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The KLS Martin LINOS Wrist System is indicated for use in forearm fractures, osteotomies, and arthrodeses. It is intended for adults, and children (2-12 years) and adolescents (12-21 years) in which growth plates have fused or in which growth plates will not be crossed by fixation.

The KLS Martin LINOS Wrist System consists of metallic plates used in conjunction with bone screws and locking pins intended for the internal fixation, alignment, stabilization, reconstructive osteotomies of the distal radius and/or ulna. Plates are manufactured from Ti-6Al-4V or CP Titanium. Plates are pre-contoured to accommodate patient anatomy and are available in various shapes and dimensions. The system also includes the necessary instruments to facilitate placement of the implants.

This document is a 510(k) summary for the KLS Martin LINOS Wrist System. It outlines the device's characteristics, intended use, and compares it to legally marketed predicate devices to demonstrate substantial equivalence.

Here's an analysis of the provided text in relation to acceptance criteria and study proving device performance:

Crucially, this document does not describe an AI/ML medical device. It describes a traditional Class II orthopedic implant (metallic bone fixation appliance). Therefore, many of the typical acceptance criteria and study aspects for AI/ML devices (like MRMC studies, ground truth establishment for algorithms, training/test set sizes for algorithms, expert adjudication methods for AI performance, etc.) are not applicable to this submission.

The acceptance criteria and study described here are for the mechanical and biocompatibility performance of a physical medical device.

Acceptance Criteria and Device Performance (for a physical orthopedic implant)

Since this is a physical medical device and not an AI/ML algorithm, the "acceptance criteria" table below reflects the types of performance metrics that would be relevant for such a device, and how its performance is typically proven.

Study Information (as applicable to a non-AI/ML medical device 510(k))

Since the provided document is a 510(k) summary for a physical orthopedic implant, not an AI/ML device, many of the requested points below (especially those related to AI/ML specific studies like MRMC or standalone algorithm performance) are not applicable or are addressed by the foundational regulatory framework for traditional medical devices.

1. Sample size used for the test set and the data provenance:

   • Test Set (for mechanical testing): The document states "Comparative head-to-head static and dynamic bench testing was conducted on the subject and predicate...". It doesn't specify the exact sample size (N number of implants tested), but standard mechanical testing for medical devices typically involves a statistically robust number of samples to demonstrate equivalence or superiority according to relevant ISO/ASTM standards.
   • Data Provenance: The studies are bench tests conducted in a laboratory setting, not on patient data. Thus, "country of origin of the data" or "retrospective/prospective" clinical study design are not relevant in this context. The "data" are mechanical test results.

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

   • Not Applicable. For a physical implant device proving mechanical performance, "ground truth" is established by adherence to recognized engineering standards (ASTM, ISO) for material properties, mechanical strength, and biocompatibility. Experts involved would be engineers, material scientists, and toxicologists conducting the tests and interpreting results against these standards, not clinicians establishing "ground truth" on patient images or outcomes.

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

   • Not Applicable. This concept is critical for establishing ground truth in clinical data, especially for AI/ML devices where reader variability exists. For mechanical bench testing, results are objective measurements against defined criteria and standards; adjudication of "readings" is not relevant.

4. 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 a type of study specifically for evaluating the performance of AI/ML diagnostic or prognostic tools when used by human readers (e.g., radiologists interpreting images). The KLS Martin LINOS Wrist System is a surgical implant; it does not involve diagnostic image interpretation or AI assistance for human readers.
   • The document explicitly states: "Clinical testing was not necessary for the determination of substantial equivalence." This reinforces that the evaluation was based on non-clinical (bench) testing.

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

   • Not Applicable. Again, this pertains to an AI/ML algorithm's performance. The device is a physical implant.

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

   • For this physical medical device, "ground truth" for proving substantial equivalence relies on:
     • Standardized Mechanical Test Results: Comparing the device's measured mechanical properties (strength, torque, pullout) to those of the predicate device, as defined by ASTM and ISO standards.
     • Biocompatibility Standards (ISO 10993-1:2018): Ensuring the materials meet safety criteria for biological interaction.
     • Sterilization Standards (ISO 11137, ISO 17665): Demonstrating the effectiveness of the sterilization process.
     • Packaging Standards (ISO 11607, ASTM D4169): Verifying package integrity and shelf life.

7. The sample size for the training set:

   • Not Applicable. This concept is for AI/ML models. This device does not use a training set.

8. How the ground truth for the training set was established:

   • Not Applicable. This concept is for AI/ML models. This device does not use a training set.

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