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The MAJOR III Blood Glucose Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood. Testing is done outside the body ( in vitro diagnostic use). It is indicated for use at home ( over the counter [OTC] ) by person with diabetes, or in clinical setting by health care professionals, as an aid to monitor the effectiveness of diabetes control.

Based on an electrochemical biosensor technology and the principle of capillary action, MAJOR III Blood Glucose Monitoring System only needs a small amount of blood. Capillary action at the end of the test strip draws the blood into the action chamber and your blood glucose result is precisely and displayed in 8 seconds.

The provided text does not contain detailed acceptance criteria or a study that explicitly demonstrates the device meets such criteria. It primarily focuses on the device's substantial equivalence to a predicate device and its intended use. However, based on the information provided, here's an attempt to answer your questions, highlighting where information is not available:

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

The document does not explicitly state acceptance criteria in terms of performance metrics (e.g., accuracy percentages, sensitivity, specificity) for the MAJOR III Blood Glucose Monitoring System. Instead, the "Synopsis of Test Methods and Results" section broadly states:

"Pre-clinical and clinical data are employed upon submission of this 510(K) premarket notification according to the Guidance Document for In Vitro Diagnostic Test System; Guidance for Industry and FDA document provided by CDRH/FDA."

This indicates that some form of testing was done, but the specific performance results or acceptance thresholds are not detailed in this summary. The substantial equivalence claim is based on the device having the "same working principle and technologies" as the predicate device. Therefore, the "acceptance criteria" here implicitly revolve around demonstrating that the new device performs comparably to the predicate.

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

This information is not provided in the given text. There is no mention of specific sample sizes for any test sets, data provenance, or whether the studies were retrospective or prospective.

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)

This information is not provided in the given text.

4. Adjudication method (e.g. 2+1, 3+1, none) 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, If so, what was the effect size of how much human readers improve with AI vs without AI assistance

This information is not applicable and not provided. This document pertains to a blood glucose monitoring system, which is an in vitro diagnostic device, not an imaging device that would typically involve human "readers" or AI assistance in the way described for MRMC studies.

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

This information is not explicitly stated in the provided text. However, blood glucose monitoring systems like the MAJOR III are inherently "standalone" in that they provide a direct measurement result without human interpretation of complex outputs in the way an AI algorithm for image analysis might require. The device itself is the "algorithm" giving the quantitative measurement.

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

The document mentions "fresh capillary whole blood" for glucose measurement. For a blood glucose monitoring system, the "ground truth" would typically be established by a reference method for glucose measurement (e.g., a laboratory-grade analyzer using enzymatic methods) against which the device's readings are compared. This information is not explicitly detailed but is implied by the nature of the device (quantitative measurement of glucose).

8. The sample size for the training set

This information is not provided in the given text. The term "training set" is also typically associated with machine learning models, which is not clearly the primary focus for this type of electrochemical biosensor.

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

This information is not provided in the given text, and also not directly applicable in the context of what is presented.

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