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Cemex System Genta Fast Bone Cement is indicated for the fixation of prostheses to living bone in the second stage of a two-stage revision for total joint arthroplasty after the initial infection has been cleared.

The individual chemical constituents in Cemex System Genta Fast bone cement are identical to those in the predicate Centa / Cemex System Genta bone cement (#K033596). The liquid component contains methylmethacrylate, N-N dimethyl p-toluidine, and hydroquinone. The dry powder component contains polymethylmethacrylate, barium sulphate, benzoyl peroxide and gentamicin sulphate. The only difference is that the predicate Cemex Genta / Cemex Genta System has a 2.7:1 powder-to-liquid ratio compared to the 2.4:1 ratio the new Cemex System Genta Fast product. The powder-to-liquid ratio reduction results in a quicker setting time to accommodate various application techniques. Use of Cemex System Genta Fast bone cement takes place in two consecutive stages. During the first stage, the glass ampoule containing the liquid monomer is broken to allow the component to flow into the chamber containing the powdered constituents. The device is then used as a closed manual mixing device. Mixing is accomplished by firmly striking the device against the palm of the hand and mating at each strike. In re second stage, the container is attached to an application gun device and used as a syringe while the cement is still in a semi-fluid state.

The provided document is a 510(k) summary for the Tecres Cemex® System Genta Fast bone cement. It describes the device, its intended use, and substantial equivalence to a predicate device. However, it does not contain information about a study with acceptance criteria and device performance in the context of an AI/ML medical device.

The document discusses the physical and chemical properties of the bone cement and its comparison to a predicate device. The "performance testing" mentioned refers to engineering and material science tests to ensure the bone cement meets specific standards (ISO 5833 and ASTM 451-99) and that gentamicin release is comparable to the predicate. This is typical for a traditional medical device, not an AI/ML device.

Therefore, I cannot provide the requested information for an AI/ML device based on the given input, as the document does not describe such a device or study.

Here's why the specific questions cannot be answered from the provided text:

1. A table of acceptance criteria and the reported device performance: The document states that "Performance testing shows that the proposed device is equivalent to the predicate and meet the requirements of ISO 5833 and ASTM 451-99." It also mentions "gentamicin release is within the safety range and comparable to the predicate Cemex Genta." This refers to material and chemical properties, not diagnostic performance metrics like sensitivity, specificity, or AUC which would be relevant for an AI/ML device. Specific numerical acceptance criteria or performance metrics for these standards are not detailed in this summary.
2. Sample sized used for the test set and the data provenance: Not applicable, as this is a non-AI bone cement. No "test set" of patient data is mentioned for performance evaluation.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for an AI/ML device would be established by human experts or pathology, which is not relevant here.
4. Adjudication method: Not applicable. This relates to expert review in AI/ML studies.
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 is for AI-assisted human reading.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This describes AI performance without human intervention.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For a bone cement, "ground truth" would relate to its physical properties meeting specifications, potentially in vivo performance in animal studies or clinical trials for safety and efficacy, but not in the sense of diagnostic ground truth for an AI/ML system.
8. The sample size for the training set: Not applicable. No AI model is trained here.
9. How the ground truth for the training set was established: Not applicable. No AI model is trained here.

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