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The AutoSure Voice 3 Plus Blood Glucose Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood samples drawn from the fingertips, forearm, or palm. The meter includes voice functionality to assist visually impaired users. It is indicated for lay use by people with diabetes as an aid to monitoring levels in Diabetes Mellitus and should only be used by a single patient and it should not be shared. It is not indicated for the diagnosis or screening of diabetes or for neonatal use.

The AutoSure Plus Blood Glucose Test Strips are to be used with the AutoSure Voice 3 Plus Blood Glucose Meter to quantitatively measure glucose in capillary whole blood taken from fingertips, palm, or forearm. They are not indicated for the diagnosis or screening of diabetes or for neonatal use.

The AutoSure Voice 3 Plus blood glucose meter and AutoSure Plus test strips are used for testing of blood glucose by self-testers at home. Contrex Plus III Glucose Control Solutions are used for quality control testing of the system.

The provided text is a 510(k) Summary for the AutoSure Voice 3 Plus Blood Glucose Monitoring System. It details the device, its intended use, and a comparison to a predicate device. However, it does not contain specific acceptance criteria, detailed clinical study results with performance metrics, sample sizes for test sets, data provenance, expert qualifications, adjudication methods, or information about MRMC studies, standalone performance, training sets, or how ground truth was established.

The document primarily focuses on demonstrating substantial equivalence to a predicate device (AutoSure Voice II Plus Blood Glucose Monitoring System) based on changes in button relocation and the use of the same test algorithm and test strips.

Here's an analysis based only on the provided text, highlighting what is present and what is missing:

1. Table of Acceptance Criteria and Reported Device Performance:

The document explicitly states that the AutoSure Voice 3 Plus system uses the same test algorithm and test strips as the predicate meter (AutoSure Voice II Plus Blood Glucose Monitoring System). This implies that the performance expectations align with those of the predicate device. However, the specific acceptance criteria and numerical performance metrics for either the predicate or the new device are not provided in this summary.

The document mentions:

• "EMC & Electrical Safety and linearity testing. Results demonstrate substantial equivalence to the predicate system."
• "A user survey shows substantial equivalence in ease-of-use after the relocation of the operation buttons."
• "Testing demonstrated that the AutoSure Voice 3 Plus system performs in a substantially equivalent manner to that of the predicate."

Therefore, a table cannot be constructed with specific metrics based on the provided text. The general "acceptance criterion" appears to be "substantial equivalence" to the predicate device.

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

• Test Set Sample Size: Not specified. The document mentions a "user survey" for ease-of-use but does not provide details on the number of participants.
• Data Provenance (Country of Origin, Retrospective/Prospective): Not specified. The submitter is from China (Taiwan), but the location of the clinical testing (user survey) is not mentioned. The nature of the user survey (retrospective or prospective) is also not specified.

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

• Not Applicable / Not Specified. For a blood glucose monitoring system, the "ground truth" for glucose levels is typically established by a laboratory reference method, not by human experts interpreting data or images. The document does not describe any expert involvement in establishing ground truth for glucose measurements or for the user survey.

4. Adjudication Method for the Test Set:

• Not Applicable / Not Specified. As there's no mention of expert ground truth establishment, there's no adjudication method described.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size:

• No. An MRMC study is typically performed for diagnostic imaging devices where multiple readers interpret cases. This device is a blood glucose monitoring system, which does not involve human readers interpreting images.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done:

• Yes, implicitly. The device itself is designed to provide a quantitative measurement of glucose. The "test algorithm" is key to this standalone performance. The document states that the new device uses the "same test algorithm" as the predicate. The "EMC & Electrical Safety and linearity testing" would also fall under standalone performance testing. However, specific performance results (e.g., accuracy, precision) of this standalone algorithm are not provided in this summary.

7. The Type of Ground Truth Used:

• Not explicitly stated in detail, but for a blood glucose monitoring system, the ground truth for glucose measurements would typically be established by a laboratory reference method (e.g., a YSI analyzer or similar highly accurate laboratory instrument). The summary does not provide details on the reference method used or how it was applied during any performance studies. For the "user survey," the ground truth was "user satisfaction/ease-of-use."

8. The Sample Size for the Training Set:

• Not Applicable / Not Specified. For a traditional blood glucose meter, there isn't typically a "training set" in the sense of machine learning. The algorithm is based on electrochemical principles and calibration.

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

• Not Applicable. As there's no distinct training set mentioned in the machine learning context, this question isn't relevant to the information provided.

In summary, the provided 510(k) Summary focuses on demonstrating substantial equivalence primarily through design changes (button relocation) and the continuity of the core technology (same algorithm and test strips). It lacks granular detail on performance criteria, clinical study methodology, and specific results often found in submissions for devices with more complex diagnostic algorithms or imaging components.

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