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SurgiAid® Collagen Wound Dressing is indicated for use in patients who have surgical wounds, donor sites/grafts, podiatric wound, wound dehiscence, traumatic wounds, abrasions, lacerations, partial thickness burns or skin tears. SurgiAid® Collagen Wound Dressing can be applied to wounds with depth less than 0.3 cm.

SurgiAid Collagen Wound Dressing (SurgiAid) is white, porous pliable and absorbable collagen wound dressing. It is fabricated by fibrous collagen matrix which is purified from bovine Achilles tendon. SurgiAid is pliable and can be applied easily to clean wound. The product is supplied in sterile, non-pyrogenic package, and is indicated for single use only.

The provided text describes a 510(k) submission for a medical device called "SurgiAid® Collagen Wound Dressing" (K223126). This submission focuses on demonstrating substantial equivalence to a previously cleared predicate device, rather than a de novo approval requiring extensive clinical efficacy studies. Therefore, the "study" described and the "acceptance criteria" are primarily related to non-clinical performance data and comparison to the predicate device.

Here's an analysis of the requested information based on the provided text:

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

The document provides a comparison table (Table 1) between the subject device (K223126), the predicate device (K100927), and a reference device (K122325). The acceptance criteria are implied by the "Comparison" column, which states "Identical to Predicate Device" or similar, indicating that the subject device's performance should match that of the predicate. For specifications (dimensions), the acceptance is that the new sizes "fall within the size range of the reference device."

The Study that Proves the Device Meets the Acceptance Criteria:

The "study" here is a series of non-clinical tests and a comparison to the predicate device to demonstrate substantial equivalence, rather than a clinical trial.

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 primarily discusses non-clinical performance and material characteristics.

• Sample size: The specific sample sizes for each non-clinical test (e.g., how many dressings were tested for water absorption, porosity, sterilization validation, etc.) are not explicitly provided in the summary.
• Data provenance: The document states the manufacturer is Maxigen Biotech Inc. in Taoyuan City, Taiwan. The non-clinical tests would have been conducted by or for this manufacturer. It does not specify whether these tests were performed in Taiwan or elsewhere. The data is "retrospective" in the sense that the new device's characteristics were compared to already established characteristics of the predicate and reference devices, and tested against established standards (ISO10993, etc.). These are typically laboratory tests, not patient data trials.

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 question is not applicable to this type of submission. The "ground truth" for non-clinical performance data (e.g., water absorption, porosity, biocompatibility) is established according to recognized international standards (e.g., ISO 10993 for biocompatibility) and validated laboratory methods. It does not involve expert consensus on medical images or clinical outcomes.

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

This question is not applicable. Adjudication methods are typically used in clinical trials involving subjective interpretation of data (like imaging studies where multiple readers agree/disagree on a finding). For non-clinical tests, results are typically quantitative and objective measurements against predefined criteria/standards.

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 question is not applicable. An MRMC study is relevant for diagnostic devices, especially those incorporating AI, where human readers interpret medical images. This document describes a collagen wound dressing, which is a therapeutic device, and does not mention any AI component or diagnostic function.

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

This question is not applicable. The device is a physical wound dressing, not an algorithm or software.

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

For the non-clinical tests:

• Standards/Specifications: The "ground truth" for characteristics like water absorption, porosity, density, sterilization, packaging integrity, and biocompatibility is based on established international standards (e.g., ISO10993-1:2018) and predefined acceptance criteria derived from the predicate device's performance and general recognized medical device safety and efficacy principles.
• Predicate Device Data: The performance of the predicate device (K100927) serves as a key "ground truth" for comparison to establish substantial equivalence.

8. The sample size for the training set

This question is not applicable. There is no "training set" in the context of this 510(k) submission for a wound dressing. Training sets are used in machine learning for AI algorithms.

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

This question is not applicable as there is no training set.

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SurgiAid Collagen Wound Dressing is intended for use in patients who have surgical wounds, donor sites/grafts podiatric wounds, wound dehiscence, traumatic wounds, abrasions, lacerations, partial thickness burns or skin tears. SurgiAid Collagen Wound Dressing can be applied to wounds with depth less than 0.3 cm.

SugiAid Collagen Wound Dressing is white, porous, pliable and absorbable collagen wound dressings. It is fabricated by fibrous collagen matrix which is purified from bovine Achilles tendon. SugiAid is pliable and can be applied easily to clean wounds. The product is supplied in sterile, nonpyrogenic package, and is indicated for single use only.

The provided text describes a 510(k) summary for the "SurgiAid Collagen Wound Dressing." This document focuses on demonstrating substantial equivalence to a predicate device rather than conducting a de novo clinical study to define and meet specific acceptance criteria for performance.

Therefore, the study design elements typically associated with establishing acceptance criteria for a new AI/medical device (like sample size for test sets, ground truth methodology, MRMC studies, or standalone performance) are not applicable here. The submission's goal is to prove the new device is as safe and effective as a previously cleared device, not to prove its own independent performance against a set of statistical targets.

Here's a breakdown based on the provided text, highlighting what is (and isn't) present:

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

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

• Not Applicable. This submission relies on bench testing and biocompatibility assessments rather than a clinical trial with a "test set" of patient data in the typical sense for AI/diagnostic devices. The goal is to show the device itself meets material and safety standards and is similar to a predicate, not to test its performance on a dataset of clinical cases.

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. No human experts were used for "ground truth" establishment in this context, as it's a submission for a wound dressing, not an AI diagnostic device. The "ground truth" for material properties is established through standardized laboratory testing and specific ISO standards.

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

• Not Applicable. As there is no "test set" in the context of clinical image or data interpretation, no adjudication method was used.

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 a physical medical device (collagen wound dressing), not an AI-assisted diagnostic tool. Therefore, MRMC studies are irrelevant to this submission.

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

• Not Applicable. This is a physical medical device, not an algorithm.

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

• The "ground truth" here is based on established scientific and regulatory standards for material properties, biocompatibility, and intended use. This includes:
  • ISO 10993-1:2009 series for biocompatibility (cytotoxicity, hemolysis, sensitization, etc.).
  • Validated laboratory methods for physical and chemical tests (Purity, Endotoxin level, Pepsin resistance, Collagenase resistance, Rehydration Test).
  • Comparison to the known characteristics of the predicate device (SkinTemp, K925545).

8. The sample size for the training set

• Not Applicable. This device is not an AI algorithm that requires a "training set."

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

• Not Applicable. No training set was used.

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