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The SPS Monoaxial Locking Plates in the Stryker Locked Plating System are intended for use in long bone fracture fixation. The SPS Monoaxial Locking Plates are indicated for fixation of long bone fractures including fractures of the distal radius, the proximal humerus, the distal tibia, proximal tibia and the distal femur.

This Special 510(k) submission is intended to address modifications to the predicate Stryker Locking Inserts. The AxSOS® Locking Insert is being modified as part of a line extension of the AxSOS® Locked Plating System. The AxSOS® Locked Plating System contains 3mm Locking Inserts to which changes are being made.

The provided text describes a Special 510(k) submission for a line extension of 3mm locking inserts for the AxSOS® Locked Plating System. This type of submission is for modifications to a legally marketed device that do not alter the intended use or fundamental scientific technology. Therefore, the "study" conducted is a demonstration of comparable mechanical and functional properties to predicate devices, rather than a clinical study involving human subjects or AI performance.

Here's an analysis based on the provided text, addressing your points:

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

The document does not explicitly state quantitative "acceptance criteria" for the modified device in terms of specific performance thresholds (e.g., minimum tensile strength, fatigue life). Instead, the performance is evaluated in comparison to predicate devices. The implicit acceptance criterion is that the modified device demonstrates comparable mechanical and functional properties to the predicate devices.

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document does not specify the sample size used for the mechanical and functional testing. It also does not provide details on data provenance (e.g., country of origin) or whether it was retrospective or prospective, as it pertains to engineering bench testing rather than clinical study data.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)

This question is not applicable to this type of submission. "Ground truth" established by experts (like radiologists) is relevant for diagnostic devices, particularly those involving image analysis or clinical assessments. This submission is for a medical implant (bone plates and screws), and the evaluation is based on engineering principles and mechanical testing, not expert interpretation of clinical data.

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

This question is not applicable. Adjudication methods are relevant for resolving discrepancies in expert interpretations, typically in clinical ground truth establishment. For mechanical testing, the results are typically quantitative and objective, and do not involve human adjudication in the same way.

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. MRMC studies are used to evaluate diagnostic systems, especially those assisted by AI, by comparing the performance of multiple human readers on multiple cases. This submission is for a mechanical medical device, not an AI-powered diagnostic tool.

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

No standalone algorithm performance study was done for the same reasons as above. This is not an AI/algorithm-based device.

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

As discussed, "ground truth" in the clinical sense is not directly applicable. The "ground truth" for the assessment of this device is based on established engineering standards and direct physical measurements from mechanical and functional testing. The comparable performance to predicate devices serves as the benchmark.

8. The sample size for the training set

This question is not applicable. Training sets are used for machine learning models (AI). This device is a mechanical implant and does not involve any AI components or machine learning.

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

This question is not applicable, as there is no training set for an AI model.

In summary:

This 510(k) submission is for a modification to a mechanical implant. The "study" involved mechanical and functional bench testing to demonstrate the modified device's performance is comparable to its predicate devices. Details regarding specific test parameters, sample sizes for testing, or objective acceptance criteria are not provided in this summary, but the overarching conclusion is that comparable performance was demonstrated. The concepts of expert ground truth, adjudication, MRMC studies, or AI algorithm performance are not relevant to this type of device and submission.

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