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510(k) Data Aggregation
(368 days)
AERONEB II, MODEL APN 200
The AeroNeb™ II Portable Nebulizer is intended for breath-triggered nebulization of aerosolized medications prescribed by a physician.
The AeroNeb™ II is a battery operated hand-held portable nebulizer using the same materials and piezoelectric vibration aerosol generator technology as the predicate device.
The provided text describes the AeroNeb™ II Portable Nebulizer and aspects of its 510(k) premarket notification. However, it does not contain the detailed information necessary to fully answer all the questions regarding acceptance criteria and the study that proves the device meets them.
Here's a breakdown of what can be extracted and what is missing:
1. A table of acceptance criteria and the reported device performance
The document states: "The performance evaluations including nebulizer delivery characterization, electrical, and EMC safety, were based on those suggested in the FDA CDRH - REVIEWER GUIDANCE FOR NEBULIZERS, METERED DOSE INHALERS, SPACERS AND ACTUATORS issued on: October 1, 1993." and "The successful tests demonstrated the device consistently performed within its design parameters, is as safe and effective, and performs as well as, or better than, the predicate device."
This indicates that specific performance evaluations were conducted, but the acceptance criteria values and the actual reported device performance values are not detailed in this summary. These would typically be found in the full submission, not a general 510(k) summary.
Acceptance Criteria Category | Acceptance Criteria (Value/Range) | Reported Device Performance (Value/Range) |
---|---|---|
Nebulizer Delivery Characterization | Not specified in document | Stated as "performed within its design parameters" |
Electrical Safety | Not specified in document | Stated as "successful tests" |
EMC Safety | Not specified in document | Stated as "successful tests" |
Overall Safety and Effectiveness | As safe and effective as predicate | Stated as "as safe and effective, and performs as well as, or better than, the predicate device" |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
This information is not provided in the given text.
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)
This device is a nebulizer, not a diagnostic imaging device. Therefore, the concept of "ground truth" derived from expert consensus, as typically applied in AI/ML performance studies, is not applicable here. The performance is assessed through objective engineering and safety tests (nebulizer delivery characterization, electrical, and EMC safety).
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
As mentioned above, the concept of "adjudication" for expert consensus is not applicable for this type of device testing.
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
This is a physical medical device (nebulizer), not an AI/ML diagnostic or assistive tool. Therefore, an MRMC comparative effectiveness study involving human readers and AI assistance is not applicable.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
This is a physical medical device (nebulizer), not an algorithm. Therefore, "standalone" algorithm performance is not applicable.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
For this device, the "ground truth" or standard of comparison is based on:
- FDA CDRH - REVIEWER GUIDANCE FOR NEBULIZERS, METERED DOSE INHALERS, SPACERS AND ACTUATORS issued on: October 1, 1993.
- Comparison to the predicate device (FPT Nebulizer K970010), demonstrating it is "as safe and effective, and performs as well as, or better than" the predicate.
8. The sample size for the training set
This is a physical medical device. The concept of a "training set" as understood in machine learning is not applicable. Device development involves design, prototyping, and testing, but not a "training set" in the computational sense.
9. How the ground truth for the training set was established
Again, the concept of "training set" and "ground truth for the training set" is not applicable to this type of device. Performance is validated against established physical and electrical standards, and comparison to a legally marketed predicate device.
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