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The Paragon 28 Patient Specific Marking Guide is intended to be used as a surgical instrument to assist in preoperative planning and/or in guiding the marking of bone and/or in guiding surgical instruments in non-acute, non-joint replacing osteotomies for adult patients in the foot ankle. The Patient Specific Guide is not intended to directly guide the cutting of bone. The device is single use only.

The Paragon 28 Patient Specific Marking Guides are designed and additively manufactured based on an individual patient's CT scan(s). In surgery, these guides, templates, or anatomical models are used to assist a surgeon in guiding the marking of a bone and/or guiding a surgical instrument for placement (i.e., placing a k-wire). The guides are not used for cutting bone. All guides are patient specific and utilize a CT scanning protocol previously cleared in K180239 (Paragon 28 formerly Additive Orthopaedics). The anatomical landmarks necessary for the design and creation of the Patient Specific Marking Guides must be present and identifiable on computed tomography scan.

The Paragon 28 Patient Specific Marking Guides are additively manufactured from biocompatible nylon (PA 2200 - polyamide 12 white) and produced by laser sintering. The Patient Specific Marking Guides are optional for surgeons to help visualize and plan osteotomies in the foot and ankle and are for single use only.

The provided text is a 510(k) summary for the Paragon 28 Patient Specific Marking Guides. It describes the device, its intended use, and substantial equivalence to a predicate device, supported by various performance tests. However, it does not contain the specific details requested regarding acceptance criteria for device performance, a study proving those criteria were met, sample sizes for test or training sets, data provenance, number or qualifications of experts, adjudication methods, multi-reader multi-case studies, standalone performance, or how ground truth was established for training data.

Therefore, I cannot fulfill your request for that specific information based solely on the provided text.

The closest information provided related to performance is:

1. A table of acceptance criteria and the reported device performance
No explicit table of acceptance criteria or quantitative reported device performance is provided in the document. The general statement is that "a cadaver lab were conducted to prove the subject device performs in accordance with its intended use."

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document mentions a "Cadaver Study" but does not specify the sample size (number of cadavers or cases) or the provenance of the 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)
This information is not provided.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided.

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 information is not provided. The device is a physical instrument, not an AI-assisted diagnostic tool, so an MRMC study in this context would be unlikely.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not provided. The device is a surgical guide, not a standalone algorithm.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For the cadaver study, the "ground truth" would implicitly be the actual anatomical marking or instrument placement achieved by the surgeon using the guide, compared to the intended pre-operative plan. However, the specific method of establishing this ground truth (e.g., measurement, expert verification) is not described.

8. The sample size for the training set
This device is designed based on individual patient CT scans. There is no "training set" in the traditional machine learning sense, as it's a patient-specific physical device, not an algorithm being trained. Each guide is custom-made based on one patient's data.

9. How the ground truth for the training set was established
As there isn't a traditional training set, this question is not applicable. The design of each guide is based on the anatomical data from the specific patient's CT scan.

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The Additive Orthopaedics 3D Printed Bone Segments are intended to be used for internal bone fixation for bone fractures or osteotomies in the ankle and foot, such as:

*Cotton (opening wedge) osteotomies of the medial cuneiform *Evans lengthening osteotomies

The Additive Orthopaedics 3D Printed Bone Segments are intended for use with ancillary plating fixation.

The Additive Orthopaedics 3D Printed Bone Segments are not intended for use in the spine.

It is a patient specific device.

The Additive Orthopaedics Patient Specific 3D Printed Bone Segments is a simple one piece device constructed individually for each patient using CT image data. It is intended to be used for internal bone fixation for bone fractures or osteotomies in the foot and ankle. The segments are additively manufactured from medical grade titanium alloy (Ti-6AL-4V Eli). It is a patient specific device. The bone segments come in a variety of configurations that depend on the geometry of the application. The surgeon approves the design of the 3D Printed Bone Segments by comparing his/her design requirements to engineering drawings prior to the construction of the implant device.

This is a 510(k) premarket notification for a medical device, not an AI/ML device. Therefore, the requested information about acceptance criteria and studies (such as MRMC, standalone performance, ground truth, sample sizes for training/test sets, and expert qualifications) is not typically found in this type of document because it pertains to the evaluation of AI/ML algorithm performance.

Here's what can be extracted from the document regarding the device's evaluation, rephrased to align with the spirit of the request, focusing on how the device meets the regulatory requirements for "substantial equivalence":

Device Name: Additive Orthopaedics Patient Specific 3D Printed Bone Segments
510(k) Number: K180239

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a non-AI/ML device submission, there are no "acceptance criteria" in the traditional sense of performance metrics like AUC, sensitivity, or specificity. Instead, the "acceptance criteria" are related to demonstrating substantial equivalence to a predicate device. The "performance" is shown through comparative testing against that predicate.

Study Proving Device Meets Criteria (Substantial Equivalence Study):

The submission highlights a substantial equivalence study based on non-clinical evidence.

2. Sample Size Used for the Test Set and Data Provenance:

This information is not applicable and not provided in the document. The evaluation is based on demonstrating equivalence in materials, manufacturing, indications, and non-clinical performance characteristics (morphological, mechanical, biocompatibility) rather than a "test set" of patient data for an algorithm. The "data" here refers to test results from the device itself and the predicate.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

This information is not applicable. "Ground truth" in the context of an AI/ML device (e.g., expert consensus on medical images) is not relevant for this type of device submission. The verification of the patient-specific design is done by the surgeon.

4. Adjudication Method for the Test Set:

Not applicable. There is no "test set" in the sense of evaluating diagnostic performance.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

No, an MRMC study was not done. This type of study is relevant for evaluating the impact of AI on human reader performance, which doesn't apply to this 3D-printed bone segment device.

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

Not applicable. This device is a physical, patient-specific implant, not a standalone algorithm.

7. The type of ground truth used:

The concept of "ground truth" (e.g., pathology, outcomes data) as it applies to AI/ML diagnostic or prognostic devices is not relevant here. For device design, the "ground truth" for the patient-specific geometry is derived from the patient's CT image data and subsequently "verified by the surgeon."

8. The Sample Size for the Training Set:

Not applicable. There is no machine learning "training set" for this device. The device is custom-designed for each patient based on their CT scan data.

9. How the Ground Truth for the Training Set was Established:

Not applicable, as there is no training set. The patient-specific designs are generated using individual patient CT image data, and the final design is approved by the surgeon.

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The Additive Orthopaedics Bunion System is indication and fusion of fractures, ostotomies and arthrodesis of small bones such as the foot and ankle.
The Additive Orthopaedics Bunion System is indicated for alignment, stabilization and fusion of fractures, osteotomies and arthrodesis of small bones such as the foot and ankle.

The Additive Orthopaedics Bunion System consists of a plate and screws (both locking and nonlocking) with surgical site preparation and insertion instruments. The devices is intended to be used for fixation following an osteotomy in bunion correction procedures. The plates are additively manufactured from medical grade titanium alloy (Ti-6AL-4V Eli). The screws are manufactured from medical grade titanium alloy. (Ti-6AL-4V). The implants are provided sterile and intended for single use only. The bunion plate comes in 1 individual size and the screws come in 4 lengths.

The provided document is a 510(k) premarket notification for a medical device called the "Additive Orthopaedics Bunion System." This document does not describe a study involving an AI/Machine Learning device and human readers, nor does it provide acceptance criteria and performance metrics in the way requested for such studies.

This document describes a traditional medical device (metallic bone fixation appliances) and focuses on demonstrating substantial equivalence to pre-existing predicate devices through mechanical testing and comparison of technological characteristics.

Therefore, I cannot extract the requested information regarding acceptance criteria, device performance, sample sizes, expert qualifications, ground truth, MRMC studies, or training sets, as these are not relevant to the content of this 510(k) submission.

Key takeaway from the document:

• Device: Additive Orthopaedics Bunion System (plate and screws for bone fixation).
• Purpose: To demonstrate substantial equivalence to legally marketed predicate devices for the indication of alignment, stabilization, and fusion of fractures, osteotomies, and arthrodesis of small bones (foot and ankle).
• Methods of demonstration: Comparison of technological characteristics (indications, dimensions, geometry, materials, manufacturing process) and mechanical testing (4-point bending per ASTM F382, static driving torque, removal torque, static axial pullout per F543).
• Conclusion: The device is substantially equivalent to the predicate devices and is expected to perform at least as well.

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The Additive Orthopaedics Locking Lattice Plate is indicated for alignment, stabilization and fusion of fractures, osteotomies and arthrodesis of small bones such as the foot and ankle.

The Additive Orthopaedics Lattice Locking Plates consist of a plate and locking and non-locking screws with surgical site preparation and insertion instruments. It is indicated for alignment, stabilization and fusion of fractures, osteotomies and arthrodesis of small bones such as the foot and ankle. The plates are additively manufactured from medical grade titanium alloy (Ti-6AL-4V Eli). The screws are manufactured from medical grade titanium alloy. (Ti-6AL-4V Eli). The implants are provided sterile and intended for single use only. The locking lattice plate and screws come in multiple sizes.

The provided text is a 510(k) premarket notification for a medical device (Additive Orthopaedics Locking Lattice Plate). It describes the device, its intended use, and claims substantial equivalence to predicate devices based on non-clinical evidence. However, this document does not contain information about acceptance criteria or a study proving the device meets said criteria in the context of an AI/algorithm-based diagnostic or assistive device.

The document describes a mechanical device, specifically a surgical plate, and the assessment of its physical properties for substantial equivalence to existing similar devices. It does not involve any AI algorithms, human readers, ground truth establishment through expert consensus, or performance metrics like sensitivity, specificity, or AUC, which are typically found in studies for AI-powered medical devices.

Therefore, I cannot provide the requested information based on the provided text, as the context is entirely different.

Here's why and what the document does discuss regarding evaluation:

• Device Type: The "Additive Orthopaedics Locking Lattice Plate" is a physical implant used for bone fixation.
• Evaluation Method: The document relies on "Substantial Equivalence - Non-Clinical Evidence" which includes mechanical testing (e.g., 4-point bending, static torsion, static axial pullout) per ASTM standards (F382, F543) and bacterial endotoxin testing (LAL pyrogen testing).
• "Acceptance Criteria" in this context: The "acceptance criteria" are implied by meeting the performance demonstrated by the predicate devices through the specified ASTM standards and pyrogen limits (e.g., "Pyrogen levels for the device system were below the 20 EU/device limit"). The study demonstrating this is the mechanical and biological testing itself.
• No AI/Algorithm: The concepts of "test set," "training set," "ground truth experts," "adjudication," "MRMC study," or "standalone algorithm performance" are not applicable because this is not an AI-driven device.

To reiterate, the requested information cannot be extracted from the provided text because it pertains to an entirely different type of medical device evaluation (mechanical implant vs. AI/diagnostic software).

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The Additive Orthopaedics Bone Wedges are intended to be used for internal bone fixation for bone fractures or osteotomies in the ankle and foot, such as:

*Cotton (opening wedge) osteotomies of the medial cuneiform
*Evans lengthening osteotomies

The Additive Orthopaedics Bone Wedges are intended for use with ancillary plating fixation.

The Additive Orthopaedics Bone Wedges are not intended for use in the spine.

The Additive Orthopaedics Bone Wedge System is a series of wedge-shaped devices intended to be used for internal bone fixation for bone fractures or osteotomies in the foot and ankle. The wedges are additively manufactured from medical grade titanium alloy (Ti-6AL-4V Eli). The implants are provided sterile and intended for single use only. The wedges come in 18 individual sizes and configurations to correct various skeletal deformities in the foot. The Additive Orthopaedics Bone Wedge System is intended to be used with ancillary plating fixation.

I am unable to provide a description of the acceptance criteria and the study that proves the device meets the acceptance criteria based on the provided text.

The document is a 510(k) premarket notification letter from the FDA to Additive Orthopaedics, LLC regarding their Bone Wedge System. It confirms that the device has been found substantially equivalent to legally marketed predicate devices.

While the document mentions "mechanical testing (including, friction, roughness, durability/abrasion, and compressive fatigue)" and "biocompatibility testing" as part of the "Non-Clinical Evidence" used to demonstrate substantial equivalence, it does not provide:

• Specific acceptance criteria: It states that these activities "demonstrate that the Additive Orthopaedics Bone Wedges are substantially equivalent," but doesn't list the quantitative acceptance thresholds for these tests.
• Detailed study results: It doesn't report the actual performance data from these tests against any acceptance criteria.
• Information related to human reader studies or ground truth establishment: The nature of this device (bone wedges for internal fixation) means that an "AI" component as typically understood in diagnostic software is not applicable here. Therefore, information about sample sizes for test sets, data provenance, number of experts for ground truth, adjudication methods, MRMC studies, standalone performance, or training set details are not relevant or present in this document.

The document primarily focuses on establishing "substantial equivalence" based on similar indications, dimensions, geometry, and materials, supported by general non-clinical testing. It does not contain the detailed study information you requested for an AI/software device.

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The Additive Orthopaedics Hammertoe Correction System is indicated for fixation of fractures, and fusion of small bones in the foot and hand; where such fragments are not under tension or load-bearing.

The Additive Orthopaedics Hammertoe Correction System is a monoblock non-circular shaft implant that is cannulated and non-cannulated and incorporates barbs along its longitudinal axis. The system is provided with a drill designed for preparation of the implant site. The implant device, and the drill, are provided in a sterile procedure pack. The implant is intended for single use only and it is available in 0° and 10° configurations. The implant device is additively manufactured from medical grade titanium alloy (Ti-6A1-4V).

This document is a 510(k) premarket notification for a medical device (Additive Orthopaedics Hammertoe Correction System), not a study report or clinical trial. Therefore, it does not contain the detailed information typically found in a study proving a device meets acceptance criteria, especially for AI/ML-based devices.

The document focuses on demonstrating substantial equivalence to existing legally marketed predicate devices, rather than establishing de novo performance criteria with specific acceptance thresholds for a novel device.

However, based on the provided text, I can infer and extract some relevant information:

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

The document does not specify quantitative acceptance criteria in a table format, nor does it report specific performance metrics with numerical values in relation to such criteria. Instead, it states that "Mechanical testing was performed as described in relevant recognized standards, including testing for pull-out force, static and dynamic flexion extension resistance." It then concludes, "From the evidence submitted in this 510(k), the subject devices can be expected to perform at least as well as the predicate device."

This implies that the acceptance criterion for substantial equivalence was that the device's mechanical performance, as measured by standard tests, was comparable to or better than predicate devices. The reported device performance is summarized as meeting this comparability standard, rather than providing specific numerical results.

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

• Sample size for test set: Not explicitly stated. The document refers to "mechanical testing," which typically involves a set number of physical samples, but the exact number isn't provided.
• Data provenance: Not explicitly stated, but the testing would have been conducted on manufactured devices in a laboratory setting. This is not clinical data (retrospective or prospective from human patients) but rather engineering/mechanical test data.

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 in this context. Mechanical testing of a bone fixation device does not involve human experts establishing ground truth in the same way an AI diagnostic tool would. The "ground truth" for mechanical testing is based on objective physical measurements according to established engineering standards.

4. Adjudication method for the test set:

Not applicable. There's no human interpretation or adjudication in the context of mechanical performance testing as described.

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 device is a physical Hammertoe Correction System (implant), not an AI-assisted diagnostic or therapeutic tool for "human readers."

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

Not applicable. This is a physical medical device, not an algorithm.

7. The type of ground truth used:

For mechanical testing, the "ground truth" would be the objective physical measurements obtained during the tests (e.g., actual pull-out force values, flexion/extension resistance) against established engineering standards and comparative data from predicate devices. It is not expert consensus, pathology, or outcomes data in the clinical sense.

8. The sample size for the training set:

Not applicable. This is a physical device undergoing mechanical testing, not an AI/ML system requiring a training set.

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

Not applicable. This is a physical device, not an AI/ML system.

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