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The EVOS Mini Plating System, excluding EVOS Patella Plates, is indicated for patients 12 – 21 and those over 21 years of age, as well as patients with osteopenic bone. The Smith & Nephew EVOS Mini Plating System is indicated for fracture fixation or reduction of small bones and small bone fragments. This system is also indicated for non-load bearing stabilization of bone fragments in long bones.

The EVOS Patella Plates are indicated for the fixation of patellar fractures for patients over 21 years of age.

The subject EVOS Patella Plates are an extension to the EVOS Mini Fragment system previously cleared under K140814 (S.E. 5/7/2014). The subject bone plates consist of a Staggered Patella Plate, and a Small and Large Mesh Patella Plate. The subject plates are compatible with the previously cleared EVOS 2.7mm locking screws, and partially and fully threaded 4.0mm osteopenia screws (K140814). The proposed plates feature a variable angle locking screw hole feature, are manufactured from implantgrade 316L Stainless Steel material and will be available in a sterile packaged condition.

The provided text describes a 510(k) premarket notification for the "EVOS Patella Plates" and does not contain information about acceptance criteria or a study proving device performance against such criteria. The document is a letter from the FDA confirming substantial equivalence to predicate devices, and a 510(k) summary.

It lists the following nonclinical tests performed:

• Finite element analysis (FEA)
• Four Point Bend Fatigue performance evaluation
• Magnetic resonance imaging (MR) compatibility evaluation per ASTM F2213, ASTM F2182, and ASTM F2119
• Packaging verification testing per ASTM F2096 and ASTM F88

However, it does not provide:

1. A table of acceptance criteria and reported device performance.
2. Sample sizes used for test sets, data provenance, number of experts for ground truth, or adjudication methods.
3. Information on a multi-reader, multi-case (MRMC) comparative effectiveness study or standalone algorithm performance.
4. Type of ground truth used (as these are physical devices, ground truth in the context of diagnostic performance is not applicable).
5. Sample size for the training set or how ground truth for the training set was established.

The document states that Finite Element Analysis (FEA) and predicate clinical data were leveraged to support device performance, suggesting that a specific study proving the EVOS Patella Plates meet defined acceptance criteria beyond the listed non-clinical tests is not detailed within this submission. The focus of a 510(k) summary is to demonstrate substantial equivalence to a predicate device, rather than to present a de novo study proving novel performance criteria.

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The EVOS Wrist Plating System is indicated for adult and pediatric patients with osteopenic bone. It is indicated for fixation of fractures, malunions, and osteotomies involving the radius and ulna.

Subject of this premarket notification is the EVOS Wrist Fragment Plating System. The proposed devices incorporate design features that are currently incorporated on previously cleared Smith & Nephew bone plate and screw systems. Like their previously cleared counterparts, the proposed plates feature a screw-to-plate locking feature that permits their use with the proposed and compatibility designed locking and non-locking cortex screws described in this premarket notification. Each screw hole contains five separate tabs that engage with the threads of the locking screw. The locking screws can be angled and locked up to fifteen degrees in any direction, allowing for custom, multi-directional locked plating constructs. The subject plates can be used with screws previously cleared via K161665, K132296, K993106, K162078, K140814 and K132886 and pegs subject of this premarket notification.

This document describes the submission for the EVOS Wrist Fracture Plating System and does not contain information related to software or AI/ML acceptance criteria or studies. Instead, it focuses on the substantial equivalence of a medical device (bone plating system) to previously cleared predicate devices.

Therefore, I cannot provide the requested information about acceptance criteria and studies proving the device meets those criteria, as it pertains to AI/ML devices. The document details mechanical testing, packaging verification, bacterial endotoxin testing, and biocompatibility testing for a physical implantable device, not a software algorithm.

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The EVOS Small Fragment Plating System is indicated for adult and pediatric patients with osteopenic bone. It is indicated for fixation of small and long bone fractures, including, but not limited to, those of the tibia, fibula, femur, humerus, ulna, radius, pelvis, acctabulum, metacarpals, metatarsals, and clavicle.

The subject of this special premarket notification is a modification in the manufacturing process for select EVOS Small Fragment Straight Plates that were previously cleared via K162078. Also subject to this special premarket notification is the addition of EVOS 3.5mm Locking Hole Inserts and EVOS 3.5mm Washers and Double Washers. The subject devices are intended to be used with existing Smith & Nephew implants and instruments that have been previously cleared for market for use with the EVOS Small Fragment Plating System.

This document is a 510(k) premarket notification for the EVOS Small Fragment Plating System. The focus of the changes discussed in this submission is on manufacturing process modifications and the addition of new components (locking hole inserts and washers), rather than providing a detailed study that proves the device meets specific performance acceptance criteria in a clinical setting.

Therefore, the requested information cannot be fully provided as the document does not contain details about:

• A specific clinical study proving device performance against acceptance criteria.
• Sample sizes for test sets, data provenance, number of experts, adjudication methods, or MRMC studies.
• Standalone algorithm performance.
• Specific ground truth types or training set details.

However, based on the provided text, here is what can be inferred about the pre-clinical engineering testing and its acceptance criteria:

1. Table of Acceptance Criteria and Reported Device Performance (Pre-clinical Engineering Testing)

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

• Sample Size: Not explicitly stated for each test, but referred to as "worst-case designs" for plate fatigue testing.
• Data Provenance: This is pre-clinical engineering testing, not clinical data from patients or a specific country. It's a lab-based study to assess mechanical properties and biocompatibility.

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

• Not applicable as this is pre-clinical mechanical and biological testing, not a study involving human expert interpretation of data like images.

4. Adjudication method for the test set

• Not applicable for pre-clinical mechanical and biological 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. This is not an AI/imaging device.

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

• Not applicable. This is not an AI/imaging device.

7. The type of ground truth used

• For the plate and locking hole insert bending fatigue tests, the "ground truth" would be established by the physical testing methods themselves (e.g., measuring force, displacement, cycles to failure) against predefined engineering specifications derived from predicate devices and industry standards.
• For bacterial endotoxin levels, the ground truth is established by the LAL (Limulus Amebocyte Lysate) method, which is a standard assay for endotoxin detection.

8. The sample size for the training set

• Not applicable. This is pre-clinical testing, not a machine learning model.

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

• Not applicable. This is pre-clinical testing, not a machine learning model.

In summary: The provided document is a 510(k) submission focusing on demonstrating substantial equivalence through engineering rationales and pre-clinical mechanical and biological testing. It does not include information about clinical studies with human subjects or AI performance, which are the typical contexts for many of the questions asked. The "acceptance criteria" here refer to engineering performance benchmarks.

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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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