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The 3test® Glucose Supreme Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood from the finger. 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, 3test* Supreme Glucose Monitoring System only needs a small amount of blood ( 2μL. same as predicate device ). 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 5 seconds, and 200 blood glucose result memory.

The provided text is a 510(k) summary for the "3test® Supreme Glucose Monitoring System." It states that the device is substantially equivalent to a predicate device (3test® Blood Glucose Monitoring System, K050224) and describes its intended use and basic technology. However, it does not include detailed acceptance criteria, specific performance metrics, or information about a comprehensive study that proves the device meets those criteria. The document focuses on regulatory approval based on equivalence rather than presenting an in-depth performance study with acceptance criteria and results.

Therefore, many of the requested fields cannot be filled based on the provided text.

Here's a breakdown of what can and cannot be extracted:

Acceptance Criteria and Study Details for 3test® Supreme Glucose Monitoring System

1. Table of Acceptance Criteria and Reported Device Performance:

Explanation: The document does not specify any quantitative acceptance criteria or report specific performance metrics for accuracy, precision, linearity, or other analytical performance characteristics. It relies on the claim of substantial equivalence to a predicate device (K050224) which is stated to have the "same working principle and technologies."

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

• Sample Size for Test Set: Not provided.
• Data Provenance: The document mentions "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." However, it does not specify the country of origin of the data or whether the studies were retrospective or prospective.

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

• Not provided. The document does not describe the methodology for establishing ground truth for any test set.

4. Adjudication Method for the Test Set:

• Not provided.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done:

• No, a MRMC comparative effectiveness study is not mentioned as this is a glucose monitoring system, not an imaging device typically assessed with MRMC studies.

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

• Not applicable in the typical sense for a glucose monitoring system. This device is used by individuals (patients or healthcare professionals) to obtain a reading. The performance relates to the accuracy of the sensor and meter, not an AI algorithm.

7. The Type of Ground Truth Used:

• Not explicitly stated. For glucose monitoring systems, ground truth is typically established using a laboratory reference method (e.g., YSI analyzer) to measure glucose levels in the same blood samples used for device testing. The document refers to "Pre-clinical and clinical data" but does not detail how ground truth was established for those studies.

8. The Sample Size for the Training Set:

• Not applicable as this is a glucose monitoring system that uses electrochemical biosensor technology, not a machine learning or AI-based device that would typically have a "training set."

9. How the Ground Truth for the Training Set was established:

• Not applicable for the same reason as above.

Summary of Device and Approval Basis:

The "3test® Supreme Glucose Monitoring System" uses an electrochemical biosensor and capillary action to measure glucose in whole blood. It requires 2μL of blood and provides results in 5 seconds. The device is intended for self-monitoring by people with diabetes at home and for use by healthcare professionals in clinical settings.

The 510(k) clearance (K072905) for this device was based on a claim of substantial equivalence to the predicate device, the "3test® Blood Glucose Monitoring System" (K050224). The manufacturer states that both devices use the "same test strips, have the same working principle and technologies." The differences noted are in the levels range of the control solution, battery number, memory results, and test strip lot calibration, which were deemed to not raise new safety or effectiveness aspects. The provided document details the regulatory approval process but does not contain the specific performance study data or acceptance criteria that would typically be reported in a technical validation study.

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The 3test® Glucose test strip is intended to measure the glucose in whole blood with the 3test® Glucose Monitoring System. It is suitable for a person with diabetes to monitor their blood glucose at home by themselves. The 3test® Glucose Monitoring System can also be used at clinical sites by nurses or professional people to test patient's glucose level in whole blood.

NOTE:
a. the 3test is to be used with capillary whole blood from the fingertip
b. the 3test is not for use with neonates
b. the stest meter is to be used with the 3test Blood Glucose Test Strip, and the 3test High and Low Glucose Control Solutions

Based on an electrochemical biosensor technology and the principle of capillary action, 3test® 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 is displayed in 5 seconds, and 100 blood glucose result memory.

Here's an analysis of the provided text regarding the 3test® Glucose Monitoring System, focusing on the acceptance criteria and the study that proves the device meets those criteria:

The provided text does not include specific acceptance criteria or the full study details that would typically be found in a comprehensive medical device submission. It primarily focuses on the device's administrative details, its intended use, and its claim of substantial equivalence to a predicate device.

However, based on the information provided, we can infer some aspects and highlight what's missing:

Acceptance Criteria and Reported Device Performance

The document states, "your blood glucose result is precisely and displayed in 5 seconds." This implies a performance claim related to speed and accuracy, but it doesn't quantify "precisely" with specific numerical acceptance criteria (e.g., accuracy within a certain percentage of a reference method).

Inferred Acceptance Criteria & Reported Performance (Based on limited information):

Key Missing Information for Acceptance Criteria:

• Numerical Accuracy Targets: The most critical missing piece is the quantitative acceptance criteria for accuracy (e.g., ISO 15197 standards like 95% of results within ±15 mg/dL or ±15% of a reference method for concentrations >100 mg/dL).
• Precision/Repeatability/Reproducibility: No data on the variability of the device's measurements.
• Interference Studies: No mention of testing for interference from common substances in blood.
• User Performance Studies (for home use): No details on studies demonstrating that lay users can operate the device correctly and achieve accurate results.
• Linearity/Measuring Range: The range of blood glucose values over which the device is accurate is not specified.

Study Information:

The document broadly mentions "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." However, it does not provide any specific details about these studies.

Here's a breakdown of what we can and cannot answer based on the provided text:

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

   • Not provided. The text does not mention the sample size for any clinical or pre-clinical studies, nor does it specify the data provenance (e.g., country, retrospective/prospective nature).

2. 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)

   • Not provided. The document makes no reference to experts or the establishment of ground truth for any test sets. For blood glucose monitoring systems, ground truth is typically established using a laboratory reference method, not expert consensus as in imaging.

3. Adjudication method (e.g. 2+1, 3+1, none) for the test set

   • Not applicable/Not provided. Adjudication methods like 2+1 or 3+1 are typically used in imaging studies where subjective interpretation is involved. For a quantitative device like a blood glucose meter, ground truth is usually an objective lab reference measurement, not a consensus among experts. No such method is mentioned.

4. 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 device is a blood glucose monitoring system, not an AI-assisted diagnostic imaging device that involves human readers interpreting cases. Therefore, an MRMC study is not relevant to this technology.

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

   • Implied, but details are missing. A blood glucose meter inherently operates as a standalone device to measure glucose levels. Its "performance" would be the accuracy of its measurement against a reference. However, the study details validating this standalone performance (e.g., against a laboratory analyzer) are not provided.

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

   • Not explicitly stated, but inferred to be a laboratory reference method. For a blood glucose meter, the "ground truth" for clinical studies would typically be a highly accurate and precise laboratory reference method (e.g., hexokinase method on a clinical chemistry analyzer). The document does not describe how ground truth was established, only that "Pre-clinical and clinical data are employed."

7. The sample size for the training set.

   • Not applicable/Not provided. Blood glucose meters based on electrochemical biosensor technology generally do not employ machine learning algorithms that require a "training set" in the conventional sense of AI/ML. Their performance is based on the chemical and electrical properties of the test strip and meter. If there were any internal calibration or factory adjustments involving data, it's not described as a "training set."

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

   • Not applicable/Not provided for the same reasons as point 7.

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