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Dafilon Nonabsorbable Polyamide Surgical Sutures are indicated for use in all types of general soft tissue approximation and/or ligation, including use in cardiovascular, ophthalmic, microsurgery and neurological procedures.

Dafilon is a nonabsorbable monofilament surgical suture which is supplied sterile. Dafilon is composed of the long-chain aliphatic polymers polyamide 6 and/or 6,6. The Dafilon suture is offered undyed and dyed with FDA approved colorants Logwood extract in accordance with Title 21 CRF, §73.1410 or [Phthalocyaninato(2-)] copper in accordance with Title 21 CFR, §74.3045. The Dafilon suture will be offered in diameters ranging from USP size 11-0 through 5 and will be available in a variety of cut lengths with out needles attached.

This document is a 510(k) premarket notification for a surgical suture, not a device that involves performance criteria typically associated with AI/ML algorithms or interpretative medical devices. Therefore, many of the requested sections regarding acceptance criteria and study design are not applicable in the context of this document. This submission primarily focuses on demonstrating substantial equivalence to existing predicate devices based on material composition, indications for use, and mechanical/biocompatibility testing, rather than an AI model's diagnostic or predictive performance.

However, based on the provided text, I can extract the relevant "acceptance criteria" and "performance data" for this suture device where applicable.

Here's an interpretation of the document in the context of your request, focusing on the available information:

Device: Aesculap Dafilon Nonabsorbable Polyamide Surgical Suture

Since this is a surgical suture, the "acceptance criteria" are related to its physical properties, sterility, and biocompatibility, rather than diagnostic accuracy or sensitivity/specificity of a predictive model.

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

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

The document specifies "tests were conducted for diameter, tensile strength, and needle attachment" and "biocompatibility testing." However, it does not specify the sample sizes for these tests. The provenance is internal testing by Aesculap, Inc. against USP (United States Pharmacopeia) requirements and ISO (International Organization for Standardization) standards. The tests are likely prospective, conducted on manufactured samples of the device.

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

This question is not applicable to a nonabsorbable surgical suture device. The "ground truth" for suture performance is established by standardized physical and biological tests (USP, ISO standards), not by human expert interpretation or consensus in the way it would be for an AI diagnostic device.

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

Not applicable for a surgical suture. Adjudication methods are relevant for subjective interpretations of data, typically in diagnostic studies. Here, the "truth" is determined by objective measurements against established 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

Not applicable. This device is a surgical suture, not an AI-assisted diagnostic tool. No human reader involvement or AI assistance is relevant to its performance evaluation for this 510(k) submission.

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 (suture), not an algorithm.

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

The "ground truth" is based on established industry standards and regulatory requirements:

• USP Requirements: For physical characteristics such as diameter, length, needle attachment, and tensile strength.
• ISO 10993-1: For biocompatibility testing (Cytotoxicity, Sensitization, Intracutaneous Irritation, Systemic and Muscle Implantation).
• 21 CFR §73.1410 and §74.3045: For colorant approval.

8. The sample size for the training set

Not applicable. This device does not involve a "training set" in the context of machine learning or AI.

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

Not applicable. As there is no training set, there is no ground truth establishment for it.

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Dafilon® Nonabsorbable Polyamide Surgical Sutures are indicated for use in all types of general soft tissue approximation and/or ligation, including use in cardiovascular, ophthalmic, and neurological procedures.

The subject device is a nonabsorbable, flexible, monofilament suture thread which is supplied sterile. It is composed of the long-chain, linear aliphatic polymers nylon 6 and/or nylon 6,6. It is indicated for general soft tissue approximation and/or ligation. It will be offered undyed, or dyed with the FDA listed colorants FD&C Blue No. 2 (in accordance with Title 21 CFR, §74.1102) or Logwood extract (in accordance with Title 21 CFR, §73.1410). It will be offered uncoated, and will be available with and without standard needles attached.

The provided text is a 510(k) summary for a medical device (Dafilon® Nonabsorbable Polyamide Surgical Suture) and not a study describing AI/machine learning model performance. Therefore, many of the requested categories related to AI model evaluation, such as "effect size of how much human readers improve with AI vs without AI assistance," "standalone performance," "training set size," and "ground truth establishment for the training set," are not applicable.

However, I can extract information related to acceptance criteria and the non-clinical studies conducted for this traditional medical device.

Acceptance Criteria and Device Performance (Non-AI/ML Device)

The "acceptance criteria" for this device are its conformance to established medical device standards and its substantial equivalence to predicate devices. The performance is assessed against these standards and predicates.

Study to Prove Acceptance Criteria:

The study to prove the device meets acceptance criteria was a series of "Non-Clinical Tests" to demonstrate substantial equivalence to predicate devices.

1. Sample size used for the test set and the data provenance: Not explicitly stated. The text mentions "physical testing for all parameters identified above" and "in vitro and in vivo biosafety studies, and one (1) and two (2) year implant studies in animals." The provenance for animal studies is "in animals," but specific species or location are not detailed. These are non-clinical studies.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This is not an AI/ML study involving expert ground truth for image interpretation or diagnosis. The "ground truth" here is the conformance to U.S.P. standards and comparison to predicate device characteristics.

3. Adjudication method for the test set: Not applicable. No human interpretation or adjudication process described.

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 not an AI-assisted device.

5. 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.

6. The type of ground truth used:

   • Regulatory Standards: Conformance to U.S. Pharmacopoeia (U.S.P.) XXIII standards for sutures (e.g., diameter, needle attachment, tensile strength).
   • Predicate Device Characteristics: Comparison of material composition, design, physical properties, manufacturing, packaging, sterilization, and labeling to existing "predicate devices" (Ethilon®, DERMALON®, MONOSOF®).
   • Biological Response: Results from in vitro and in vivo biosafety studies and long-term animal implant studies (1 and 2 years) to assess retention of tensile strength and safety.

7. The sample size for the training set: Not applicable. This is not an AI/ML device.

8. How the ground truth for the training set was established: Not applicable. This is not an AI/ML device.

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