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The Prodigy® Diabetes Management Software is indicated for use as a data management tool for the acceptance, transfer, display, storage, processing (e.g., averaging). Reporting, and printing of patient blood glucose monitoring data.
The Prodigy® Diabetes Management Software is indicated for use with the Prodigy Blood Glucose Monitoring Systems only.

The Prodigy® Diabetes Management Software is a moderate level of concern software management system that allows the user an additional method of tracking their blood glucose level. The software allows for an accident member of their blood Glucose Monitor via a USB cable. The Prodigy® Diabetes Management Software is designed to operate on the patient's PC with Microsoft SQL Server 2005 or later operating system. Prodigy® Diabetes Care LLC website will provide a link to download the Microsoft SQL Server 2005 Server 2005.

Here's a breakdown of the acceptance criteria and study information for the Prodigy® Diabetes Management Software, based on the provided text:

1. Acceptance Criteria and Reported Device Performance

The provided document, primarily a 510(k) summary, focuses on demonstrating substantial equivalence to a predicate device rather than explicitly stating quantitative or qualitative "acceptance criteria" and then directly reporting performance against them in the traditional sense of a clinical trial. Instead, the "acceptance criteria" are implied by the features and functionalities deemed necessary to be equivalent to the predicate device. The "reported device performance" is largely qualitative, indicating that these functionalities are present and work.

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

The document mentions a "clinical usability study" or "Human Factor Study" but does not specify the sample size used for the test set.

The data provenance is not specified (e.g., country of origin). It can be inferred that the study was prospective, as it was conducted "to verify ease of use and label comprehension" for the device being submitted.

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

The document does not specify the number of experts or their qualifications, nor does it explicitly mention "ground truth" in the context of expert review for the usability study. The usability study would typically involve end-users, not necessarily experts for ground truth establishment.

4. Adjudication Method for the Test Set

The document does not provide any information regarding an adjudication method for the test set.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The performance data section only mentions a "clinical usability study" or "Human Factor Study" to verify ease of use and label comprehension. This type of study is not an MRMC comparative effectiveness study, and there is no mention of comparing human readers with and without AI assistance, nor any effect size.

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

The device is described as "software management system" and "data management tool" for blood glucose monitoring data. Its primary function is displaying, storing, processing, reporting, and printing data from a blood glucose meter. It is not an AI algorithm performing diagnostic tasks in a standalone manner where performance metrics like sensitivity/specificity for a diagnosis would be relevant. The "performance data" refers to a usability study, not a standalone algorithmic performance test. Therefore, a standalone algorithmic performance study in the typical sense for an AI diagnostic device was not conducted or is not applicable to this type of device.

7. The Type of Ground Truth Used

For the "clinical usability study," the "ground truth" would implicitly be the successful and intuitive completion of tasks by the study participants and their feedback on ease of use and comprehension, as measured against predefined usability criteria. It's not a "ground truth" derived from expert consensus, pathology, or outcomes data, as those are typically associated with diagnostic or image analysis devices.

8. The Sample Size for the Training Set

The document does not mention a training set sample size. This is because the device is a data management software, 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

Since there is no mention of a training set for an AI/ML model, there is no information on how ground truth for a training set was established.

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