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This device is to be used to expand the tooth socket to facilitate tooth extraction, and/or to prepare the site for placement of endosseous dental implants or abutments.

The Powertome periotome is designed as an aid to dental professionals in the extraction of a tooth, or multiple teeth, from their socket. It is designed to minimize alveolar bone loss, thus providing an initial step in the preparation prior to placing dental implants, whose success rate is highly dependent on minimal (or no) bone loss. It functions by severing the periodontal ligaments that attach the cementum of the tooth to the alveolar bone, by use of different sized and shaped tips that provide the leverage and effect desired. These ligaments are one of two methods by which teeth stay in the jaw. The second function is to push the alveolar bone away from the tooth, thus disengaging the mechanical leverage the alveolar bone uses on the imequiarity of the tooth to also help hold the tooth in place. Once the ligaments are cut, and the alveolar bone pushed away, the tooth extracts trivially. Our method is the same as using a manual periotome and mallet, except that instead of an assistant tapping on the end of the periotome with a mallet, we use a small solenoid in the handpiece, which delivers a small but consistent force on the periotome tip, controlled in duration by the professional by use of a foot switch (for on/off control). The total delivered power for each stroke is controlled, and can be set by the professional.

This submission is about a medical device (Powertome Periotome) and not an AI/ML device, therefore, the information requested in the prompt regarding AI/ML device evaluation is not available in the provided text.

The Powertome Periotome is a dental tool designed to aid in tooth extraction by severing periodontal ligaments and minimizing alveolar bone loss, especially in preparation for dental implants. It uses a small solenoid to deliver controlled force to the periotome tip, simulating the action of a mallet but with greater control for the dental professional.

Here's an analysis of the provided text based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" in a quantitative sense as might be found for an AI/ML device. Instead, it compares the technological characteristics and functional success of the Powertome Periotome to predicate (manual) periotomes. The "acceptance criteria" can be inferred from the stated claims of improvement and equivalence.

Conclusion from the document: The Powertome Periotome is claimed to be "as safe and as effective as the predicate device in performing its indicated use," and offers "significantly increased control over the outcome."

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

• Sample Size for Test Set: Not applicable in the context of clinical trials or AI/ML model performance evaluation. The "test" in this context refers to engineering characterization of the device's physical properties compared to manual methods.
• Data Provenance: The force and frequency data for both the predicate device (mallet-assisted) and the Powertome periotome were generated through bench testing and characterization. For the predicate device, typical numbers were also "characterized ... by interviewing professionals." This suggests an internal, controlled environment for the Powertome and a combination of observation/interview for the manual method.

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

• Number of Experts: Not applicable for establishing ground truth in a clinical or diagnostic sense. The comparison here is based on physical characteristics (force, frequency, duration, etc.) and anecdotal feedback.
• Qualifications of Experts: For the anecdotal data, "Two dental professionals have been using prototype versions of the product." Their specific qualifications (e.g., years of experience) are not provided beyond being "dental professionals." For the "characterization of typical numbers by interviewing professionals" no exact number or qualification is provided.

4. Adjudication Method for the Test Set:

• Not applicable. This was not a study involving human interpretation of medical data requiring adjudication. The comparison was based on physical device performance measurements.

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:

• No, an MRMC comparative effectiveness study was not done. This is not an AI/ML device, and the submission explicitly states: "We have not used clinical data to support our claim of substantial equivalence." The comparison is based on the device's mechanical characteristics and anecdotal feedback.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

• No. This is a medical device, not an algorithm. The device is designed to be used with a human professional, providing them with enhanced control over the process.

7. The Type of Ground Truth Used:

• For the physical characteristics (force, frequency, duration), the ground truth was established through direct measurement and engineering characterization of the devices.
• For the effectiveness claims (cutting ligaments, expanding socket, repeatability, safety), the ground truth is based on comparison of mechanical properties and anecdotal feedback from dental professionals, rather than a formal, clinical ground truth (e.g., pathology, outcomes data).

8. The Sample Size for the Training Set:

• Not applicable. This is a hardware medical device, not an AI/ML model that requires a training set.

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

• Not applicable. As above, no training set was used.

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