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510(k) Data Aggregation
(245 days)
PIEZOSURGERY 3; OSSTEM PIEZO
The OSSTEMPiezo is intended for use in the following dental applications:
- Bone cutting for use in oral surgery
- Removing supra and subgingival calculus deposits and stains from teeth
- Periodontal pocket lavage with simultaneous ultrasonic tip movement
- Scaling and root planing
- Retrograde preparation of root canals
The Piezosurgery 3 is intended for use in the following dental applications:
- Bone cutting for use in oral surgery
- Removing supra and subgingival calculus deposits and stains from teeth
- Periodontal pocket lavage with simultaneous ultrasonic tip movement
- Scaling and root planing
- Retrograde preparation of root canals
The OSSTEMPiezo uses piezoelectric ultrasonic technology to generate mechanical microvibrations for bone cutting and ultrasonic scaling, with minimal trauma to soft tissue. The device is supplied with rer smoothing and blunt insert tips for use in oral surgery, including implantology, periodontal surgery, endodontic surgery and surgical orthodontics.
The device uses piezoeledric ultrasonic technology to generate mechanical microvibrations of insert tips for cutting mineralized structures with minimal trauma to soft tissue and for ultrasonic scaling.
The provided text does not contain specific acceptance criteria or a detailed study proving that the OSSTEMPiezo device meets such criteria. Instead, it focuses on demonstrating substantial equivalence to a predicate device based on performance evaluations.
Here's a breakdown of the information that is available and what is missing, structured according to your request:
- A table of acceptance criteria and the reported device performance
- No explicit acceptance criteria (e.g., "The device must achieve a cutting depth of X mm with Y pressure") are provided in the document.
- The "performance evaluations" section describes qualitative outcomes rather than measurable performance statistics against defined criteria.
Acceptance Criteria | Reported Device Performance |
---|---|
Not specified in the document | - Precisely delineated incisions |
- Limited pressure on the handpiece required for desired cutting action | |
- Improved surgical control | |
- Reduced possibility of trauma to soft tissue | |
- Preserving osteotomized surfaces | |
- Reduction of risk of adjacent tissue damage | |
- Reduction of tissue heating | |
- Improved post-operative healing |
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Sample size used for the test set and the data provenance
- The document does not provide details on a specific "test set" sample size or its provenance (e.g., country of origin, retrospective/prospective). The performance evaluations are described in general terms, implying a summary of observations rather than a detailed study protocol.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- No information is provided regarding the number of experts, their qualifications, or their role in establishing "ground truth" for any test set. The 'evaluations' appear to be based on general observation of device functionality.
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Adjudication method (e.g., 2+1, 3+1, none) for the test set
- No adjudication method is mentioned, as there is no described formal test set requiring such a process.
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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 MRMC study was conducted or mentioned. This device is a surgical instrument, not an AI-assisted diagnostic tool for "human readers."
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done
- The device is a human-operated surgical instrument, so the concept of an "algorithm only" or "standalone" performance without human-in-the-loop is not applicable in this context.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
- No formal "ground truth" in the sense of a definitive reference standard (like pathology or clinical outcomes) is described for the performance evaluations. The evaluations appear to be based on observations of physical effects (e.g., incision quality, tissue preservation).
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The sample size for the training set
- The document does not describe a "training set" as this is not a machine learning or AI-based device.
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How the ground truth for the training set was established
- Not applicable, as there is no training set for this device.
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