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The Extremity Medical Screw System is intended for fixation arthrodesis of the metatarsalcuneiform, navicular-cuneiform, metatarsal-cuboid, talonavicular, calcaneocuboid, metatarsalphalangeal and metacarpal-phalangeal joints.

The EXTREMITY MEDICAL Screw System consists of two metallic components a Metacarpal (distal) screw and a Lag Screw (proximal). The two components are designed to rigidly lock together to form an angle between the two components. The system includes common instrumentation for the application of surgical bone screws.

This 510(k) summary describes a medical device, the EXTREMITY MEDICAL Screw System, and its substantial equivalence to predicate devices. It does not contain information about acceptance criteria or a study proving the device meets said criteria in the context of typical AI/software performance evaluation. The document focuses on the regulatory clearance for a physical medical implant.

However, based on the structure of your request and the provided document, I can deduce information related to regulatory acceptance and the studies performed (or not performed) for this physical medical device.

Here's an interpretation framed to address your questions as much as possible, re-interpreting "acceptance criteria" and "study" in the context of a 510(k) submission for a physical implant:

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

For a physical medical device seeking 510(k) clearance, the "acceptance criteria" are typically demonstrating substantial equivalence to a legally marketed predicate device. This is primarily done through showing similar indications for use, design, materials, and equivalent mechanical properties.

2. Sample size used for the test set and the data provenance

• Test Set Sample Size: Not applicable in the context of image data or an AI algorithm’s test set. For the bench testing, specific sample sizes for pull-out strength and torque tests are not provided in this summary. For clinical simulations in cadavers, the summary does not specify the number of cadavers used.
• Data Provenance: Not applicable in the context of geographical origin or retrospective/prospective data as it relates to clinical or imaging datasets, since no clinical or imaging studies were performed for device performance evaluation. The "data" here refers to bench test results which are typically generated in a lab setting.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

• Number of Experts & Qualifications: Not applicable. This summary describes a physical implant which establishes "ground truth" through direct measurement (e.g., of mechanical properties) rather than expert interpretation of data. The adjudication of substantial equivalence is done by FDA reviewers based on the engineering and design comparisons provided by the manufacturer.

4. Adjudication method for the test set

• Adjudication Method: Not applicable. This concept pertains to resolving discrepancies in expert labeling or diagnoses of datasets, which is not relevant for the bench testing and cadaveric simulations described for this physical device.

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

• MRMC Study: No. This type of study (MRMC, AI assistance) is completely irrelevant to the submission for this physical medical screw system.

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

• Standalone Performance Study: No. This is not an AI algorithm.

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

• Type of Ground Truth: For the mechanical properties, the "ground truth" would be established by direct physical measurement using calibrated lab equipment for metrics like pull-out strength and torque, and by comparing these values to those of the predicate devices. For surgical technique verification, the "ground truth" would be the successful and safe application of the device in cadaveric models as assessed by trained surgeons.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This document describes a physical medical device, not an AI algorithm requiring a training set.

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

• Ground Truth for Training Set Establishment: Not applicable, as there is no training set for a physical implant.

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