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Quill™ PDO Knotless Tissue-Closure Device, comprised of Polydioxanone, is indicated for soft tissue approximation where use of an absorbable suture is appropriate.

The Quill™ Knotless Tissue-Closure Device comprised of PDO (Polydioxanone) is a synthetic absorbable tissue-closure device that is intended for use in the closure of soft tissue. It is comprised of polyester [poly (p-dioxanone)] monofilament suture material, dyed with D&C Violet No. 2. The device is designed with small bi-directional barbs along the length that eliminate the need to tie knots during approximation. The device is available in various lengths in diameter sizes 2 through 4-0 with various needles attached to each end.

This document describes the K120827 Quill™ PDO Knotless Tissue-Closure Device. The provided text does not contain a specific table of acceptance criteria or detailed results of a study that directly proves the device meets quantitative criteria. Instead, it relies on a demonstration of "substantial equivalence" to predicate devices through performance testing.

Here's an analysis based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text does not contain a table of acceptance criteria or quantitative performance metrics. The submission relies on a qualitative statement of substantial equivalence.

Reported Device Performance (Qualitative):
"The results of this testing demonstrates that the Quill™ Knotless Tissue-Closure Device comprised of PDO (Polydioxanone) is substantially equivalent in safety and performance to the predicate devices."

2. Sample Size Used for the Test Set and Data Provenance

The text states: "Pre-clinical animal performance testing was conducted to confirm and support the information provided in the QuillTM Knotless Tissue-Closure Device comprised of PDO (Polydioxanone) Instructions for Use."

• Sample Size for Test Set: Not specified.
• Data Provenance: "Pre-clinical animal performance testing." The country of origin is not specified, but it's typically understood to be conducted under the manufacturer's internal protocols. This is a form of prospective testing.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not provided. The "ground truth" for this device's performance would primarily be derived from the animal model's physiological response to the suture (e.g., tissue approximation efficacy, absorption rate, inflammatory response) rather than expert interpretation of images or clinical data.

4. Adjudication Method for the Test Set

This information is not applicable/not provided. Adjudication methods like 2+1 or 3+1 are typically used for studies involving human interpretation of medical data (e.g., in diagnostic imaging studies) to establish a consensus ground truth. For animal performance testing of a physical device, the assessment would be based on direct observation, physical measurements, and histological analysis, not on expert adjudication of interpretations.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, an MRMC comparative effectiveness study was not done. Such studies are relevant for diagnostic AI tools where human readers are interpreting data. This submission is for a physical medical device (suture) and its performance in animal models, not an AI algorithm assisting human interpretation.

6. If a Standalone Study (Algorithm Only Without Human-in-the-Loop Performance) Was Done

No, this is not applicable. A standalone study typically refers to the performance of an AI algorithm without human involvement. This submission is for a physical medical device, not an AI algorithm.

7. The Type of Ground Truth Used

The ground truth for this type of device performance testing would be based on:

• Direct observation and measurement of the suture's physical interaction with tissue (e.g., tissue approximation).
• Histological analysis of tissue response (e.g., inflammation, foreign body reaction, absorption characteristics).
• Mechanical testing (e.g., tensile strength over time, knot security) although the text specifically mentions "Knotless" suggests this might be different.

8. The Sample Size for the Training Set

This information is not applicable/not provided. The concept of a "training set" is relevant for machine learning algorithms. This submission is for a physical medical device; its development relies on engineering principles and materials science, not machine learning training.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable/not provided for the same reasons as point 8.

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