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The EASYMAX® Tag Self-Monitoring Blood Glucose System is comprised of the EASYMAX® Tag meter and the EASYMAX® Tag test strips. The kit is intended for the quantitative measurement of glucose in fresh capillary whole blood samples drawn from the fingertip, palm, or forearm. Testing is done outside the body (In Vitro diagnostic use). It is indicated for use at home (over the counter [OTC]) by a single patient with diabetes and should not be shared, as an aid to monitor the effectiveness of diabetes control. The system is not to be used on neonates, nor for the diagnosis of, or screening for diabetes mellitus. Alternative site testing can be only used during steady-state blood glucose conditions.

The modified device of EASYMAX® Tag (EM Tag) self-monitoring blood glucose system is derived from the existing device of EasyMax MU glucose meter and the modified device contain the NFC (Near-field communication) function to transfer glucose results to the mobile app. The self-monitoring blood glucose system consists of a blood glucose meter and test strips which are designed, tested, and verified to work together as a system to produce accurate blood glucose test results. The electrochemical principle on the test strip is the reaction of FAD glucose dehydrogenase (FAD-GDH) with blood glucose and a small electrical current generated proportional to the glucose concentration in the blood sample. The meter measures the current and displays the blood glucose result.

The provided text describes a 510(k) premarket notification for the EASYMAX® Tag Self-Monitoring Blood Glucose System, which is an updated version of a previously cleared device. While the document broadly discusses verification and validation activities and risk analysis, it does not provide the specific details required to answer all parts of your request.

Here's what can be extracted and what information is missing:

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

The document states: "The similar V&V testing with similar acceptance criteria as the predicate was performed and the design outputs met pre-determined design inputs was confirmed in the software validation report in this submission."

However, the specific acceptance criteria (e.g., accuracy percentages within certain glucose ranges) and the reported device performance against those criteria are not provided in this summary. These details would typically be found in the actual validation reports (Software Validation Report, Risk Management Report, etc.) which are referenced but not included here.

2. Sample sized 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.

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. Since this is a blood glucose monitoring system, the ground truth would likely be established using a laboratory reference method, not expert consensus in the way it would be for imaging.

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

An MRMC study is relevant for devices where human interpretation of medical images or data is involved and the AI assists that interpretation. This device is a self-monitoring blood glucose system which directly provides a numerical measurement to the user. Therefore, an MRMC comparative effectiveness study in the context of human readers improving with AI assistance would not be applicable to this type of device.

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

This device is a standalone system in the sense that it provides a direct measurement. The "algorithm only" aspect would refer to the internal functioning of the meter in conjunction with the test strip. The document indicates that "the design outputs met pre-determined design inputs was confirmed in the software validation report," implying that the standalone performance of the device's measurement function was evaluated. However, specific performance metrics are not provided in this summary.

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

For a blood glucose monitoring system, the ground truth would typically be established by a laboratory reference method for glucose measurement (e.g., using a YSI glucose analyzer). While the document does not explicitly state this, it is standard practice for such devices.

8. The sample size for the training set

This information is not provided in the given text.

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

This information is not provided in the given text. For a blood glucose meter, the ground truth for any training (or calibration) would typically be established using a laboratory reference method.

In summary, the provided document is a 510(k) summary, which focuses on demonstrating substantial equivalence to a predicate device. It briefly mentions that verification and validation activities were performed according to risk analysis and that design outputs met design inputs. However, it does not include the detailed performance data, sample sizes, ground truth establishment specifics, or expert qualifications that would be found in the full validation reports.

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