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The reprocessed fixation device is indicated for use with adults and pediatric patients and intended for fracture fixation (open and closed) fractures and disease generally resulting in joint contractures of loss of range and fractures requiring distraction; post-traumatic joint contracture which has resulted in loss of rantion; pseudoarthrosis or non-union of long bones; limb lengthening by epiphyseal or metaphyseal distraor joint athrodosis, correction of segmental bony of soft tissues; and management of committed intra-articular fractures of the distal radius.

SterilMed's reprocessed external fixation devices consists of the standard bridge elements (rods, articulating and telescoping components), and connection elements (clamps) contained in the original manufacturer's system. Some of the components are MR safe and made of non-magnetic materials. MR safe components are intended for use in the MR environment. Note: Only the non-patient contact, external frame elements are the subject of this submission, the anchorage pins and wire elements are not included in the scope of this submission

The provided text describes a 510(k) premarket notification for a Reprocessed External Fixation Device (K081342) by SterilMed, Inc. This submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving performance against specific acceptance criteria through a clinical study with human subjects or an AI-based algorithm.

Therefore, many of the requested sections (e.g., sample sizes for test/training sets, number of experts, adjudication methods, MRMC studies, standalone algorithm performance, ground truth types for AI) are not applicable to this type of device and submission.

Here's a breakdown of the available information:

1. Table of Acceptance Criteria and Reported Device Performance

This submission does not provide a table with specific acceptance criteria in terms of performance metrics (e.g., sensitivity, specificity, accuracy) for a diagnostic device, nor does it report device performance in that way. Instead, it focuses on demonstrating substantial equivalence to an existing predicate device (Smith & Nephew Jet-X® External Fixation System) through functional and safety testing.

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

• Not Applicable. This is not a study assessing diagnostic performance on a test set of data. The "test set" here refers to representative samples of the reprocessed physical devices used for functional and safety testing.
• The document states "Representative samples of reprocessed external fixation constructs were tested." The specific number of samples is not provided.
• Data Provenance: Not applicable in the context of data for an AI/diagnostic device. The "data" here refers to the results of physical device testing. The testing was conducted by SterilMed, Inc. (Maple Grove, MN, USA).

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

• Not Applicable. This submission does not involve establishing ground truth from expert consensus for a diagnostic test. The testing involves physical properties and functionality of a medical device.

4. Adjudication method for the test set

• Not Applicable. No expert adjudication method is relevant for this type of device and submission.

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

• Not Applicable. This device is a reprocessed external fixation device, not an AI-assisted diagnostic tool.

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

• Not Applicable. This is a physical medical device, not an algorithm.

7. The type of ground truth used

• For Physical Device Testing: The "ground truth" for the functional and safety testing would be established by validated engineering specifications, performance standards, and comparisons against the original manufacturer's specifications and the predicate device's known performance characteristics. The document mentions "appropriate functional characteristics" and "validated functional testing."

8. The sample size for the training set

• Not Applicable. This is not an AI/machine learning device.

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

• Not Applicable. This is not an AI/machine learning device.

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