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Fracture reduction and external fixation for treatment of distal radius fractures.

The WristJack ORIF System is an external fixation system used for reduction and fixation of distal radius fractures. The system includes an adjustable reduction/fixation frame (fixator), application instrumentation and skeletal fixation pins.

The fixator element has multiple adjustments to aid in fracture reduction and stabilization of distal radius fractures. The device and instrumentation are constructed of polyetherimide resin, carbon fiber, stainless steel, titanium and aluminum alloy. The fixation pins are constructed of implant grade 316 stainless steel per ASTM F138.

The provided text is a 510(k) summary for the WristJack ORIF System, an external fixation system for distal radius fractures. This document focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed study proving the device meets specific acceptance criteria in the way a clinical trial for an AI/CADe device would.

Therefore, the information requested about acceptance criteria, study details, sample sizes, expert involvement, and ground truth establishment, which are typical for studies validating AI or diagnostic devices, is largely not present in this type of regulatory submission.

Here's an attempt to answer based on the provided text, highlighting what is (and isn't) available:

1. Table of acceptance criteria and the reported device performance

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

• Not applicable / Not provided. This document is a premarket notification (510(k)) for a medical device (external fixator), not an AI/CADe device. The assessment of substantial equivalence relies on comparing the new device's design, materials, and intended use to a legally marketed predicate device, rather than a clinical study with a "test set" of patient data in the context of an AI algorithm. There is no mention of patient data, clinical trial, or geographical origin of data.

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)

• Not applicable / Not provided. The concept of "ground truth" established by experts for a test set is relevant for AI or diagnostic performance studies. For this external fixator, the "ground truth" for its safety and effectiveness is largely established by its similarity to a previously cleared predicate device, and the engineering and material specifications provided in the submission. The FDA reviewers (Celia M. Witten, Ph.D., M.D., Director, Division of General, Restorative and Neurological Devices, Office of Device Evaluation) are the experts who reviewed the submission.

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

• Not applicable / Not provided. This concept is for resolving discrepancies in expert interpretations within an AI/diagnostic study.

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

• No. An MRMC study is specific to evaluating diagnostic performance, often with AI assistance. This device is an external fixator, not an AI/CADe system.

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

• No. This question is also specific to AI algorithms.

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

• The "ground truth" for this 510(k) submission is the demonstration of substantial equivalence to a predicate device. This involves comparing technological characteristics, materials, and intended use to established standards of safety and effectiveness, rather than a clinical "ground truth" from patient data. The basis for this is engineering comparison, material specifications, and regulatory precedent.

8. The sample size for the training set

• Not applicable / Not provided. This concept applies to AI algorithm development.

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

• Not applicable / Not provided. This concept applies to AI algorithm development.

In summary, the provided document is a regulatory submission for a physical medical device (an external fixator). It demonstrates compliance through substantial equivalence to a predicate device, rather than through a clinical study designed to meet specific performance metrics with patient data, which would be typical for an AI algorithm or diagnostic device.

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