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510(k) Data Aggregation
(149 days)
SHARPOINT PDO (POLYDIOXANONE) SUTURES
Sharpoint® PDO sutures are indicated for use in general soft tissue approximation and/or ligation, but not for use in cardiovascular, or neurological tissues, microsurgery or ophthalmic surgery.
The Sharpoint® (Polydioxanone) PDO Suture is a synthetic, absorbable, monofilament surgical suture available dyed D&C violet No.2. The PDO Sutures are attached to various size needles made of 400 series stainless steel
The provided text is a 510(k) summary for a medical device (Sharpoint® PDO Sutures) and does not describe a study involving AI, image analysis, or human readers. Instead, it describes a traditional medical device submission for a surgical suture.
Therefore, many of the requested categories (like "Sample sized used for the test set and the data provenance," "Number of experts used," "Adjudication method," "MRMC comparative effectiveness study," "Standalone performance," "Training set sample size," and "Ground truth for training set") are not applicable to this document.
However, I can extract the acceptance criteria and performance data as presented for this type of medical device submission.
Acceptance Criteria and Reported Device Performance for Sharpoint® PDO Sutures
| Category | Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Material Characteristics | Well-characterized polydioxanone material. | "The Polydioxanone material is well characterized through absorption studies and biocompatibility studies." |
| Safety & Effectiveness | Device demonstrated to be safe and effective. | "Bench testing has demonstrated the device to be safe and effective." |
| Equivalency to Predicate | Performance equivalent to the predicate device, Ethicon PDS II. | "Its performance is equivalent to the predicate device, Ethicon PDS II." and "The Sharpoint® PDO sutures are equivalent to the predicate device PDS II in material composition, intended use, absorption profile and bench testing." |
| Physical Testing | Conformance to USP 29 standards for Suture Diameter, Suture Attachment, Tensile Strength. | "Physical testing was performed on PDO (Polydioxanone) Synthetic, Absorbable sutures to USP 29, including Suture Diameter, Suture Attachment, Tensile Strength." |
| Biocompatibility | Conformance to ISO 10993 for Biocompatibility. | "Animal testing was performed for conformance to ISO 10993 for Biocompatibility..." |
| Implant Studies | Demonstration of rates of tensile and mass loss (absorption profile). | "...and Implant studies to demonstrate rates of tensile and mass loss." |
Additional Information (Not Directly Applicable to AI/Image Analysis)
- Sample sized used for the test set and the data provenance: Not explicitly stated in terms of specific numbers for physical or animal testing, but the provenance is internal testing by the manufacturer.
- Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for sutures is based on objective physical measurements and biological responses.
- Adjudication method: Not applicable.
- If a multi reader multi case (MRMC) comparative effectiveness study was done: No, this is not relevant for suture validation.
- If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable.
- The type of ground truth used:
- Physical Properties: Established by validated laboratory measurement methods (e.g., USP standards for diameter, tensile strength).
- Biocompatibility/Absorption: Established through in-vivo animal testing according to ISO 10993.
- The sample size for the training set: Not applicable (no "training set" in the AI sense).
- How the ground truth for the training set was established: Not applicable.
This document describes a regulatory submission for a conventional medical device (surgical sutures) where the validation relies on established international standards, bench testing, and animal studies to demonstrate safety, effectiveness, and substantial equivalence to a predicate device. It does not involve any artificial intelligence, machine learning, or human-in-the-loop evaluation as typically seen in AI/image analysis device submissions.
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