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The FORA ADVANCED GD40 Glucose, ß-Ketone and Cholesterol Monitoring System consists of the FORA ADVANCED GD40 meter, the FORA ADVANCED GD40 Blood Glucose strips, the FORA ADVANCED GD40 B-Ketone strips, and the FORA ADVANCED GD40 Total Cholesterol strips.

The FORA ADVANCED GD40 Glucose, B-Ketone and Cholesterol Monitoring System is intended for the quantitative measurement of glucose, beta-hydroxybutyrate (8-ketone), and cholesterol in fresh capillary whole blood from the finger. This system is intended for single-patient home use and should not be intended for use by patients with diabetes. It is only for use outside the body (in vitro diagnostic use).

Glucose and {}-ketone measurements are used as an aid to monitor the effectiveness of a diabetes control program. Glucose measurements should not be used for the diagnosis of or screening for diabetes.

Cholesterol measurements are used in the diagnosis and treatment of disorders involving excess cholesterol in the blood and lipid and lipoprotein metabolism disorders. Cholesterol should be measured at the frequency recommended by your healthcare provider.

FORA ADVANCED GD40 Glucose, ß-Ketone and Cholesterol Monitoring System includes the FORA ADVANCED GD40 Meter, analyte-specific test strips (FORA ADVANCED GD40 Blood Glucose Test Strips, FORA ADVANCED GD40 Blood Cholesterol Test Strips, and FORA ADVANCED GD40 Blood Ketone Test Strips) and control solutions (FORA Glucose Control Solutions, B-Ketone Control Solutions and Total Cholesterol Control Solutions).

The glucose/9-ketone test strips and control solutions utilized in the FORA ADVANCED GD40 Glucose, B-Ketone and Cholesterol Monitoring System are the same as the predicate, FORA ADVANCED GD40 Blood Glucose and ß-Ketone Monitoring System (K161738).

The provided text describes the FORA ADVANCED GD40 Glucose, β-Ketone and Cholesterol Monitoring System, a device for measuring glucose, beta-hydroxybutyrate (β-ketone), and cholesterol in fresh capillary whole blood. It is a 510(k) summary, therefore, it focuses on demonstrating substantial equivalence to predicate devices rather than a detailed clinical study for a novel device.

Based on the provided information, here's a breakdown of the acceptance criteria and the study conducted to prove the device meets these criteria:

Key Takeaway: The document primarily focuses on non-clinical and clinical "studies" to demonstrate performance characteristics and compare them to predicate devices, rather than a single, large-scale comparative effectiveness study with human readers (MRMC). The "acceptance criteria" are implied by the performance characteristics tested and similarity to the predicate.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated as numerical targets in a table within the provided text. Instead, the document discusses "performance criteria were met" and that the device "met design specifications and requirements." The "acceptance criteria" are implied by meeting the established ranges and performance levels comparable to the predicate devices.

However, the "performance" is reported through the summary of testing. Since this is a 510(k) submission, the primary "performance" shown is that the device is substantially equivalent to the predicate devices. The listed similarities and differences in characteristics serve as the de facto "reported device performance."

2. Sample Size and Data Provenance

• Test Set Sample Size: The document does not specify the sample sizes for the "non-clinical" or "clinical" studies. It only states that "Non-clinical and clinical studies were conducted to test, verify and validate the performance."
• Data Provenance: The document does not explicitly state the country of origin for the data or whether the studies were retrospective or prospective. Given the submitter's address (TaiDoc Technology Corporation, New Taipei City, Taiwan), it's highly probable the studies were conducted in Taiwan or involved participants from that region. The studies are described as "verification and validation testing" and "user evaluation," which suggests prospective data collection for the purpose of regulatory submission.

3. Number of Experts and Qualifications for Ground Truth

• This information is not provided in the summary. Since the device is a direct measurement system (glucose, ketone, cholesterol) and relies on chemical reactions rather than interpretation of medical images or complex diagnostic algorithms, the "ground truth" would typically be established by laboratory reference methods, not by expert consensus of clinicians/radiologists.
• Therefore, the concept of "experts" in the context of establishing ground truth for this type of device (an in-vitro diagnostic) would refer to the use of highly accurate laboratory equipment and trained laboratory personnel following established protocols, rather than medical specialists.

4. Adjudication Method (for test set)

• This is not applicable and not provided. Adjudication methods like 2+1 or 3+1 are used in studies where human readers (often radiologists) interpret medical images and their interpretations need to be reconciled to establish ground truth or compare to AI performance. For an in-vitro diagnostic device that measures chemical concentrations, the ground truth comes from laboratory reference methods, not subjective human interpretation requiring adjudication.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

• No, an MRMC comparative effectiveness study was not done (or at least not described in this summary). This type of study is relevant for imaging AI devices where the effect of AI assistance on human reader performance is evaluated.
• This device is an in-vitro diagnostic for direct chemical measurement, not an imaging AI. Therefore, an MRMC study is not relevant for demonstrating its performance or substantial equivalence.

6. Standalone (Algorithm Only) Performance

• No, not specified as a separate study type in the context of imaging AI.
• However, the "Non-Clinical Testing Summary" mentions "functional performance tests (precision, linearity, interference, flex studies)." These are essentially "standalone" performance evaluations of the device's accuracy and robustness under various conditions, independent of a human user's direct interpretive "performance" in the way an AI algorithm's standalone performance might be assessed. The "clinical testing" included a "user evaluation" to confirm accuracy and ease of use in a real-world scenario.

7. Type of Ground Truth Used

The ground truth used for this device would be laboratory reference methods.

• The test principle explicitly states that the device is "calibrated to display the equivalent of plasma glucose values to allow comparison of results with laboratory methods."
• The non-clinical testing included "precision, linearity, interference, flex studies," all of which require comparison to a highly accurate reference method to establish the true concentration of the analytes (glucose, β-ketone, cholesterol).
• For the β-ketone and cholesterol measurements, the process involves enzymatic reactions that are proportional to the amount of the substance in the sample, which implies quantitative comparison to a known concentration.

8. Sample Size for the Training Set

• This information is not applicable and not provided. This device is a traditional in-vitro diagnostic, not a machine learning or AI-based device that would require a "training set" in the sense of AI model development. Its calibration and function are based on electrochemical biosensor technology and established chemical principles.

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

• This is not applicable as there is no "training set" in the context of an AI/ML algorithm. The device's operational parameters would be established through calibration against known standards and validation against reference laboratory methods during its development and manufacturing process.

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