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The PRO Plating System is indicated for:
· Fractures, non-unions, deformities and malunions of the pelvic ring and acetabulum
• Sacroiliac joint dislocations
The Stryker Trauma Pelvic Set (Matta) is indicated for:
• Fractures of the acetabulum, sacrum, illium, and entire pelvic ring;
• Revision surgery of pseudarthrosis, non-unions and mal-unions;
• Osteonomies;
• Arthrodeses;
• Sacroilic joint dislocations;
• Symphysis pubis disruptions

This Traditional 510(k) submission is being supplied to the U.S. FDA to gain clearance to market the new devices of the PRO Plating System, to align indication of the existing PRO Pelvis System and the new devices and add MRI labeling to the existing PRO Pelvis System and the Trauma Pelvic Set System (Matta). This submission encompasses multiple systems (PRO Pelvis System and Trauma Pelvic Set System (Matta)) that have similar intended use and/or will be used together during the surgical procedure.

The PRO Plating System (Pelvis II Implant System) is an internal fixation device that consists of different types of plates used with compatible screws to fit different types of fractures in the pelvis. All devices in the system are provided sterile and non-sterile.

The Stryker Trauma Pelvic Set System (Matta) consists of plate, screw, and washer components of various sizes. All are manufactured from stainless steel (ASTM F-138/139). All devices in the system are provided sterile and non-sterile.

This document describes a 510(k) premarket notification for the Stryker PRO Plating System and Stryker Trauma Pelvic Set (Matta). This submission is for a medical device (bone fixation appliances and accessories), not for an AI/ML powered device. As such, the sections regarding AI/ML performance criteria, ground truth, expert adjudication, and comparative effectiveness studies are not applicable.

Here's a summary of the non-clinical performance data provided, as relevant to this type of device:

1. Table of Acceptance Criteria and Reported Device Performance

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

This document does not specify the exact sample sizes used for each non-clinical test. For mechanical and MRI compatibility testing of medical devices, samples are typically chosen to represent the range of device types, sizes, and materials. The data provenance is implied to be from internal laboratory testing conducted by Stryker or a qualified testing facility, relevant to the manufacturing location (Selzach, Switzerland) and for the US market. The data is non-clinical/pre-clinical.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

Not applicable. This device is not an AI/ML device that requires expert-established ground truth for its performance assessment. The "ground truth" for this type of device is established through engineering and material science principles, and adherence to recognized standards like ASTM.

4. Adjudication Method for the Test Set

Not applicable. This device is not an AI/ML device requiring human adjudication of its output.

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

No, an MRMC comparative effectiveness study was not done as this is not an AI/ML diagnostic or assistive device.

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

Not applicable. This is a physical medical implant, not an algorithm, so standalone performance in the context of AI/ML is irrelevant.

7. The Type of Ground Truth Used

The ground truth for this device's performance is based on established engineering principles, material science, and conformance to recognized consensus standards (e.g., ASTM F382, F2052, F2213, F2182, F2119). These standards define the methodologies and acceptable performance metrics for the tested properties.

8. The Sample Size for the Training Set

Not applicable. This is a physical medical device, not an AI/ML model, so there is no "training set."

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

Not applicable, as there is no training set for this type of medical device.

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The Stryker Trauma Pelvic Set is indicated for:

• Fractures of the acetabulum, sacrum, illium, and entire pelvic ring
• Revision surgery of pseoduarthroses, non-unions and mal-unions
• Osteonomies
• Arthrodeses
• Sacroilic joint dislocations
• Symphysis pubis disruptures

The Stryker Trauma Pelvic Set consists of reconstruction plates, acetabulum plates, and symphysis-pubis plates. All reconstruction plates, acetabulum plates, and symphysis-pubis plates are available in 1.2mm, 2.0mm, and 2.5mm thicknesses. The symphysis-pubis plates are also available in a 12.5mm width and 1.2mm thickness. The subject components vary in length from 20mm to 200mm. The system also includes 3.5mm diameter and 4.5mm diameter screws. All devices in the system are provided both sterile and non-sterile.

This document is a 510(k) Premarket Notification Summary for the Stryker Trauma Pelvic Set, a medical device. It does not contain information about acceptance criteria or a study proving the device meets acceptance criteria in the context of device performance metrics often associated with AI/ML devices (e.g., sensitivity, specificity, AUC).

Instead, this submission focuses on demonstrating substantial equivalence to a predicate device, which is a regulatory pathway for medical devices in the United States. In this context, "acceptance criteria" are related to satisfying the regulatory requirements to show that the new device is as safe and effective as a legally marketed predicate device.

Here's why the requested information cannot be provided from this document:

1. AI/ML Device Performance Metrics: The Stryker Trauma Pelvic Set is a set of bone fixation plates and screws, not an AI/ML diagnostic or predictive device. Therefore, metrics like sensitivity, specificity, AUC, or the concepts of "ground truth," "test set," "training set," "experts," or "adjudication methods" as applied to AI/ML performance are not relevant or discussed in this type of submission.

2. Substantial Equivalence: The "study" mentioned here is the comparison made by the manufacturer to demonstrate substantial equivalence to a predicate device (Synthes Pelvic Implant Set). The "proof" is the argument presented to the FDA that the devices are similar in design, materials, and intended use.

3. No Clinical Effectiveness Study (in the AI/ML context): This document does not detail a clinical study designed to measure the performance of the device in terms of diagnostic accuracy or a human-AI comparison. Substantial equivalence typically relies on technological comparison and, if needed, non-clinical bench testing or materials testing, rather than large-scale comparative clinical trials for performance metrics.

Based on the provided document, I can only extract information relevant to the regulatory approval process for a traditional medical device, not the performance evaluation of an AI/ML algorithm.

If this were an AI/ML device, the table would look like this (but the data is not available in the provided text):

Here's what can be extracted from the document regarding the device and its regulatory submission:

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

   • Acceptance Criteria (Regulatory): The primary acceptance criterion for this 510(k) submission is that the Stryker Trauma Pelvic Set is substantially equivalent to the Synthes Pelvic Implant Set in design, materials, and intended use.
   • Reported Device Performance: The document states, "The subject components of the Stryker Trauma Pelvic Set are substantially equivalent in design and intended use to the predicate device offered by Synthes." No specific performance metrics (e.g., mechanical strength benchmarks, clinical outcome data) are quantified and presented for comparison against a pre-defined acceptance threshold in this summary. The "performance" is implicitly deemed equivalent to the predicate.

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/Not mentioned in the context of device performance testing. This is a traditional medical device submission, not an AI/ML algorithm requiring a test dataset of patient data. The "test" here refers to the FDA's evaluation of the substantial equivalence claim.

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 "test set" in the AI/ML sense, nor is there a "ground truth" established by experts for performance evaluation of a diagnostic or predictive algorithm.

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

   • Not applicable for a traditional medical device demonstrating substantial equivalence.

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 an implantable surgical kit, not an AI-assisted diagnostic tool.

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 a standalone algorithm.

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

   • Not applicable in the AI/ML sense. The "ground truth" for this submission is the regulatory standard of substantial equivalence, which is assessed against the predicate device.

8. The sample size for the training set:

   • Not applicable. There is no AI/ML model being "trained."

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

   • Not applicable.

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