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AdvaCoat™ Sinus Gel and Stent are indicated for use in patients undergoing nasal/sinus surgery as a space-occupying dressing and/or stent intended to prevent adhesions in the nasal cavity, separate mucosal surfaces compromised by surgery or trauma, minimize edema and help control minimal bleeding following surgery or trauma, and act as an adjunct to aid in the natural healing process.

AdvaCoat™ Sinus Gel and Stent (AdvaCoat™) is a sterile, non-pyrogenic, viscoelastic, bioresorbable material composed of cross-linked polymers of a derivatized hyaluronan. AdvaCoat™ is produced from a non-animal, nonpathogenic source using a highly purified hyaluronan. AdvaCoat™ Sinus Gel and Stent and its break down products are biocompatible, non-immunogenic and non-toxic.

AdvaCoat™ Sinus Gel and Stent are provided in two formats, a gel and a stent. The gel is delivered using a syringe and the stent is applied dry as a packing material.

Due to its tissue adhesive properties, AdvaCoat™ will not migrate or be dislodged from the application site. AdvaCoat™ may be used as a space occupying dressing and/or stent to minimize bleeding. Upon application, AdvaCoat™ forms a viscous and transparent gel conforming to mucosal surfaces.

The final packaged product is sterilized with E-beam radiation to a Sterility Assurance Level (SAL) of 10° and intended for single use only.

This 510(k) premarket notification (K070496) for the AdvaCoat™ Sinus Gel and Stent device is a claim of substantial equivalence to previously cleared predicate devices, rather than a study demonstrating that the device meets specific acceptance criteria through novel performance data.

The FDA's review for a 510(k) submission primarily focuses on comparing the new device's technological characteristics and intended use to those of a legally marketed predicate device(s). If the new device is "substantially equivalent," meaning it is as safe and effective as the predicate device(s), it can be cleared for market without requiring new clinical trials or extensive performance testing beyond demonstrating this equivalence.

Therefore, the input document does not contain the detailed information typically found in a study designed to "prove the device meets acceptance criteria" for a novel device. Instead, it argues that the device's characteristics are similar enough to existing, cleared devices that new performance studies are not necessary to demonstrate safety and effectiveness.

Here's an analysis based on the provided document, addressing the requested points where possible, and noting where the information is not applicable due to the nature of a 510(k) relying on substantial equivalence:

Description of Acceptance Criteria and Study to Prove Device Meets Them (K070496)

The submission for AdvaCoat™ Sinus Gel and Stent (K070496) is a Premarket Notification (510(k)) which claims substantial equivalence to predicate devices. This means that the "acceptance criteria" are primarily met by demonstrating that the new device shares the same intended use and similar technological characteristics as devices already legally on the market, without raising new questions of safety or effectiveness. The "study" demonstrating this is the comparison presented in the submission itself.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence claim, the "acceptance criteria" are implied by the characteristics of the predicate devices. The "reported device performance" is a demonstration that the new device's characteristics are sufficiently similar or identical to the predicate's for the intended use.

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

• Not applicable / No specific test set data provided.
  • This submission relies on demonstrating substantial equivalence to existing predicate devices rather than presenting new performance data from a specific test set. The efficacy and safety data of the predicate devices implicitly serve as the "proven" performance. The document states, "There are no new performance characteristics for AdvaCoat™ compared to the substantially equivalent predicate devices marketed for sale."
  • The "data provenance" for the underlying safety and efficacy of the predicate devices would be based on their original clearances, which are not detailed here.

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

• Not applicable.
  • No specific "test set" and corresponding "ground truth" establishment by experts is described for this 510(k) submission. The FDA's review process (which includes internal expert review) determined that the information provided supported substantial equivalence.

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

• Not applicable.
  • No explicit adjudication method for a test set is described, as the submission focuses on comparing characteristics to predicates rather than presenting de novo clinical or performance data for 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

• Not applicable.
  • This device is a physical sinus gel/stent and does not involve AI or any form of "human reader" interpretation (e.g., in medical imaging). Therefore, an MRMC study is irrelevant to this submission.

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

• Not applicable.
  • As noted above, this device does not involve an algorithm or AI.

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

• Not applicable / Implied by predicate clearance.
  • For this 510(k), the "ground truth" for proving safety and effectiveness relies on the prior clearance of the predicate devices. Those predicates would have established their safety and effectiveness through various studies (e.g., biocompatibility testing, clinical outcomes, animal studies) potentially using expert consensus, pathology, and/or outcomes data, but these details are not provided in this submission for the AdvaCoat™ device.

8. The sample size for the training set

• Not applicable.
  • This device is a physical medical device, not an AI or machine learning algorithm that requires a "training set."

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

• Not applicable.
  • As no training set is relevant, this question is not applicable.

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Gelita-Spon® Absorbable Gelatin Sponge is indicated for use to control minimal bleeding by tamponade effect, blood absorption and platelet aggregation following ENT surgery and also to prevent adhesions in the nasal cavity.

Gelita-Spon® Absorbable Gelatin Sponge is a sterile absorbable gelatin sponge composed of highly purified pH neutral pharmaceutical gelatin of porcine origin with haemostatic effect suitable for the control of bleeding and as a packing material. It is able to absorb blood corresponding to about 50 times its own weight and when implanted in vivo, it is completely absorbed within approximately 3 weeks.

The provided document focuses on the 510(k) summary for the Gelita-Spon® Absorbable Gelatin Sponge, establishing its substantial equivalence to predicate devices rather than presenting a study demonstrating its performance against specific acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, study details, and AI-related aspects cannot be extracted from this document.

Here's a breakdown of what can and cannot be answered based on the provided text:

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

The document does not specify formal acceptance criteria with numerical targets. Instead, it demonstrates substantial equivalence by comparing the technological characteristics of Gelita-Spon® with two predicate devices (MeroPack™ Nasal Dressing and Sinus Stent and MeroGel™ Nasal Dressing and Sinus Stent).

A comparative table of these characteristics is provided:

The acceptance criteria implicitly are that the device's characteristics are comparable to or better than the predicate devices, particularly for features like absorbent qualities and biocompatibility.

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

This information is not provided in the document. The submission relies on comparative data with predicate devices and general performance characteristics of the gelatin sponge, not on a specific clinical test set with a defined sample size or data provenance.

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 in the document. No expert review or ground truth establishment relevant to a clinical test set is mentioned.

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

This information is not provided in the document. No adjudication method is mentioned as there is no specific clinical test set described.

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

This information is not applicable/provided. The device is a physical medical device (absorbable gelatin sponge), not an AI-powered diagnostic or assistive technology. Therefore, an MRMC study related to human readers and AI is irrelevant to this submission.

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

This information is not applicable/provided. The device is a physical medical device, not an algorithm.

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

This information is not provided in the document. The submission relies on the established science and performance characteristics of absorbable gelatin sponges and a comparison to legally marketed predicate devices, rather than a specific ground truth derived from expert consensus, pathology, or outcomes data from a new study for this device.

8. The sample size for the training set

This information is not provided in the document. No "training set" in the context of an algorithm is discussed.

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

This information is not provided in the document. No "training set" or its ground truth establishment is mentioned.

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