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The HemaMyst Surgical Applicator System is indicated for the simultaneous application of the two separate components of HEMASEEL APR Fibrin Sealant or Tisseel VH Fibrin Sealant to the treatment site.

The HemaMyst Surgical Applicator System is a sterile, single-use device consisting of a Head that attaches by Luer connectors to currently available dual syringe spray noals and is coupled to an air regulator base unit by means of a sterile filtered air applicators, and is obablicator System allows simultaneous delivery, by spraying, of the two components of fibrin sealant to the treatment site.

The provided text describes a 510(k) summary for the HemaMyst Surgical Applicator System. However, it does not contain information about acceptance criteria, device performance, a specific study proving acceptance criteria, sample sizes for test or training sets, data provenance, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance.

The document primarily focuses on:

• Device Description: A sterile, single-use device for simultaneous delivery of two components of fibrin sealant.
• Changes from Predicate: The key change is the indication for application of HEMASEEL APR Fibrin Sealant or Tisseel VH Fibrin Sealant.
• Functionality Testing: States that functionality testing shows the device is "function[al] with 3, 50 and 11, 2017 [sic] and and Spray of HEMASEEL APR or Tisseel VH fibrin sealant." This is a very brief and incomplete statement regarding testing and doesn't provide detailed performance metrics or acceptance criteria.
• Intended Use/Indications for Use: Simultaneous application of HEMASEEL APR Fibrin Sealant or Tisseel VH Fibrin Sealant to the treatment site.
• Substantial Equivalence: The FDA's letter confirming substantial equivalence to predicate devices (K994023 and K981089).

Therefore, based solely on the provided text, I cannot complete the requested tables and information.

Here's an attempt to fill in what can be inferred or directly stated, and to explicitly highlight what is missing:

1. Table of Acceptance Criteria and Reported Device Performance

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

• Sample Size for Test Set: Not specified. The phrase "function[al] with 3, 50 and 11, 2017" is unclear. It might refer to three specific tests, or some other parameters, but it's not a clear sample size.
• Data Provenance (country of origin, retrospective/prospective): Not specified.

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

• This device is mechanical. The concept of "ground truth" and "experts" as in diagnostic AI studies typically doesn't apply to this kind of functionality testing in the same way. The assessment would likely be based on engineering specifications and direct measurement, not expert consensus on an image or medical condition.
• Number of experts: Not applicable/Not specified.
• Qualifications of experts: Not applicable/Not specified.

4. Adjudication method for the test set

• Not applicable/Not specified, as this refers to a diagnostic assessment process. For a mechanical device, performance is typically measured against specifications.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

• No. This is a mechanical device, not a diagnostic algorithm involving human readers.

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

• Yes, implicitly. The "Functionality testing" refers to the device's performance. Since it's a mechanical applicator for fibrin sealant, its performance would inherently be evaluated in a standalone manner, separate from a human operator's skill, to ensure it delivers the sealant correctly. However, a specific study detailed as "standalone performance" is not described.

7. The type of ground truth used

• The "ground truth" for a mechanical device's functionality would be its adherence to engineering specifications and proper delivery of the fibrin sealant. The text does not detail these specifications or measurement methods.

8. The sample size for the training set

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

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

• Not applicable.

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Haemacure HemaMyst Surgical Applicator System is indicated for the application of two non-homogeneous fluids or solutions to the treatment site.

The Haemacure HemaMyst Surgical Applicator System consists of an air regulator that can be coupled with compressed gasses present in the operating suite, a foot pedal to control air flow; and a spray head that can be coupled to currently available dual syringe applicators with a filtered air line to connect the base unit to the applicator spray head.

The base unit with the regulator and foot pedal is provided non-sterile and sold as a reusable device.

The spray head and filtered gas tubing is ethylene oxide (EtO) sterilized and sold as a sterile, single-use device.

The provided documentation is for a 510(k) premarket notification for the Haemacure HemaMyst Surgical Applicator System. This type of submission relies on demonstrating substantial equivalence to a predicate device, rather than conducting new clinical studies to prove effectiveness or safety. Therefore, many of the typical acceptance criteria and study design elements for AI/ML-based medical devices are not present.

However, I can extract the information relevant to performance testing that was conducted to demonstrate equivalence.

Here's a breakdown of the available information:

Acceptance Criteria and Device Performance

Explanation of "Acceptance Criteria" in this context: For a 510(k) submission, the primary "acceptance criterion" is demonstrating substantial equivalence to a legally marketed predicate device. This means showing that the new device is as safe and effective as the predicate, or that any differences do not raise new questions of safety or effectiveness. The performance testing conducted here directly addresses this.

Regarding the other requested information, much of it is not applicable or not provided in the context of this 510(k) submission for a non-AI surgical applicator system:

1. Sample size used for the test set and the data provenance: Not applicable. Performance testing for this device would likely involve engineering bench testing, not a clinical "test set" with patient data. No details about sample sizes for such tests are provided.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This device does not involve a diagnostic or predictive algorithm that requires expert-established ground truth.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.

4. 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 a surgical applicator, not an AI-assisted diagnostic tool.

5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" for this device's performance would be engineering specifications and functional output, not clinical outcomes or pathology.

7. The sample size for the training set: Not applicable. This device does not use machine learning and therefore has no "training set."

8. How the ground truth for the training set was established: Not applicable.

In summary: The provided document describes a 510(k) submission for a surgical applicator system. The "study" mentioned is performance (functionality) testing, which aimed to demonstrate substantial equivalence to a predicate device. This is primarily bench testing to ensure the device performs as intended and similarly to its predicate. It does not involve clinical trials with "test sets," "ground truth" as typically defined for diagnostic devices, or AI/ML components.

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