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The Arthrex Meniscal Dart System is intended for the repair of Meniscal tears that would otherwise be considered for standard repair using suture.

The Chondral Dart is intended for the use in fixation of small bone fragments, such as apical fragments, osteochondral fragments and cancellous fragments. Specific applications include the following: Apical fragments (radial head, patellar rim, navicular, metacarpal/metatarsal), osteochondral fragments (talus vault, femoral chondyle) and cancellous fragments (talus).

The Arthrex Meniscal Dart, Arthrex Meniscal Dartstick, and Arthrex Chondral Dart are identical to the predicate devices. The Arthrex Meniscal Dart and Arthrex Meniscal Dartstick are intended to be use for the repair of meniscal tears. The Arthrex Chondral Dart is intended to be used for the fixation of small bone fragments. See the Indications for Use statements for specific indications.

The provided document is a 510(k) summary for the Arthrex Meniscal Dart, Arthrex Meniscal Dartstick, and Arthrex Chondral Dart, which describes an "Extended Shelf Life" for these devices. It does not contain information about the performance criteria, clinical studies, or acceptance criteria in the context of device performance metrics like sensitivity, specificity, or accuracy, which are typical for AI/ML devices.

The submission claims substantial equivalence to predicate devices (K983577, Arthrex Meniscal Dart System and K991971, Arthrex Chondral Dart) based on "identical" features and intended uses, with "minor" differences not raising safety and effectiveness concerns. This implies that the acceptance criteria are met by demonstrating equivalence to previously cleared devices, particularly concerning an extended shelf life, rather than through a study proving specific performance metrics of an AI/ML component.

Therefore, many of the requested details are not applicable or cannot be extracted from this document, as it pertains to a traditional medical device modification (extended shelf life) and not an AI/ML device performance study.

Here's an attempt to address the points based on the provided document, noting where information is not available:

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

• Acceptance Criteria: Based on the nature of this 510(k) (extended shelf life and substantial equivalence to predicates), the primary acceptance criterion is that the modified devices (with extended shelf life) maintain the same safety and effectiveness as the predicate devices. This is achieved by demonstrating that "differences between the Arthrex Meniscal Dart, Arthrex Meniscal Dartstick, and Arthrex Chondral Dart in comparison to the cleared devices in K983577 and K991971 are considered minor and do not raise questions concerning safety and effectiveness" as stated in the Substantial Equivalence Summary. The specific criteria for extended shelf life (e.g., maintaining mechanical properties, sterility, biocompatibility over a longer period) are not explicitly detailed here but would have been part of the full 510(k) submission.
• Reported Device Performance: The document states that the devices are "identical to the predicates" in their basic features and intended uses. Performance would thus be considered equivalent to the predicate devices. No specific performance metrics (like accuracy, sensitivity, specificity for an AI/ML diagnostic) are reported as this is not an AI/ML device.

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

This information is not available in the provided 510(k) summary. Given that this is a traditional medical device and not an AI/ML system, a "test set" in the context of AI model evaluation would not apply. The "study" for extended shelf life would typically involve stability testing, which doesn't directly map to a "test set" as understood for AI/ML.

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 information is not available and is not applicable to this type of device modification. "Ground truth" in the context of expert consensus is not relevant here.

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

This information is not available and is not applicable to this type of device modification.

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

An MRMC comparative effectiveness study is not applicable and was not done, as this is not an AI-assisted device.

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

A standalone performance study for an algorithm is not applicable and was not done, as this is a physical medical device, not an algorithm or AI system.

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

"Ground truth" as defined for AI/ML performance evaluation is not applicable here. The "truth" in this submission relates to the device's physical properties, sterility, and functional equivalence to its predicates over an extended shelf life. This would be established through bench testing, material characterization, and potentially animal/cadaver studies (for the original device, not necessarily for a shelf-life extension).

8. The sample size for the training set

This information is not applicable as this is not an AI/ML device, and therefore, there is no "training set."

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

This information is not applicable as this is not an AI/ML device, and therefore, there is no "training set" or ground truth for one.

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