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Spacer-S is intended for use as a temporary (maximum 180 days) shoulder replacement in patients undergoing a two-stage procedure due to a septic process.

The device is intended for use in conjunction with systemic antimicrobial antibiotic therapy (standard treatment approach to an infection) as defined by physician and/or surgeon.

Spacer-S is indicated for temporary use (maximum 180 days) as an adjunct to total shoulder replacement and hemi shoulder replacement procedures in skeletally mature patients undergoing a two-stage revision procedure due to a septic process. Spacer-S is only indicated for an implantation period of 180 days or less.

Spacer-S is composed of fully formed gentamicin/polymethylmethacrylate (PMMA) bone cement. The one piece design mimics a hemi-shoulder prosthesis.

The K060535 filing describes the Tecres Spacer-S, a temporary shoulder prosthesis. The information provided primarily focuses on its device description, intended use, and a demonstration of substantial equivalence to a predicate device through performance testing, rather than an AI/ML device and its associated acceptance criteria and study data.

Therefore, many of the requested categories (e.g., sample size for test/training sets, experts for ground truth, MRMC studies, standalone performance, etc.) are not applicable or cannot be extracted from the provided text, as this is a medical device approval for a physical implant, not a software or AI/ML diagnostic tool.

However, I can extract the relevant performance data that was used to establish substantial equivalence.

Here's the information that can be extracted or inferred from the provided text:

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

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

This information is not provided in the document. The performance testing refers to mechanical and material evaluations, not clinical trials with human subjects in the typical sense of test sets for AI/ML.

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/provided. Ground truth, in the context of this traditional medical device, is established through engineering and laboratory testing (e.g., measuring physical properties like strength and antibiotic release), not through expert consensus on diagnostic images or clinical outcomes.

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

This information is not applicable/provided. Adjudication methods are relevant for studies involving human interpretation or clinical endpoints, which is not the focus of the performance testing described for this device.

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

This information is not applicable. This is a physical medical implant, not an AI or imaging diagnostic device.

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

This information is not applicable. This is a physical medical implant, not an algorithm.

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

For the performance data, the "ground truth" would be established through engineering standards and laboratory measurements of the device's mechanical properties (fatigue strength, static strength) and its antibiotic release characteristics. There is no mention of clinical pathology or outcomes data being used to define the "ground truth" for these specific performance tests.

8. The sample size for the training set

This information is not applicable. There is no "training set" in the context of this traditional medical device approval based on performance testing of the device itself.

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

This information is not applicable. As there is no "training set," there is no ground truth to establish for it.

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