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The Aesculap SternumFix Sternal Closure System is intended for use in primary or secondary closure/ repair of the sternum following sternotomy or fracture of the sternum to stabilize the sternum and promote fusion.

The Aesculap Sternal Closure System consists of an implantable single use clamp made of titanium alloy (TiAl6V4) and a specially designed applicator instrument.

The provided text describes a medical device called the "SternumFix Sternal Closure System" and its substantial equivalence to predicate devices, but it does not contain a detailed study proving the device meets specific acceptance criteria in the format requested.

Here's an analysis based on the available information and a breakdown of why some requested fields cannot be filled:

The document (K063017) is a 510(k) summary, which typically focuses on demonstrating "substantial equivalence" to a legally marketed predicate device rather than presenting a comprehensive clinical trial with explicit acceptance criteria and detailed performance metrics against those criteria.

However, based on the text provided:

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

Note: The document states, "Mechanical testing of the SternumFix and the predicate Ethicon Stainless Steel proved the efficacy of the new device." This implies that the acceptance criteria for efficacy were met through this comparative mechanical testing. However, the specific numerical thresholds or performance targets for "efficacy" are not provided.

Regarding the other requested information:

• 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 for the mechanical testing or any other test set.
  • It does not specify the data provenance (country of origin, retrospective/prospective). As it's mechanical testing, it's likely laboratory-based rather than patient-based.

• 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 information is not applicable or provided. The "ground truth" for mechanical testing would typically be based on established engineering standards and measurements, not expert human assessment in the way clinical studies requiring image interpretation or diagnosis would.

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

  • This information is not applicable or provided as the primary evidence cited is mechanical testing, not a clinical study involving human judgment that would require adjudication.

• 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, an MRMC comparative effectiveness study was not done. This device is a surgical implant for sternal closure, not an AI-based diagnostic or assistive technology for human readers.

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

  • This information is not applicable. The device is a physical implant, not an algorithm.

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

  • For the "efficacy" claim, the ground truth was established through mechanical testing against a predicate device. This would involve objective physical measurements rather than expert consensus, pathology, or outcomes data in a clinical sense.

• 8. The sample size for the training set:

  • This information is not applicable. The device is a physical implant, not an AI algorithm that requires a training set.

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

  • This information is not applicable for the same reason as point 8.

In summary: The provided 510(k) summary focuses on demonstrating substantial equivalence primarily through a comparison of technological characteristics and mechanical testing against a predicate device. It does not detail specific acceptance criteria in a quantitative manner or describe a clinical study with elements like human experts, adjudication, or AI performance, as these are generally not required for this type of device and regulatory submission.

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