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WoundStat™ is intended for emergency use only as an external temporary traumatic wound treatment to achieve hemostasis for moderate to severe bleeding.

WoundStat™ is a clay-based, granular hemostatic agent that is poured on or into a moderate to severe wound and held in place until it adheres to the wound and hemostasis is achieved. The device is packaged in a foil package and is provided sterile.

This document is a 510(k) premarket notification for the WoundStat™ device, comparing it to a predicate device, QuikClot®. It does not describe a study that uses acceptance criteria in the way a diagnostic AI device would. Instead, it focuses on demonstrating substantial equivalence to a legally marketed predicate device through pre-clinical testing, intended use, and mechanism of action.

Therefore, many of the requested fields regarding acceptance criteria, performance metrics, sample sizes for test/training sets, expert involvement, and ground truth establishment (which are typical for AI/diagnostic studies) are not applicable to this type of regulatory submission.

Here's the information that can be extracted or deduced from the provided documents:

1. Table of Acceptance Criteria and Reported Device Performance:

• Acceptance Criteria: Not explicitly stated as quantifiable metrics with thresholds (e.g., sensitivity > X%, specificity > Y%) in the context of a diagnostic or AI device study. The "acceptance criteria" here are generally meeting the requirements of substantial equivalence to the predicate device.
• Reported Device Performance:
  "WoundStat™ has equivalent, if not better, hemostasis results in terms of speed and effectiveness as QuikClot®."
  "The results of these tests demonstrate that WoundStat™ is safe for its intended use."

2. Sample size used for the test set and the data provenance:

• Sample Size for Test Set: Not specified in terms of patient or case numbers. Pre-clinical models were used.
• Data Provenance: Pre-clinical models.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Number of Experts: Not applicable. Ground truth was not established by human experts in a diagnostic reading context. The "truth" was determined during pre-clinical hemostasis and safety studies.

4. Adjudication method for the test set:

• Adjudication Method: 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:

• MRMC Study: No. This is not an AI device or a diagnostic device evaluated with human readers.

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

• Standalone Performance: Not applicable. This is a medical device (hemostatic agent), not an algorithm.

7. The type of ground truth used:

• Type of Ground Truth: Hemostasis results (speed and effectiveness) in pre-clinical models, and biocompatibility test results (systemic toxicity, cytotoxicity, intracutaneous studies).

8. The sample size for the training set:

• Sample Size for Training Set: Not applicable. This device does not involve machine learning or a "training set."

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

• Ground Truth Establishment for Training Set: Not applicable.

In summary, this document is a regulatory submission for a physical medical device (hemostatic agent) and not an AI or diagnostic device. Therefore, the questions tailored for AI/diagnostic study evaluations are largely not relevant or applicable to the information provided. The "study" referenced is pre-clinical testing to demonstrate safety and effectiveness comparable to a predicate device.

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