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BePOD® EZ Weil screws are designed for the following indication:
-Treatment of metatarsalgia on the lateral metatarsal shafts (side toes), by Weil osteosynthesis, following osteotomies carried out:

• by the opened surgery (standard Weil) technique,
• by the DMMO percutaneous technique (Distal Metatarsal Mini Invasive Osteotomy).

The BePOD® EZ Weil Screws are threaded titanium screws which are self-drilling and selftapping designed for use in the foot. Once completely implanted, the screw is designed so the surgeon can snap off the introducer at the snap off axis.
The BePOD® EZ Weil Screws is intended to be implanted using the dedicated instrumentation supplied by the manufacturer.

This document is a 510(k) premarket notification for a medical device called "BePOD® EZ Weil Screws." It describes the device's intended use and compares it to predicate devices to establish substantial equivalence for regulatory approval.

Based on the provided text, the device is a bone fixation fastener (specifically, screws for foot surgery). The document does not describe an AI/ML-based medical device or a study involving acceptance criteria for AI/ML performance, human readers, ground truth establishment, or training/test sets in the context of diagnostic or prognostic performance.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves the device meets the acceptance criteria in the context of AI/ML device performance, as the document does not contain this information.

The document focuses on:

• Device Type: Metallic bone fixation screws.
• Indications for Use: Treatment of metatarsalgia on lateral metatarsal shafts by Weil osteosynthesis (open surgery or percutaneous technique).
• Substantial Equivalence: Comparison to legally marketed predicate devices based on materials, size ranges, and design features.
• Non-Clinical Testing: Mentions "Engineering Analysis" and "LAL pyrogen testing" but these are mechanical and biocompatibility tests, not performance studies as requested for AI/ML.

The "study" referenced in the document is a comparison for substantial equivalence, not a performance study as would be conducted for an AI/ML diagnostic or prognostic tool.

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THE ARROW ANATOMICAL POROUS GLENOID, DEPENDING ON THE COMPONENTS USED, IS DESIGNED FOR:

• CENTRED GLENOHUMERAL OSTEOARTHRITIS -
• RHEUMATOID POLYARTHRITIS -
• POST-TRAUMATIC SEQUELA WITH GLENOID INJURY -
• -FRACTURES OF THE PROXIMAL HUMERUS WITH GLENOID INJURY
• REVISION FOR GLENOID LOOSENING -
• GLENOID BONE LOSS. WHERE BONE GRAFT IS NEEDED -
• A FUNCTIONAL ROTATOR CUFF IS NECESSARY TO USE THIS DEVICE

THE POROUS GLENOID BASE IS INTENDED FOR CEMENTLESS APPLICATION WITH THE ADDITION OF BONE SCREWS FOR FIXATION

The ARROW anatomical porous glenoid consists of a glenoid insert and a porous glenoid base. The porous glenoid base is used with bone screws for fixation (cleared in K112193). The glenoid inserts and the porous glenoid bases are used in total anatomical prosthesis and are designed to articulate with the ARROW anatomical shoulder system (cleared in K093599).

The ARROW anatomical porous glenoid is intended to be implanted using the dedicated instrumentation supplied by the manufacturer. This instrument set is common for all the configurations of prosthesis namely: simple humeral prosthesis, total anatomical prosthesis (cemented glenoid implant with 4 pegs), total anatomical prosthesis (porous glenoid implant), pending, and reverse prosthesis.

The provided text is a 510(k) Summary for a medical device called "ARROW® ANATOMICAL POROUS GLENOID." This document focuses on demonstrating substantial equivalence to predicate devices based on design, materials, and performance testing, rather than reporting on a clinical study involving human subjects or AI-assisted diagnostic performance.

Therefore, the requested information regarding acceptance criteria and performance data from a study involving AI assistance or human-in-the-loop performance cannot be extracted from this document. The document describes mechanical performance testing, not clinical performance for diagnostic or treatment effectiveness in the way an AI diagnostic device would.

Here's what can be extracted based on the document:

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

The document states: "The ARROW anatomical porous glenoid was tested according to the ASTM F 1829 and ASTM F 2028 standards. After the tests were completed, it was determined that the ARROW anatomical porous glenoid performances were substantially equivalent to those of the selected predicate devices."

It does not provide specific numerical acceptance criteria or detailed results from these tests, only that the device met the standards and was "substantially equivalent."

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

Not applicable. This document describes mechanical testing of a medical implant, not a clinical study involving a test set 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. Ground truth for mechanical testing is established by engineering specifications and standard test methods (ASTM F 1829 and ASTM F 2028), not by expert human interpretation.

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

Not applicable, as this is not a diagnostic performance study requiring adjudication.

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 document does not describe any MRMC study or AI assistance.

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

Not applicable. This document pertains to a physical medical implant, not an algorithm.

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

Not applicable. For mechanical testing, the "ground truth" would be established by the ASTM standards themselves and the physical properties of the materials and design, verified through laboratory measurements.

8. The sample size for the training set

Not applicable. This document describes mechanical performance testing, not the development of an AI algorithm.

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

Not applicable. There is no training set mentioned in this document.

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The ARROW® Reverse Shoulder long keel and short keel glenoid base is indicated for patients with severe shoulder arthropathy and a grossly deficient rotator cuff or a previously failed shoulder joint replacement with a grossly deficient rotator cuff. A functional deltoid muscle and adequate glenoid bone stock are necessary to use this device. The humeral stem is intended for cemented or cementless application while the metal-back glenoid baseplate is intended for cementless application with the addition of bone screws for fixation.

The ARROW® Reverse Shoulder long keel and short keel glenoid base consist of a metal-back glenoid base, used with bone screws for fixation and assembled with previously cleared glenosphere. These components are used in total reverse prosthesis and are designed to articulate with ARROW® Reverse Shoulder System cleared in K112193.

The bone fixation screws are cleared in K112193.

The ARROW® Reverse Shoulder long keel and short keel glenoid base is intended to be implanted using the dedicated instrumentation supplied by the manufacturer. This instrument set is common for all the configurations of prosthesis (and identical to those for ARROW® anatomical (K093599) and reverse shoulder system (K112193)).

The provided document is a 510(k) premarket notification for a medical device (ARROW® Reverse Shoulder long keel and short keel glenoid base) and focuses on demonstrating substantial equivalence to predicate devices, rather than establishing performance against specific acceptance criteria for a novel device or software. Therefore, much of the requested information regarding acceptance criteria, specific study designs, expert involvement, and ground truth establishment, which are typical for software-as-a-medical-device (SaMD) or diagnostic devices, is not directly applicable or available from this type of regulatory submission.

However, I can extract the information that is present and explain why other aspects are not applicable.

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

The document does not provide a table of explicit acceptance criteria with numerical targets and reported performance values in the way one would typically expect for a diagnostic or AI-driven device. Instead, the "performance" is assessed through a cyclic mechanical protocol to demonstrate substantial equivalence to predicate devices.

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

The "test set" for this device refers to the physical devices subjected to mechanical testing. The document does not specify the exact sample size (number of devices or components tested) used for the cyclic mechanical protocol.

Regarding data provenance, the testing was performed by the manufacturer, Fournitures Hospitalières Industrie, in France. The document does not specify if different batches or manufacturing runs were tested, nor does it refer to "countries of origin" for data in the context of clinical populations, as this is a mechanical testing scenario for an orthopedic implant.

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

This question is not applicable to this type of device and study. For a mechanical device like a shoulder implant component, "ground truth" is not established by human experts in the diagnostic sense. The "ground truth" for mechanical performance is typically defined by engineering specifications, material properties, and validated testing methods (e.g., ISO standards, ASTM standards) that simulate in-vivo conditions. The evaluation of whether the mechanical tests were performed correctly and meet the implicit equivalence criteria would be done by engineers and regulatory reviewers, not medical experts establishing a diagnostic ground truth.

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

This question is not applicable. Adjudication methods like 2+1 or 3+1 are used in clinical studies or for establishing ground truth in diagnostic imaging cases, especially when there's inter-reader variability. For mechanical testing of a medical device, the results are typically quantitative and objective measurements (e.g., strength, fatigue life). The "adjudication" (if one could even call it that) of the test results themselves would be against predefined engineering acceptance criteria, potentially verified by internal quality control or external testing labs, not by a panel of experts.

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

This question is not applicable. An MRMC study is relevant for evaluating the performance of diagnostic devices or AI algorithms that assist human readers (e.g., radiologists). The ARROW® Reverse Shoulder long keel and short keel glenoid base is an orthopedic implant (a physical device), not a diagnostic tool or an AI-assisted system.

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

This question is not applicable. This device is a physical implant, not an algorithm or software. Therefore, there is no "standalone algorithm only" performance to evaluate.

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

The document does not describe "ground truth" in terms of clinical or diagnostic data. For the mechanical testing, the "ground truth" is effectively the performance of the predicate devices and generally accepted mechanical engineering principles and standards for orthopedic implants under simulated physiological loads. The goal was to show that the new device's mechanical performance was "substantially equivalent" to these established benchmarks.

8. The sample size for the training set

This question is not applicable. As this is a physical medical device (an implant), there is no "training set" in the context of an AI algorithm or a statistical model derived from a dataset.

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

This question is not applicable (see response to #8).

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