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The ANTHEM™ Fracture System is indicated for fixation of fractures, arthrodesis and reconstruction of bones for the appropriate size of the device to be used in adult patients, including the clavicle, scapula, humerus, radius, ulpa, small bones (metacarpals, metatarsals, phalanges), wrist, pelvis, fibula, ankle, and foot. Small fragment and distal fibula plates may be used in all pediatric subgroups (except neonates) and small stature adults. Distal radius plates may be used in adolescents (12-21 years of age).

The ANTHEM™ Fracture System is a family of plates and screws designed to be used for internal bone fixation. The implants are available in various sizes and shapes to accommodate patient anatomy, and may be contoured or straight, sterile and non-sterile, with locking and non-locking screws. ANTHEM™ implants are manufactured from medical grade titanium alloy, cobalt chromium molybdenum alloy, or stainless steel. All implants are for single use only.

This document is a 510(k) Summary for the ANTHEM™ Fracture System, a medical device. Based on the provided text, there is no study described that proves the device meets specific acceptance criteria based on AI/algorithm performance, nor is there any mention of an AI device. The document explicitly describes the ANTHEM™ Fracture System as a system of "plates and screws designed to be used for internal bone fixation."

Therefore, I cannot provide the requested information regarding:

• A table of acceptance criteria and reported device performance related to AI/algorithmic accuracy.
• Sample size and data provenance for an AI test set.
• Number of experts and qualifications for AI ground truthing.
• Adjudication method for an AI test set.
• MRMC comparative effectiveness study for AI assistance.
• Standalone AI performance.
• Type of ground truth used for AI.
• Sample size for training set for AI.
• How ground truth for a training set was established for AI.

The document focuses on the mechanical and material performance of bone fixation devices, not on diagnostic or AI-driven performance.

Here's a summary of the performance data that is mentioned in the document, which pertains to the physical device itself:

1. Acceptance Criteria and Reported Device Performance (for the physical device):

• Acceptance Criteria (Implicit Standard Performance): The device's performance was evaluated in accordance with recognized ASTM standards for bone fixation devices. This implies that the device had to meet performance benchmarks defined by these standards to demonstrate substantial equivalence to predicate devices. While specific numerical acceptance criteria are not explicitly stated (e.g., "minimum bending strength of X N-m"), the adherence to these standards serves as the implicit acceptance criteria for mechanical performance.
• Reported Device Performance:
  • Tests Conducted: Engineering analysis, bending strength tests (for plates and screws), pullout strength tests (for screws), and insertion/removal torque tests (for screws).
  • Outcome: "Performance data demonstrates substantial equivalence to the predicate devices."
  • Bacterial Endotoxin Testing (BET): Conducted in accordance with ANSI/AAMI ST-72:2011 to ensure sterility or low endotoxin levels.

2. Sample Size and Data Provenance (for the physical device testing):

• The document does not specify the sample sizes used for the mechanical performance tests (e.g., how many plates or screws were tested for bending strength).
• The data provenance is not mentioned (e.g., where the tests were conducted, whether the materials were from specific batches, etc.).

3. Number of experts used to establish the ground truth... and qualifications of those experts:

• Not applicable. This document is about a physical medical device (bone plates and screws), not an AI algorithm requiring expert review for ground truth.

4. Adjudication method for the test set:

• Not applicable. This document is about a physical medical device (bone plates and screws), not an AI algorithm.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done...:

• Not applicable. This document is about a physical medical device (bone plates and screws), not an AI algorithm.

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

• Not applicable. This document describes a physical medical device, not an algorithm.

7. The type of ground truth used:

• For the physical device, "ground truth" would be the objective measurements obtained from standardized mechanical tests (e.g., actual force at failure, actual torque values) against the requirements of the ASTM standards.

8. The sample size for the training set:

• Not applicable, as this is not an AI/machine learning device.

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

• Not applicable, as this is not an AI/machine learning device.

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The Biomet Proximal Humerus Plating System is indicated for fixation of fracture dislocations, fusions, osteotomies and non-unions of the humerus, particularly in osteopenic bone.

The Biomet Proximal Humeral Plating System offers two plating families (Low and High) with both left and right configurations in various lengths. Both plating families in the Biomet Proximal Humerus Plating System incorporate the same spatial subchondral support as the Biomet S3 proximal humerus plates (K060290) in the head of the plates. The plates and screws will be manufactured from Titanium Alloy (ASTM F136) and are either type II or color anodized. The system will also include multidirectional screws that are manufactured from Cobalt Chromium (ASTM F1537). The plates are anatomically designed to match the anatomy of the proximal humerus. The system will also include instrumentation to aid the user in alignment and stabilization of fractures to the skeletal system.

The provided text describes the Biomet Proximal Humerus Plating System, a metallic bone fixation device, and states that substantial equivalence was determined based on non-clinical tests. However, it does not provide specific acceptance criteria or details of a study that proves the device meets such criteria in terms of performance metrics (like sensitivity, specificity, accuracy, etc., which are typical for AI/diagnostic devices).

The document is a 510(k) summary for a medical device that appears to be a physical implant, not a software or AI-driven diagnostic device. Therefore, the concepts of "acceptance criteria" and "performance" in the context of AI/diagnostic tools (e.g., sensitivity, specificity, MRMC studies, ground truth establishment) are not applicable here. Instead, the "performance" discussed relates to the mechanical and material characteristics of the implant and its substantial equivalence to predicate devices.

Here's an attempt to answer the questions based on the provided text, while noting the difference in device type:

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

Since this is a physical implant and not a diagnostic/AI device, the "acceptance criteria" are not presented in terms of typical performance metrics like sensitivity or specificity. Instead, the criteria are focused on demonstrating substantial equivalence to existing predicate devices in terms of intended use, indications for use, materials, design features, and sterilization. The reported "performance" relates to the results of non-clinical tests that support this substantial equivalence.

Regarding the specific questions tailored for AI/diagnostic devices:

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 is a physical implant, not an AI/diagnostic device that uses a "test set" of data in the common sense for AI. The "tests" were non-clinical mechanical/material tests. The document does not specify a "sample size" for these physical tests in a way that would be relevant to data analysis.

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: There is no "ground truth" in the context of this device being an implant. The "ground truth" for substantial equivalence is based on engineering principles, materials science, and regulatory comparisons to predicate devices.

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

• Not Applicable: No adjudication method is described or relevant for this type of device and its non-clinical testing.

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: No MRMC study was conducted or is relevant for this implant device. The concept of "human readers" or "AI assistance" does not apply.

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

• Not Applicable: This is not an algorithm or AI device; therefore, no standalone performance study in that sense was conducted.

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

• Not Applicable: As mentioned, ground truth in the context of an AI/diagnostic device is irrelevant here. The basis for safety and effectiveness is established through comparison to predicate devices, material standards (ASTM), and non-clinical mechanical testing, rather than a clinical ground truth.

8. The sample size for the training set

• Not Applicable: There is no training set for this physical implant device.

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

• Not Applicable: There is no training set or ground truth in the context of AI for this device.

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