. It is made of Ti-6A1-4V ELI (a titanium alloy).

Acceptance Criteria and Device Performance (Based on this document, these refer to mechanical and biocompatibility testing for a hardware device, not AI performance):

This document describes the regulatory process for a physical medical device (Metal Bone Screw), not a software or AI-driven device. Therefore, the "acceptance criteria" and "device performance" are established through non-clinical performance data (mechanical testing and biocompatibility testing) to demonstrate substantial equivalence to a legally marketed predicate device.

Table of Acceptance Criteria and Reported Device Performance (as inferred from the document for a medical hardware device):

• Insertion/removal Test (per ASTM F543-17)
• Pullout Test (per ASTM F543-17) | Tests performed "to demonstrate substantially equivalent of safety and efficacy with the predicate device". (Implied successful performance to meet substantial equivalence, specific numerical results are not detailed here). |

Details Not Applicable to This Document (as it's a hardware device 510(k) not an AI study):

• Sample size used for the test set and the data provenance: Not applicable. This refers to mechanical and biocompatibility testing of the physical device, not an AI test set.
• Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This document does not describe a study involving expert-established ground truth for a test set in the context of an AI device.
• Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
• 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: Not applicable. This is for AI-assisted diagnostic devices.
• If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is for AI algorithm performance.
• The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable in the context of an AI test set. For this hardware device, the "ground truth" for demonstrating substantial equivalence is established through adherence to recognized standards (ASTM) and a comparison of performance characteristics to a predicate device.
• The sample size for the training set: Not applicable, as this is a hardware device, not an AI model.
• How the ground truth for the training set was established: Not applicable.

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