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DYNATAPE suture is indicated for orthopedic procedural use in soft-tissue approximation, and or ligation, including use with allograft tissue.

DYNATAPE™ Suture is a sterile non-absorbable orthopedic suture. DYNATAPE™ Suture has a double sheath and core design, composed of Ultra High Molecular Weight Polyethylene and Polyester, with or without colorants, as well as a Silicone/NaCl core. DYNATAPE™ Suture's outer sheath is braided flat, with rounded tips.

The provided text does not describe acceptance criteria for a medical device's performance in the context of clinical or diagnostic accuracy studies. Instead, it refers to the DYNATAPETM Suture, a non-absorbable orthopedic suture, and its substantial equivalence to a predicate device.

The "acceptance criteria" mentioned relate to non-clinical testing for material properties and regulatory compliance, not performance in a diagnostic or clinical accuracy sense. Specifically, the text states:

• USP Knot Tensile Strength: The DYNATAPE™ Suture "meets USP knot tensile strength for size 2 non-absorbable sutures."
• In-vitro approximation force over time: This testing was conducted to demonstrate the laxity resistance of the suture.
• Sterility testing: Testing was conducted.
• Biocompatibility, stability, in-vivo testing of the predicate device: These were included by reference (K181182).
• Bacterial endotoxin testing: Completed as part of another submission (K200949), meeting endotoxin limits.

The study presented is a 510(k) Premarket Notification, which aims to demonstrate that a device is "substantially equivalent" to a legally marketed predicate device. This is a regulatory pathway, not a clinical trial to establish device performance in terms of diagnostic accuracy or comparative clinical effectiveness.

Therefore, most of your specific questions regarding sample size, data provenance, expert ground truth, adjudication methods, MRMC studies, standalone performance, and training set information are not applicable to the information provided in this document, as it focuses on non-clinical testing and substantial equivalence.

Here's a breakdown of what can be extracted and why other parts are not applicable:

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)

• The document describes non-clinical laboratory testing (e.g., mechanical property tests, sterility tests). It does not provide details on specific sample sizes for these tests, nor does it refer to a "test set" in the context of patient data or clinical studies. Data provenance (country, retrospective/prospective) is not applicable or provided for these types of non-clinical tests.

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. "Ground truth" in this context refers to clinical outcomes or expert diagnoses, which are not part of this 510(k) summary for a surgical suture based on non-clinical testing.

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

• Not applicable. This pertains to clinical studies involving multiple readers or evaluators, not non-clinical laboratory testing of a device's material properties.

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 document is about a surgical suture, not a diagnostic imaging device or an AI-assisted system.

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

• Not applicable. This is for a physical medical device (suture), not an algorithm or AI system.

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

• For the non-clinical tests described, the "ground truth" would be established by standardized testing methods and specifications (e.g., USP standards for tensile strength) rather than expert clinical consensus or pathology.

8. The sample size for the training set

• Not applicable. There is no mention of a "training set" as this document is not about an algorithm or machine learning model.

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

• Not applicable. See point 8.

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