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510(k) Data Aggregation
(85 days)
The Amplaid 460 is a two channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement and diagnosis of various types of hearing losses.
The Amplaid 460 is a two channel clinical diagnostic audiometer which can perform all audiometric tests normally performed in a clinical situation. It provides testing capability for basic evaluation, cochlear versus retrocochlear dysfunction, central dysfunction and non-organic hearing loss. Other diagnostic audiometric tests are: pure tone, Speech, High Frequency, Multifrequency, Bekesy, S.I.S.I., A.B.L.B. (Fowler), D.L.I. (Lüscher), M.L.B., Tone Decay, and M.L.D.(Masking Level Difference).
The provided text describes the 510(k) submission for the Amplaid 460 Research and Clinical Audiometer. However, it does not contain detailed information about specific acceptance criteria or the study that definitively proves the device meets those criteria. The document is a regulatory submission for substantial equivalence to a predicate device, rather than a detailed scientific study report.
Here's an analysis based on the provided text and what is typically found (or not found) in such 510(k) summaries:
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A table of acceptance criteria and the reported device performance:
The document states: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate devices." No specific acceptance criteria (e.g., accuracy, precision, sensitivity, specificity, or specific tolerances for audiometric measurements) are listed, nor are detailed performance metrics reported. The statement refers to a general equivalence to predicate devices, but without quantification. -
Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):
No information on sample size, data provenance, or study design (retrospective/prospective) is provided for the "bench and user testing." -
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 information is not available in the provided text. The document mentions the intended use by a "qualified/trained audiologist," but does not specify their role in testing or establishing ground truth for the device's performance. -
Adjudication method (e.g. 2+1, 3+1, none) for the test set:
No information about adjudication methods is provided. -
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 device is an audiometer, a diagnostic instrument that measures hearing thresholds. It is not an AI-assisted diagnostic tool that would typically involve human readers interpreting results in a MRMC study. Therefore, an MRMC study with AI assistance is not applicable here, and no such study is mentioned. -
If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The device is a standalone diagnostic instrument. Its performance would inherently be evaluated without a human-in-the-loop performance study in the context of interpretation, as it generates raw audiometric data. The "user testing" mentioned likely refers to user interaction and functionality, not diagnostic interpretation. -
The type of ground truth used (expert consensus, pathology, outcomes data, etc):
Not explicitly stated. For an audiometer, the "ground truth" would typically refer to the instrument's ability to accurately measure sound levels and hearing thresholds against a known standard, often calibrated using established methods. The "bench testing" would likely cover this. For "user testing," the ground truth might be the expected audiogram from a patient with a known hearing status, but this is speculative given the lack of detail. -
The sample size for the training set:
This device is not described as utilizing a machine learning algorithm that requires a "training set" in the conventional sense. It's a measurement instrument. -
How the ground truth for the training set was established:
As above, the concept of a "training set" and ground truth for it, as typically applied to machine learning, is not relevant to this type of device based on the provided information.
Summary of what is present:
- Predicate Device: Amplaid 309 Clinical Audiometer (K880059)
- Safety and Effectiveness Claim: "The results of bench and user testing indicates that the new device is as safe and effective as the predicate devices." This is a qualitative claim of equivalence, not a detailed report of adherence to specific, quantified acceptance criteria.
- Intended Use: Diagnosis of hearing losses by qualified audiologists on both adult and pediatric subjects.
In conclusion, the provided text from the 510(k) summary focuses on demonstrating substantial equivalence to a predicate device based on design, function, and general safety/effectiveness, rather than detailing a rigorous study with specific acceptance criteria and performance data in the manner typically expected for advanced diagnostic algorithms or AI-driven systems. For a device like an audiometer, "bench testing" would likely involve calibration against known sound pressure levels and electrical signals, and "user testing" would confirm usability and correct functionality in clinical scenarios, but the details are not provided here.
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