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The exsalt™ T7 Wound Dressing is indicated for use in partial and full thickness wounds, including decubitus ulcers, venous stasis ulcers, diabetic ulcers, first and second degree burns, grafts and donor sites, or other acute or chronic wounds. The dressing may be used over debrided and grafted wounds. The exsalt™ T7 Wound Dressing provides an antibacterial barrier that inhibits bacterial growth in the dressing for up to 7 days.

Exciton Technologies Inc. has developed the exsalt™ technology, a proprietary chemical process, which deposits oxidized silver species onto a non-woven polyester with gray Delnet® HDPE mesh layers thermally bonded on both sides. Silver in the exsalt™ T7 Wound Dressing inhibits bacterial growth in the dressing. The concentration of the silver and oxidized silver species on the dressing is 0.4 mg/cm² (4.5% w/w). The exsalt™ T7 Wound Dressing is known to be effective in vitro against Staphylococcus aureus, Enterococcus faecalis, Staphylococcus epidermidis, Pseudomonas aeruginosa, and Acinetobacter baumannii for up to 7 days. The exsalt™ T7 Wound Dressing consists of 2 outer layers of HDPE with an inner layer of polyester which are all silver-coated. The skin-contacting materials in both the exsalt™ T7 Wound Dressing and the predicate are the same. The exsalt™ T7 Wound Dressing is sterilized by gamma irradiation.

The provided document is a 510(k) summary for a medical device (exsalt™ T7 Wound Dressing). This type of submission focuses on demonstrating substantial equivalence to a predicate device, rather than proving a device meets specific performance criteria through a standalone clinical study or multi-reader multi-case (MRMC) study for an AI algorithm.

Therefore, many of the requested categories related to AI algorithm evaluation, such as acceptance criteria in terms of diagnostic performance metrics, sample sizes for test/training sets, expert adjudication methods, and MRMC study details, are not applicable to this type of device and submission.

However, I can extract the relevant information regarding performance testing that was conducted.

1. Table of Acceptance Criteria and Reported Device Performance

Study Proving Device Meets Acceptance Criteria:

The device's performance is not proven through a single, comprehensive study with explicit acceptance criteria for diagnostic metrics. Instead, the submission relies on demonstrating substantial equivalence to a predicate device (exsalt™ SD7 Wound Dressing, K103067 and K083870) through a series of performance tests and by asserting that differences in design (specifically the substrate configuration) do not raise new issues of safety or effectiveness.

The document states: "All performance characteristics of the exsalt™ T7 Wound Dressing are the same as the predicate(s)." and "The exsalt™ T7 Wound Dressing raised no new safety concerns relative to biocompatibility. Testing performed on the exsalt™ SD7 Wound Dressing (K083870) showed that it was nontoxic, non-irritant, and did not elicit a sensitization response."

The antibacterial effectiveness for exsalt™ T7 is specifically mentioned as being effective in vitro against the listed bacteria for up to 7 days, which is consistent with the intended function.

Details Not Applicable for this 510(k) Submission:

The following information types are typically relevant for AI/software as a medical device (SaMD) submissions involving diagnostic or screening performance, but are not provided or applicable in this 510(k) for a wound dressing, which focuses on material properties, safety, and functionality claims based on in vitro testing and equivalence to an existing product:

2. Sample size used for the test set and the data provenance: Not applicable. Performance tests were likely conducted on laboratory samples of the dressing, not a patient test set.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No "ground truth" in the clinical diagnostic sense was established.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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 not an AI device.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an AI algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not applicable. "Ground truth" was likely defined by standardized laboratory test results for material and antimicrobial properties.
8. The sample size for the training set: Not applicable. This is not an AI device that requires a training set.
9. How the ground truth for the training set was established: Not applicable.

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The exsalt™ SD7 Wound Dressing is indicated for the management of partial and full thickness wounds, including decubitus ulcers, venous stasis ulcers, diabetic ulcers, first and second degree burns, grafts and donor sites, or other acute or chronic wounds. The dressing may be used over debrided and grafted wounds.

Exciton Technologies Inc. has developed the exsalt™ technology, a proprietary chemical process, which deposits oxidized silver species onto a non-woven needled polyester coated with gray Delnet® HDPE mesh layers on both sides (STRATEX®). Silver in the exsalt™ SD7 Wound Dressing inhibits microbial growth in the dressing. The concentration of the silver and oxidized silver species on the dressing is 0.4 mg/cm² (2.5% w/w). The exsalt™ SD7 Wound Dressing has been shown to be effective in vitro against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Enterococcus faecalis when they are in direct contact with the dressing. In addition, in vitro data have demonstrated that exsalt™ SD7 Wound Dressing maintains its antibacterial activity for up to 7 days against Pseudomonos aeruginosa and Staphylococcus aureus.

Here's a breakdown of the acceptance criteria and study information for the exsalt™ SD7 Wound Dressing based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: The document does not specify the exact sample sizes for each in-vitro test (e.g., how many dressings tested per bacterial strain, or how many iterations for physical tests). It only states that "in vitro data have demonstrated..."
• Data Provenance: The studies were in vitro (laboratory-based) and conducted by the manufacturer, Exciton Technologies Inc., based in Canada. Given the context of a premarket notification, these are prospective studies conducted to support the device's claims.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

• This information is not provided in the document. For in-vitro studies, ground truth is typically established by the scientific methodology itself (e.g., bacterial count reduction based on established laboratory protocols), rather than by expert consensus on individual "cases."

4. Adjudication Method for the Test Set

• This information is not applicable as the studies described are in-vitro efficacy and physical performance tests, not human-reader-based assessments requiring 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 wound dressing, and the studies described are primarily in-vitro performance and biocompatibility assessments, not studies involving AI-assisted human readers.

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

• Not applicable. This device is a physical wound dressing and does not involve an algorithm or AI.

7. The Type of Ground Truth Used

• The ground truth for the performance tests (e.g., antimicrobial activity, physical properties) was established through laboratory-based, scientific measurement and observation using validated protocols (e.g., bacterial culture methods for antimicrobial efficacy, standardized tests for absorptive capacity). For biocompatibility, it was based on standardized biological reactivity tests.

8. The Sample Size for the Training Set

• Not applicable. This device does not involve machine learning or AI models, therefore there is no "training set."

9. How the Ground Truth for the Training Set Was Established

• Not applicable, as there is no training set for this device.

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The exsalt™ Wound Dressing is indicated for first aid to help minor cuts, scrapes, abrasion, lacerations and scalds.

The exsalt™ Wound Dressing consists of 2 outer layers of HDPE with an inner layer of absorbent polyester, all coated with silver. Exciton Technologies Inc. has developed exsalt™ technology; a proprietary chemical process, which deposits oxidized silver species onto the non-woven polvester coated with Delnet® HDPE mesh layers on both sides (STRATEX®). Silver in the exsalt™ SD7 Wound Dressing inhibits microbial growth in the dressit™ Wound Dressing has been shown to be effective in vitro against Staphylococcus aureus, Escherichia coli, Pseudomonas aeruginosa, and Enterococcus faecalis.

The provided text describes the "exsalt™ Wound Dressing" and its 510(k) submission. It details performance tests conducted but does not contain information about a study proving the device meets acceptance criteria in the context of an AI/ML device. This document concerns a physical wound dressing, not an AI/ML device.

Therefore, I cannot fulfill the request as it asks for information pertinent to AI/ML device studies (such as sample sizes for test/training sets, experts for ground truth, MRMC studies, standalone performance, etc.) which are not applicable to the provided document about a wound dressing.

The document discusses various performance tests for the physical wound dressing, such as Absorptive Capacity, Moisture Content, Drop Penetration, Adhesion, Abrasion, Silver Content, Anti-microbial (bacterial) Effectiveness, Bactericidal Effectiveness, Biocompatibility, and Biological Reactivity. It states that these characteristics were found to be substantially equivalent to a predicate device and that the dressing showed no new safety concerns. However, it does not present these as specific numerical "acceptance criteria" alongside "reported device performance" in a table as requested for an AI/ML context.

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