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The WaveSense Diabetes Manager (WDM) application (app) is intended for use in the home and professional settings to aid individuals with diabetes and their healthcare professionals; in the review, analysis and evaluation of blood glucose readings to support an effective diabetes management program. The WaveSense Diabetes Manager application is a digital logbook and diabetes management tool designed to operate using the iPhone Operating System platform. The application can be used alone or with the WaveSense Direct Connect Cable and a WaveSense-enabled blood glucose meter (BGM) with a mini-USB port.

The WaveSense Diabetes Manager (WDM) application (app) is a digital logbook and diabetes management tool for the iPhone operating system platform. The application can be used alone or with the WaveSense Direct Connect Cable and a WaveSense-enabled Blood Glucose Meter (BGM) with a mini-USB port.

Here's an analysis of the provided text regarding the acceptance criteria and study for the AgaMatrix WaveSense Diabetes Manager application:

1. Table of Acceptance Criteria and Reported Device Performance

The provided text focuses on demonstrating substantial equivalence to a predicate device rather than explicitly defining and meeting specific analytical or clinical performance acceptance criteria for the WaveSense Diabetes Manager application itself. The study's focus was on the ease of use and functional equivalence as a data management tool.

2. Sample Size Used for the Test Set and Data Provenance

• Sample Size: Not explicitly stated. The text mentions "Clinical setting by persons with diabetes," but does not provide a number for the participants in this evaluation.
• Data Provenance: The study was conducted "in house and in a Clinical setting." The country of origin is not specified but is presumed to be the USA, given the submission to the FDA. The study appears to be prospective in nature, as it involved actively evaluating the device.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

This information is not provided in the document. The study primarily focused on user experience and functional equivalence rather than a diagnostic performance evaluation requiring expert ground truth establishment.

4. Adjudication Method for the Test Set

This information is not provided. Given the nature of the study (ease of use and functional equivalence), a formal adjudication method for diagnostic accuracy would likely not be relevant or necessary.

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

No, an MRMC comparative effectiveness study was not done. The WaveSense Diabetes Manager application is a data management tool, not an AI-powered diagnostic device, and therefore this type of study is not applicable.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device is a standalone application in the sense that it collects and displays data. However, it's not an "algorithm-only" device for diagnostic or predictive purposes without human interaction. Its function is to facilitate human review and analysis of blood glucose data. The performance assessment was based on its operational ease and functional equivalence.

7. The Type of Ground Truth Used

The concept of "ground truth" as it applies to diagnostic accuracy (e.g., pathology, expert consensus) is not applicable to this device. The "ground truth" for this application would be the accurate transfer and display of blood glucose readings, which are generated by an external BGM, and the user's ability to easily navigate and utilize the app's features. The study implicitly evaluated the functional correctness and user experience as its "ground truth."

8. The Sample Size for the Training Set

This information is not applicable/not provided. The WaveSense Diabetes Manager is an application for data management, not a machine learning or AI model that requires a "training set" in the conventional sense.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable. As stated above, this device does not utilize a "training set" in the context of an AI/ML model.

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