Search Results

The Amplaid A724 and A728 are Programmable Admittance Meters which can:

1. Evaluate middle ear functions such as otitis media, glue ear, eardrum scar tissues, perform myringotomy status, ossicular chain discontinuity ear canal volume, otosclerosis, stapes fixation.
2. Perform Acoustic reflex test.
3. Determine acoustic reflex threshold
4. Perform reflex decay test.

They is intended for use by a qualified/trained audiologist on both adult and pediatric subjects for measurement of acoustic impedance.

The Amplaid A724 and A728 ADMITTANCE METERS perform plane and compensated tympanometry; Programmed and manual stimuli for ipsilateral and contralateral acoustic reflex; Automatic reflex threshold; and Decay measurements.

The given text describes the Amplaid A724 and A728 Clinical Automatic Programmable Admittance Meters, which are intended to evaluate middle ear functions and perform acoustic reflex tests. The submission claims substantial equivalence to the predicate device, Amplaid 770 Admittance Meter (K903066).

Here's the breakdown of the acceptance criteria and study information:

Acceptance Criteria and Reported Device Performance

The core of the "acceptance criteria" presented in this 510(k) summary is based on demonstrating substantial equivalence to a predicate device, the Amplaid 770 (K903066). The acceptance criteria are implicitly that the new device performs "as safe and effective as the predicate device" and has no new indications for use.

Study Information:

The provided document is a 510(k) Summary, which typically focuses on demonstrating substantial equivalence rather than presenting extensive clinical study data as would be found in a PMA.

1. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

   • The document states "results of bench and user testing." It does not provide specific details on the sample size of subjects or cases used for "user testing" or the data provenance (country of origin, retrospective/prospective).
   • Bench testing would involve testing the device's adherence to technical specifications and standards, not human subjects.

2. 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):

   • The document implies "user testing" was performed, but it does not specify the number or qualifications of "users" (audiologists) involved, nor how ground truth might have been established if clinical performance was assessed this way. Given the nature of a 510(k) for an impedance meter, the primary "ground truth" would be the accurate measurement of audiological parameters, likely validated against established calibration standards and potentially against a predicate device.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

   • Not applicable/Not mentioned. The document does not describe adjudication for a test set in the context of diagnostic interpretation. The evaluation is likely focused on the device's ability to accurately perform its specified measurements.

4. 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 comparative effectiveness study was done. This type of study is not relevant for an auditory impedance meter, which is a measurement device, not an AI-assisted diagnostic interpretation tool.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • The device described is an "Amplaid A724 and A728 Clinical Automatic Programmable Admittance Meters." It is a measurement device operated by a "qualified/trained audiologist." Therefore, it inherently involves a human-in-the-loop for operation and interpretation. The performance evaluation would be of the device itself and its interaction with the user, not a standalone AI algorithm.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • For this device, the "ground truth" for demonstrating safety and effectiveness would primarily be:
     • Adherence to recognized industry standards: ANSI, ISO, IEC, EN standards for audiometric and electrical safety.
     • Comparison to the predicate device: The new device must perform "as safe and effective as the predicate device," implying performance metrics that align with or are better than the predicate's established performance. This suggests comparative testing against the predicate to ensure equivalent measurement accuracy and functionality.
     • Bench testing: Verifying technical specifications of the device itself.

7. The sample size for the training set:

   • Not applicable/Not mentioned. This device is not an AI/ML product that undergoes a "training phase." Its functionality is based on established audiological measurement principles and hardware/software design.

8. How the ground truth for the training set was established:

   • Not applicable. As noted above, there is no "training set" in the context of an AI/ML algorithm.

Ask a specific question about this device