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WEGO-PGA RAPID sutures are intended for use in superficial soft tissue approximation of skin and mucosa where only short-term wound support is required. WEGO-PGA RAPID is not intended for use in ligation, ophthalmic, cardiovascular or neurological procedures.

WEGO-PGA RAPID sutures are synthetic, absorbable, braided, sterile surgical sutures composed of Polyglycolic Acid (PGA). The formula of the polymer is (CH2O2)n. The characteristic rapid loss of strength is achieved by use of a polymer material with a lower molecular weight than regular WEGO-PGA suture. WEGO-PGA RAPID sutures are available undyed violet with D&C Violet No.2 (Colour Index number 60725). WEGO-PGA RAPID sutures are coated with polycaprolactone and calcium stearate.

The performance of this absorbable suture complies with United States Pharmacopeia (U.S.P.) monograph requirements for Absorbable Surgical Suture, USP 40, USP 40 and USP 40 .

The Synthetic Absorbable Suture is provided EO sterilized as a single use device.

The provided text describes the regulatory clearance of a medical device (WEGO-PGA RAPID sutures) and includes information about non-clinical tests conducted to demonstrate its performance and substantial equivalence to a predicate device. However, it does not include information about a study proving the device meets acceptance criteria in the context of AI/ML performance, nor does it present acceptance criteria in terms of metrics like sensitivity, specificity, or AUC, which are common for AI/ML devices.

Therefore, I cannot fulfill the request as it pertains to AI/ML device acceptance criteria and a study proving those criteria are met. The document focuses on regulatory compliance for a traditional medical device (surgical sutures) through non-clinical testing against established standards and comparison to a predicate device.

Here's an analysis of the provided text in relation to your specific questions, highlighting what is not present for an AI/ML device:

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

   • Not present for an AI/ML device. The document lists standards the device complies with (e.g., USP monographs for suture properties, ISO standards for biocompatibility) and states that "The physical performance and stability of proposed device have been demonstrated by testing on samples before and after real-time-aging." It does not provide specific acceptance criteria values (e.g., "Accuracy > 90%") or reported performance metrics (e.g., "Accuracy achieved 92%") as would be expected for an AI/ML device.

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

   • Not present for an AI/ML device. The non-clinical tests described involve physical and biological testing of suture samples (e.g., diameter, tensile strength, sterility, biocompatibility). The document does not specify sample sizes for these tests in an AI/ML context, nor does it refer to "data provenance" as it would for a dataset used to evaluate an AI model.

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 present for an AI/ML device. Ground truth establishment by experts is not relevant to the non-clinical testing of surgical sutures described.

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

   • Not present for an AI/ML device. Adjudication methods are relevant for resolving discrepancies in expert labeling or diagnoses for AI/ML ground truth, not for physical and biological testing of sutures.

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 present. This type of study is specifically for evaluating the impact of AI assistance on human performance. The document explicitly states: "No clinical study is included in this submission."

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

   • Not present. There is no algorithm or AI component described for this device. The testing pertains to the physical and biological properties of the suture itself.

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

   • Not present for an AI/ML device. The "ground truth" for the non-clinical tests consists of established scientific and regulatory standards (e.g., USP monographs for tensile strength, biocompatibility test results).

8. The sample size for the training set:

   • Not applicable. There is no AI model, and therefore no training set, for this device.

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

   • Not applicable. There is no AI model, and therefore no training set or ground truth establishment process for it.

In summary: The provided document is a 510(k) clearance letter and summary for a traditional medical device (surgical sutures) and details compliance with physical, chemical, and biological standards, along with a comparison to an existing predicate device. It does not provide any information relevant to the acceptance criteria or study design for an AI/ML-powered medical device.

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