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The Tzoar Negative Pressure Wound Therapy (NPWT) System is indicated for wound management via the application of negative pressure to the wound by the removal of wound exudate, infectious materials, and tissue debris from the wound bed. The Tzoar 207 Negative Pressure Wound Therapy (NPWT) System is indicated for the following wound types: chronic, acute, traumatic, subacute and dehisced wounds, partial-thickness burns, ulcers (such as diabetic or pressure), flaps and grafts.

The Tzoar 207 Negative Pressure Wound Therapy (NPWT) System includes a pump and two types of dressings: Tzoar NPWT Foam Kits and Tzoar NPWT One Piece Dressing. The Tzoar 207 NPWT pump is a portable, battery powered pump which may promote wound healing through the drainage and removal of wound exudates, infectious material, and tissue debris from the wound bed using continuous and/or intermittent negative pressure. The Tzoar NPWT One Piece Dressing and the Tzoar NPWT Foam Kits are both Tzoar Wound Dressings intended to be used with an NPWT device to manage acute and chronic wounds.

The provided document is a 510(k) premarket notification for the Tzoar 207 Negative Pressure Wound Therapy (NPWT) System. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device, rather than proving the device meets specific performance acceptance criteria through clinical studies directly, especially for AI/ML devices. Therefore, much of the requested information regarding acceptance criteria for AI models, study design, expert ground truth, and specific performance metrics for AI will not be present in this document.

The document mainly covers the technological characteristics, performance tests of the device's physical functions, biocompatibility, and electrical safety.

Here's an analysis based on the available information:

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

The document does not explicitly state "acceptance criteria" in the context of an overall device performance metric that would be suitable for an AI/ML device. Instead, it lists several performance tests conducted on the physical device components. The conclusion drawn from these tests is that the device is "performing as intended" and is "substantially equivalent to the predicate."

Here's a table summarizing the tests mentioned and the general conclusion:

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 describe a "test set" in the context of data for an AI/ML device. The "tests" mentioned are for the physical components and functionality of the NPWT system. The sample sizes for these physical performance tests are not specified in this summary document. Data provenance is not applicable as this is a device clearance, not an AI model clearance.

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)

Not applicable. This device is a Negative Pressure Wound Therapy system, which is a physical medical device. It does not appear to incorporate AI/ML technology that would require expert-established ground truth on a test set of data.

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

Not applicable, as there is no mention of a test set requiring adjudication for AI/ML performance.

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 device is a physical wound therapy system and does not involve human "readers" or AI assistance in interpretation.

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

Not applicable, as this is a physical medical device, not an algorithm or AI.

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

Not applicable. The "ground truth" for this device would be its ability to perform its stated functions (e.g., maintain pressure, seal, battery life) according to engineering specifications and relevant standards. This is assessed through physical performance tests, not through expert review of data or pathology.

8. The sample size for the training set

Not applicable. This is a physical medical device, not an AI/ML model.

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

Not applicable. This is a physical medical device, not an AI/ML model.

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