Search Results

AirView is a web based solution for healthcare specialists intended to:

• assist in the diagnosis of sleep disordered breathing in adult patients through analysis of data recorded by an AirView compatible home sleep device.

• transfer and display machine and therapeutic information that has been transmitted remotely from the patient's therapy device. It is intended to support the standard follow-up care of patients that have been prescribed a compatible ResMed therapy device. AirView also provides remote settings capabilities for non-life support devices only.

AirView is a web application that can transfer, store, analyse, manage, and display machine and therapy data (from ResMed compatible therapy devices) and diagnostic data (from ResMed compatible sleep study devices). The data is transferred from the device either wirelessly through a communications module or with the aid of a data card/USB stick and internet technology to a central database and then displayed on the healthcare professional's computer through a web browser such as Internet Explorer.

The software application enables patient machine and therapy data to be shared across several different user groups for the primary purpose of monitoring patient compliance and home sleep studies. Clinical users and other healthcare specialists can access data with ResMed approved user accounts.

AirView can also be used by the healthcare specialist to remotely change the machine settings of compatible therapy devices. This assists in addressing any clinical issues in a timely manner and providing the necessary patient support. This is restricted to non-life support therapy devices only.

The provided document describes the AirView device, a web-based solution for healthcare specialists. It aims to assist in the diagnosis of sleep-disordered breathing and manage patient therapy data. The submission highlights that the modified AirView device underwent non-clinical testing to demonstrate substantial equivalence to its predicate devices (EasyCare Online (K132371) and ResScan (K140054)). No clinical testing was deemed necessary.

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based only on the provided text:

1. A table of acceptance criteria and the reported device performance

The document states that "All tests confirmed the product met the predetermined acceptance criteria". However, the specific quantitative acceptance criteria themselves are not explicitly listed in the provided text. The performance is reported in a descriptive manner, focusing on verification activities.

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

The document mentions "End-to-End testing," "Regression Testing," and "Side-by-Side testing," but it does not specify the sample size for any of these test sets, nor does it provide information about the data provenance (e.g., country of origin, retrospective or prospective nature of the data used in these tests).

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)

The document does not mention the use of experts to establish ground truth for the test set. The testing appears to be focused on technical validation (data transfer, functionality, output comparison) rather than clinical interpretation by human experts.

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

The document does not describe any adjudication method as it does not involve expert consensus or human interpretation for the ground truth.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not done or described in the provided text. The AirView device's primary function is data management, transfer, and display, and to "assist in the diagnosis of sleep disordered breathing in adult patients through analysis of data recorded by an AirView compatible home sleep device," not necessarily to directly improve human reader performance in interpreting images or complex diagnostic output requiring "readers." The "analysis" of data for diagnosis is performed by the system itself based on recorded sleep data.

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

The testing conducted ("End-to-End testing," "Regression Testing," "Side-by-Side testing") assessed the standalone performance of the algorithm/software in terms of data transfer, functionality, and output comparability. The device "assists in the diagnosis" through this analysis, implying it has a standalone analytical component without a human "in the loop" for that specific analytical function.

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

Given the nature of the testing (data transfer, functional verification, output comparison), the "ground truth" implicitly refers to:

• Correct data transmission: Ensuring the data sent matches the data received.
• Expected software behavior: Verifying that existing functionalities remain unchanged and new functionalities operate as designed.
• Concordance with predicate device output: Comparing the output of the modified AirView with a known, cleared predicate device (ResScan) to ensure they produce comparable results.

There is no mention of expert consensus, pathology, or outcomes data being used for ground truth in these non-clinical tests.

8. The sample size for the training set

The document does not mention a training set or any machine learning model training. The described activities are verification testing, not model development or validation.

9. How the ground truth for the training set was established

As no training set is mentioned, this information is not applicable or provided.

Ask a specific question about this device