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510(k) Data Aggregation
(29 days)
Quill™ MONODERM™ device is indicated for use in soft tissue approximation where the use of absorbable sutures is appropriate.
The Quill™ Monoderm™ Knotless Tissue-Closure Device is a sterile, synthetic absorbable tissue approximation device that is comprised of a copolymer of glycolide and e-caprolactone, undyed, or dyed with D&C Violet No. 2. The device is designed with small bi-directional barbs along the long axis of the suture monofilament. It is available in diameter Sizes 0 to 5-0, in various lengths affixed to various needle types.
The provided text describes a 510(k) premarket notification for a medical device, the Quill™ Monoderm™ Knotless Tissue-Closure Device (PGA-PCL). This document focuses on demonstrating substantial equivalence to a predicate device rather than presenting a study of its performance against specific acceptance criteria in the manner typical for AI/ML-based devices.
Therefore, many of the requested categories for AI/ML device studies (such as MRMC studies, standalone performance, training set details, or expert ground truth establishment) are not applicable to the information contained in this submission.
Here's an analysis of the provided text in relation to your questions, focusing on the available information:
1. A table of acceptance criteria and the reported device performance
Acceptance Criteria (What was measured) | Reported Device Performance (How the device measured up) |
---|---|
Conformance to USP monograph for absorbable sutures | Conforms to the USP monograph for absorbable sutures (as applicable). |
In vitro post-hydrolysis tensile testing | Results demonstrate substantial equivalence to the predicate device. |
In vivo resorption testing | Results demonstrate substantial equivalence to the predicate device. |
Same material, design, intended use, and technological characteristics as predicate device (for new sizes) | The proposed additional diameter sizes (4-0 and 5-0) have these characteristics. |
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 does not specify sample sizes for the performance tests (USP monograph, in vitro tensile, in vivo resorption). It also does not provide details about the provenance of the data, such as country of origin or whether the studies were retrospective or prospective.
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)
This type of information is not relevant or provided for this device type (a surgical suture). Ground truth, in the context of this device, would be defined by standardized chemical and physical tests rather than expert interpretation of data.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
Not applicable to the type of device and testing described. Performance was assessed via laboratory and in-vivo testing, not through adjudication of expert opinions.
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 is a surgical suture, not an AI/ML-based diagnostic device where MRMC studies would be relevant.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
Not applicable. This is a physical medical device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for this device's performance would be established through:
- Physical and chemical standards: As defined by the USP monograph for absorbable sutures.
- Direct measurement: Of properties like tensile strength and resorption rates in vitro and in vivo.
The "ground truth" is objective measurement against established standards and comparisons to the predicate device, not expert consensus or pathology in the typical sense.
8. The sample size for the training set
Not applicable. There is no training set as this is not an AI/ML device.
9. How the ground truth for the training set was established
Not applicable. There is no training set as this is not an AI/ML device.
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