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510(k) Data Aggregation
(103 days)
TruShot with Y-Knot All-Suture Anchor
Intended Use
The non-absorbable suture anchors are intended to reattach soft tissue to bone in orthopedic surgical procedures.
Indications for Use
The device may be used in either arthroscopic or open surgical procedures. After the suture is anchored to the bone, it may be used to reattach soft tissue, such as ligaments, tendons, or joint capsules to the suture anchor systems thereby stabilize the damaged soft tissue, in conjunction with appropriate postoperative immobilization, throughout the healing period.
The CONMED TruShot™ with Y-Knot® All-Suture Anchor is manufactured from High Strength Flat Braided Suture threaded with either one or two #2 (5 metric) Hi-Fi® suture strands with needles. Each All-Suture Anchor is preloaded on a disposable inserter, and pre-assembled with a disposable drill bit and guide handle. The anchor, suture(s) with needles, inserter, drill bit, and guide handle are pre-assembled and provided sterile, intended for single-use. The device is EO Sterilized.
The provided text describes a 510(k) premarket notification for a medical device called "TruShot™ with Y-Knot® All-Suture Anchor". It focuses on demonstrating substantial equivalence to a predicate device rather than presenting a detailed study proving performance against specific acceptance criteria for an AI/device algorithm in the way your request specifies.
The document discusses performance data in the context of device safety and efficacy and substantial equivalence to a predicate device, not in the terms of a novel AI algorithm's performance. Therefore, many of the requested elements (sample size for test set, data provenance, ground truth experts, adjudication methods, MRMC studies, standalone AI performance, training set size, and ground truth establishment for training set) are not applicable or extractable from this document.
However, I can extract the general acceptance criteria (testing types) and a general statement about device performance.
Here's the information that can be extracted from the provided text, recognizing the limitations of the document relative to your detailed request:
1. Table of Acceptance Criteria and Reported Device Performance
Acceptance Criteria (Testing Category) | Reported Device Performance |
---|---|
Reliability | Performed as intended |
Ultimate Fixation Strength | Performed as intended |
Cyclic | Performed as intended |
Sterilization | Performed as intended |
Pyrogen (Bacterial endotoxin testing) | Met the endotoxin limits |
Biocompatibility | Performed as intended |
Shelf-life | Performed as intended |
Post Aging Functional Testing | Performed as intended |
MR Safety Testing | Performed as intended |
User Validation | Performed as intended |
Packaging | Performed as intended |
Transportation | Performed as intended |
2. Sample size used for the test set and the data provenance
Not explicitly stated for specific tests. The document refers to "testing" in a general sense, not specific to a "test set" for an algorithm. This is a traditional medical device submission, not an AI/ML submission.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
This information is not provided. "User Validation" is mentioned, implying human interaction, but details on the number or qualifications of users/experts involved in this validation are absent.
4. Adjudication method for the test set
Not applicable based on the provided document.
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 not an AI/ML device.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
Not applicable. This is not an AI/ML device.
7. The type of ground truth used
For a traditional medical device like a suture anchor, "ground truth" would typically refer to established biomechanical properties, material standards, and clinical outcomes for similar devices. The document implies compliance with these through the various verification and validation tests listed. Pathology or outcome data are not specified as direct ground truth for these tests.
8. The sample size for the training set
Not applicable. This is not an AI/ML device, and thus no "training set" in that context is mentioned.
9. How the ground truth for the training set was established
Not applicable.
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