(343 days)
The SIS Sinus Implant Stabilizer is intended to provide a fixed anchorage point to stabilize dental implants in the sinus region, enabling sinus augmentation and implantation to be carried out in one session.
The SIS Sinus Implant Stabilizer consists of a titanium plate provided with 3 large perforations for screw fixation of implants for premolars and first molars. It may be additionally secured in place with titanium microscrews and is provided in two sizes for use with different implant systems.
This appears to be a 510(k) premarket notification for a medical device called the "SIS Sinus Implant Stabilizer." This type of document is a submission to the FDA to demonstrate that the device is at least as safe and effective as a legally marketed predicate device.
Unfortunately, the provided text does not contain specific acceptance criteria, detailed study designs, or performance metrics in the way you've outlined for a clinical study proving a device meets acceptance criteria. Instead, it states:
"Performance Data: Testing was performed to support substantial equivalence to the predicate devices. The SIS Sinus Implant Stabilizer met all specified design and performance requirements."
This is a general statement indicating that the device passed internal testing to support its substantial equivalence claim, rather than a detailed report of a study designed to evaluate its performance against pre-defined acceptance criteria with specific metrics.
Therefore, I cannot fill in the table or answer most of your detailed questions based solely on the provided text. The 510(k) summary typically doesn't include the granular details of performance testing or clinical studies unless they are novel or significant. The focus here is on demonstrating equivalence to existing predicate devices.
Here's what I can extract and state based on the provided text, and where information is missing:
Acceptance Criteria and Device Performance (Based on provided text)
| Acceptance Criteria (e.g., Sensitivity, Specificity, Accuracy, Mechanical Strength) | Reported Device Performance (Value/Range, Confidence Interval) | Basis for Acceptance (e.g., clinical need, predicate device performance) |
|---|---|---|
| General Statement of Meeting Requirements | Met all specified design and performance requirements. | Substantial equivalence to predicate devices (which implies similar safety and effectiveness). |
| Specific mechanical/biocompatibility criteria | Not detailed in this summary | Not detailed in this summary |
Detailed Study Information (Based on provided text)
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A table of acceptance criteria and the reported device performance
- As noted above, the document only states that the device "met all specified design and performance requirements." It does not provide a table with specific quantitative acceptance criteria (e.g., specific tensile strength, fatigue life, or biocompatibility pass/fail criteria) nor detailed performance values.
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Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size: Not specified.
- Data Provenance: Not specified, but likely from Mondeal Medical Systems GmbH in Germany given their address.
- Retrospective/Prospective: Not specified.
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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. This device is a physical implant. Performance testing would likely involve bench testing (mechanical, material, biocompatibility) rather than expert-established ground truth on a 'test set' in the context of diagnostic AI.
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Adjudication method (e.g. 2+1, 3+1, none) for the test set
- Not Applicable. See point 3.
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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. This is a physical medical implant device, not an AI/diagnostic software.
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If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- No. This is a physical medical implant device, not an AI/diagnostic software.
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The type of ground truth used (expert consensus, pathology, outcomes data, etc)
- Not applicable in the typical sense for an AI/diagnostic device. Performance was assessed against design and performance requirements (e.g., mechanical properties, biocompatibility). The "ground truth" is that the device must meet these engineering and regulatory specifications.
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The sample size for the training set
- Not Applicable. This is a physical medical implant device; it does not involve a "training set" in the context of machine learning.
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How the ground truth for the training set was established
- Not Applicable. See point 8.
Conclusion based on provided text:
The provided 510(k) summary is for a physical medical implant (SIS Sinus Implant Stabilizer). The performance data section broadly states that "Testing was performed to support substantial equivalence to the predicate devices. The SIS Sinus Implant Stabilizer met all specified design and performance requirements." This indicates that the device underwent necessary engineering and possibly biological testing (e.g., biocompatibility) to demonstrate its safety and effectiveness, likely by meeting recognized standards and internal specifications similar to its predicate devices. However, the document does not elaborate on the specific acceptance criteria, quantitative results, or detailed study designs that would typically be found in a clinical study report for a diagnostic AI device.
§ 872.4760 Bone plate.
(a)
Identification. A bone plate is a metal device intended to stabilize fractured bone structures in the oral cavity. The bone segments are attached to the plate with screws to prevent movement of the segments.(b)
Classification. Class II.