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The SternalPlate system is indicated for use in stabilization and fixation of fractures of the anterior chest wall including sternal fixation following sternotomy, sternal fracture(s), and sternal reconstructive surgical procedures to promote bony fusion.

The Subject Device System contains various plates with different shapes which allow for intraoperative contouring and cutting of the plates as well as for postoperative emergent cutting. The plates accept screws with a diameter of 2.3mm and 2.7mm. The Subject Device System consists of self-drilling locking screws and self-tapping locking screws. The selfdrilling locking screws are designed to allow for screw fixation with no pre-drilling. The self-tapping locking screws require pre-drilling before insertion. The Subject Device plates and screws are provided non-sterile and are for single use only.

This document describes the Stryker SternalPlate System, a medical device for sternal fixation. It does not provide information directly relevant to the acceptance criteria and study details for an AI/ML-enabled device as requested in the prompt. The document focuses on demonstrating substantial equivalence to a predicate device for traditional medical device clearance, detailing materials, operational principles, and bench testing for physical performance, not AI/ML model performance.

Therefore, I cannot fulfill the request to describe the acceptance criteria and the study that proves the device meets those criteria for an AI/ML device based on the provided text. The document does not contain any information about a machine learning algorithm, its performance, or how its ground truth was established.

However, I can extract the information provided about the device's general performance testing:

VIII. CONCLUSIONS [§807.92(b)(3)]

The results of the non-clinical data demonstrate the Subject Device will perform as intended in the specified use conditions. According to the comparison based on the requirements of 21 CFR 807.92 and the information provided herein, it is concluded that the information included in this submission supports substantial equivalence.

General Performance Data Presented (Not AI/ML specific):

• Performance Bench Testing:
  • Cleaning Validation
  • Sterilization Validation
  • Biocompatibility
  • Product Design Validation
  • MR Compatibility
  • Screw Performance
  • Plate Performance

Study Findings (Non-AI/ML):

• "The Subject Device met all pre-defined acceptance criteria and standards and was found to not represent a new worst case. Overall, the results of the performance bench tests support the substantial equivalence of the Subject device."

Missing AI/ML Specific Information:

The document explicitly states:

• Animal Testing: "Animal testing was not required as a basis for substantial equivalence."
• Clinical Testing: "Clinical testing was not required as a basis for substantial equivalence."

This further confirms the absence of studies relevant to AI/ML model performance.

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