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The SNaP Wound Care System is indicated for patients who would benefit from a suction device, particularly as the device may promote wound healing through the removal of excess exudates, infectious material and tissue debris. The SNaP Wound Care System is indicated for removal of small amounts of exudate from chronic, acute, traumatic, subacute and dehisced wounds, partial-thickness burns, ulcers (such as diabetic, venous or pressure), surgically closed incisions, flaps and grafts.

The SNaP® Wound Care System ("SNaP System") is an existing (K081406, K111393, K112341, K 113032) non-powered, portable, single-use suction device intended for wound management via application of negative pressure to the wound for removal of fluids, including wound exudate, irrigation fluids, and infectious materials. The SNaP System utilizes dedicated constant-force springs to mechanically generate the negative pressure gradient. The proposed SNaP Wound Care System will have the same indication for use as the predicate device, the SNaP Wound Care System (K113032). In addition, Spiracur has added the SNaP® Bridge Dressing Kit ("SNaP Bridge Dressing") and SNaP® SecurRing" Hydrocolloid ("SNaP SecurRing") to the SNaP Dressing Kit product family.

This document is a 510(k) summary for the SNaP® Wound Care System, focusing on modifications and additions to the existing device and dressing components. It primarily addresses substantial equivalence to predicate devices and does not contain detailed acceptance criteria and study results in the format requested for proving performance.

Based on the provided text, the device in question is the SNaP® Wound Care System, described as a "Non-powered suction apparatus device intended for negative pressure wound therapy." The submission is for modifications and additions (SNaP® Bridge Dressing Kit and SNaP® SecurRing™ Hydrocolloid) to an already cleared device, along with labeling changes.

Therefore, much of the requested information regarding a study that proves the device meets specific acceptance criteria is not present in this 510(k) summary, as the submission focuses on demonstrating substantial equivalence through bench testing rather than a clinical performance study with predefined acceptance criteria for a new device.

However, I can extract the information that is present:

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

The document does not explicitly state acceptance criteria in a quantitative manner or report specific performance metrics against such criteria in a table format. Instead, it describes various "bench testing" categories performed to ensure "conformance to design specifications" and "substantial equivalence." The performance is generally described qualitatively as being "comparable to the predicate device."

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 mentions "bench testing" but does not specify sample sizes or data provenance (country of origin, retrospective/prospective) for any of the tests conducted.

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 provided. The text describes bench testing, which typically does not involve human expert ground truth establishment in the way clinical studies with diagnostic devices do.

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

This information is not provided. As the testing is bench-based, an adjudication method for human readers would not be 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

There is no mention of a multi-reader multi-case (MRMC) comparative effectiveness study or any AI assistance. The device is a non-powered wound care system, not a diagnostic or AI-powered device.

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

There is no mention of an algorithm or standalone algorithm performance. The device is a physical medical device.

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

For the bench testing described, the "ground truth" would be the engineering specifications and established performance characteristics of the predicate device. The document states that testing was done "to ensure conformance to design specifications" and to assess "ability... to deliver negative pressure wound therapy comparable to the predicate device." No clinical ground truth (like pathology or outcomes data) is mentioned for these bench tests.

8. The sample size for the training set

There is no mention of a training set. This document describes the submission for a physical medical device undergoing bench testing for substantial equivalence, not an AI or diagnostic algorithm that would require a training set.

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

As there is no mention of a training set, this information is not applicable and not provided.

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The SNaP Wound Care System is indicated for patients who would benefit from a suction device, particularly as the device may promote wound healing through the removal of excess exudates, infectious material and tissue debris. The SNaP Wound Care System is indicated for removal of small amounts of exudate from chronic, acute, traumatic, subacute and dehisced wounds, partial-thickness burns, ulcers (such as diabetic or pressure), surgically closed incisions, flaps and grafts.

The SNaP Wound Care System is a non-powered, portable, single-use suction device intended for wound management via application of negative pressure to the wound for removal of fluids, including wound exudate, irrigation fluids, and infectious materials. The SNaP Wound Care System is designed to provide active wound treatment through the removal of excess exudates, infectious material and tissue debris. The SNaP Wound Care System is indicated for removal of small amounts of exudate from chronic, acute, traumatic, subacute and dehisced wounds, partial-thickness burns, ulcers (such as diabetic or pressure), surgically closed incisions, flaps and grafts. The SNaP Wound Care System utilizes dedicated constant-force springs to mechanically generate the negative pressure gradient.

The SNaP Wound Care System is used in conjunction with the SNaP Dressing Kit.

The provided text is a 510(k) summary for the SNaP® Wound Care System, a non-powered, negative pressure wound therapy device. This document focuses on demonstrating substantial equivalence to a predicate device, rather than proving that the device meets specific acceptance criteria based on a clinical study with performance metrics like sensitivity, specificity, or accuracy.

Therefore, many of the questions regarding acceptance criteria, study sizes, expert involvement, and ground truth establishment, which are typical for studies evaluating AI/imaging devices, are not applicable to this type of regulatory submission.

Here's an analysis based on the information provided:

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

No explicit acceptance criteria with specific performance metrics (e.g., accuracy percentages, sensitivity, specificity) are stated in the document. The regulatory pathway is based on substantial equivalence to a predicate device, meaning the new device performs "comparably" and does not raise new safety or effectiveness concerns.

The reported "performance" is primarily a demonstration of its ability to deliver negative pressure wound therapy comparable to the predicate device.

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

• Sample size for the test set: Not applicable. The "test set" in this context refers to bench testing of the device itself, not a dataset of patient cases. The document does not specify the number of units tested.
• Data provenance: Not applicable. The "data" refers to engineering test results, not patient data. No country of origin for such data is mentioned, nor is it classified as retrospective or prospective.

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. "Ground truth" in the context of device performance in this 510(k) submission relates to the physical parameters of the device (e.g., negative pressure delivery), not expert interpretation of clinical data. Therefore, no experts were used to establish ground truth in the manner typical for AI/imaging product evaluations.

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

Not applicable. Adjudication methods are used to resolve disagreements among human reviewers (experts) when establishing ground truth for clinical data. This regulatory submission relies on bench testing and engineering verification, not human adjudication of clinical cases.

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 mechanical wound therapy system, not an AI-assisted diagnostic tool for 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 medical device, not an algorithm. Its performance is inherent to its mechanical function, not an algorithmic output. The "software validation testing" mentioned is likely for internal control software, not a standalone diagnostic algorithm.

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

The "ground truth" for the device's functionality would be based on engineering specifications and measurements (e.g., verifying that the device consistently generates and maintains the specified negative pressure, or that the alarm functions correctly). This is an objective measurement of physical parameters, not a clinical diagnosis or outcome.

8. The sample size for the training set

Not applicable. This is not an AI/machine learning device that requires a training set.

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

Not applicable. As this is not an AI/machine learning device, there is no training set and therefore no ground truth established for it.

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