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The Rightest Blood Glucose Monitoring System is intended for in vitro diagnostic use (outside of body). It is indicated to be used by professional healthcare personnel or people with diabetes at home to measure the glucose concentration for aiding diabetes management. The glucose concentration is measured with quantitative capillary whole blood from fingertip, palm and forearm by using Rightest Blood Glucose Monitoring System. This test device is not intended for testing neonate blood samples.

Special condition for use statement(s): Rightest system provides plasma equivalent results.

Our Blood Glucose Monitoring System consists of a Meter, Blood Glucose Test Strips, Code Key, Check key, Two Control Solutions, Lancing Device and lancets.

The Rightest Meter, Blood Glucose Test Strips, Code Key and Check key are manufactured by BIONIME Corporation. The Rightest Meter, when used with the Rightest Test Strips Blood Glucose Test Strips, quantitatively measures glucose in fresh capillary whole blood. The performance of the Rightest Blood Glucose Test Strips is verified by the Control Solution. The Check key verifies the status of Rightest meter.

Here's a breakdown of the acceptance criteria and study information for the Rightest Blood Glucose Monitoring System, Model GM310, based on the provided 510(k) summary:

1. Table of Acceptance Criteria and Reported Device Performance

The provided document doesn't explicitly state quantitative "acceptance criteria" in a separate section. Instead, the "Discussion of Non-Clinical Tests Performed" implicitly defines performance expectations through the tests conducted (precision, linearity, interference, hematocrit, control solution). The clinical study then demonstrates the device's accuracy against a laboratory reference.

Given the context of a blood glucose monitoring system, the primary acceptance criteria revolve around the agreement with a reference method, particularly in various sample locations. The "performance" is demonstrated by the linear regression results against the Olympus AU640.

Therefore, I will construct an acceptance criteria table based on the findings used to demonstrate substantial equivalence, focusing on the agreement with the reference method. The implied acceptance criterion is that the device should show "similarly slope and intercept" and a high correlation (r-value) compared to the reference method for all tested sites, demonstrating accuracy suitable for its intended use.

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

• Sample Size for Test Set: 120 measurements for each site (fingerstick, palmstick, armstick), totaling 360 measurements.
• Data Provenance: The document does not explicitly state the country of origin for the clinical study data or whether it was retrospective or prospective. Given that the submitter's identification is BIONIME CORPORATION, TAICHUNG COUNTY, TAIWAN, it's possible the study was conducted within Taiwan, but this is not confirmed. The study appears to be a prospective clinical evaluation as it's designed to compare the device's performance against a reference.

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

The ground truth was established by a laboratory reference method, the Olympus AU640, which is an automated clinical chemistry analyzer. This machine provides the reference glucose values against which the Rightest system's readings were compared. Therefore, the ground truth was based on a highly accurate and calibrated laboratory instrument rather than individual human expert consensus. The involvement of "experts" would be related to operating and maintaining the Olympus AU640, typically qualified clinical laboratory technologists or specialists.

4. Adjudication Method for the Test Set

Not applicable. The ground truth was established by the Olympus AU640 laboratory analyzer. There was no mention of human adjudication for the primary glucose values.

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

Not applicable. This is a blood glucose monitoring system, not an imaging device typically evaluated with MRMC studies or AI assistance for human readers. It measures glucose directly.

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

Yes, a standalone performance study was done. The reported performance metrics (slope, intercept, r-value) are directly comparing the device's output (Rightest Blood Glucose Monitoring System) against the laboratory reference (Olympus AU640), without any human interpretation or intervention in the measurement process itself. The "Test capillary blood by patient Study" refers to patients using the device to take samples, but the measurement output itself is the device's standalone performance.

7. The Type of Ground Truth Used

The ground truth used was laboratory reference data obtained from an Olympus AU640 analyzer. This is a highly accurate and standardized method for measuring blood glucose.

8. The Sample Size for the Training Set

The document does not provide any information regarding a "training set" or "validation set" in the context of machine learning or algorithm development. This type of submission (510(k) for a glucose meter) typically focuses on the performance of the final device and its inherent technology, rather than iterative algorithm training. The "non-clinical tests" (precision, linearity, interference, etc.) could be seen as part of the internal development and verification, but not explicitly a "training set" in the AI sense.

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

Not applicable, as no training set (in the context of machine learning) is described or implied by the document. The device's underlying technology relies on electrochemical detection (amperometry) with glucose oxidase, and its performance is validated against laboratory-grade reference methods.

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