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The AP-3000 Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and from the alternative sites (palm, forearm, upper arm, calf, and thigh) for self testing by persons with diabetes at home. The AP-3000 Blood Glucose Monitoring Systems is intended for testing outside the body (in vitro diagnostic use). It is intended for use by lay users and should only be used by a single patient as an aid to monitor the effectiveness of diabetes control. It is intended to be used by a single person and should not be shared. It is not intended for the diagnosis of or screening for diabetes mellitus, and is not intended for use on neonates.

The AP-3000multi Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and from the alternative sites (palm, forearm, calf, and thigh) for self testing by persons with diabetes. The AP-3000multi Blood Glucose Monitoring Systems is intended for testing outside the body (in vitro diagnostic use). It is intended for multi-patient use in a professional healthcare setting, as an aid to monitor the effectiveness of diabetes control. This system is only used with single-use, auto-disabling lancing devices. It is not intended for the diagnosis of or diabetes mellitus, and is not intended for use on neonates.

The AP-3000 Blood Glucose Monitoring System consists of three main products: the meter, test strip, and control solutions. These products have been designed, tested, and proven to work together as a system accurate blood glucose test results. Use only AP-3000 test strips and MAJOR control solution with the AP-3000 Blood Glucose Monitoring System.

The AP-3000multi Blood Glucose Monitoring System consists of three main products: the meter, test strip, and control solutions. These products have been designed, tested, and proven to work together as a system accurate blood glucose test results. Use only AP-3000multi test strips and MAJOR control solution with the AP-3000multi Blood Glucose Monitoring System.

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

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state numerical acceptance criteria for accuracy or performance metrics. Instead, it makes a general statement about meeting intended use. The table below outlines the performance characteristics mentioned, but without specific numerical targets, it's impossible to directly compare to 'acceptance criteria' in the traditional sense of a specific threshold.

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

The document does not explicitly state the numerical sample size used for the test set. It mentions that "The performance of AP-3000/AP-3000multi Blood Glucose Monitoring System was studied in the laboratory and in clinical settings by healthcare professionals and lay users."

The data provenance is not explicitly stated in terms of country of origin, but the submitter's identification is Bestgen Biotech Corporation in Taipei, Taiwan. The studies were conducted in "clinical settings by healthcare professionals and lay users," suggesting prospective data collection.

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

This information is not provided in the given text. For glucose monitoring systems, ground truth is typically established using a laboratory reference method, not expert consensus in the way it might be for image analysis.

4. Adjudication Method (for the test set)

This information is not provided in the given text.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done in the context of human readers improving with AI vs. without AI assistance. This device is a blood glucose monitoring system, and the evaluation focuses on its accuracy against a reference method, not on human interpretation of images or other data with and without AI assistance.

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

The performance study described is inherently a "standalone" evaluation of the device itself (meter and strips) as it measures glucose levels, rather than an AI algorithm integrated with human interpretation. The study "demonstrated that the performance of this system meets its intended use," implying evaluation of the device's accuracy without human intervention influencing the reading of glucose levels.

7. The Type of Ground Truth Used

The type of ground truth used is not explicitly stated as "expert consensus," "pathology," or "outcomes data." However, for blood glucose monitoring systems, the ground truth is typically established using a laboratory reference method (e.g., a YSI analyzer), to which the device's readings are compared for accuracy. The text states "The performance... was studied in the laboratory," which supports this inference.

8. The Sample Size for the Training Set

This information is not applicable and therefore not provided. Blood glucose monitoring systems like the AP-3000/AP-3000multi traditionally rely on electrochemical biosensor technology and are not typically "trained" in the machine learning sense with a data set. Their performance is validated through rigorous testing against reference methods.

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

This information is not applicable as there is no "training set" in the context of a machine learning algorithm for this type of device.

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