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For in vitro diagnostic use (i.e. for external use only) by healthcare professionals and in the home by people with diabetes mellitus to assess the performance of the Liberty Blood Glucose Monitoring System.

The Liberty Control Solutions consist of a viscosity-adjusted, aqueous liquid control solution containing known quantities of glucose. They are packaged in plastic dropper tipped bottles for easy application of the control solutions to the test strips and a red coloration to aid the user to visually confirm application of the control. The product is nonhazardous and contains no human or animal derived materials.

Here's an analysis of the provided information regarding the Liberty Control Solutions:

1. Table of Acceptance Criteria and Reported Device Performance

The provided 510(k) summary does not explicitly state specific acceptance criteria (e.g., numerical thresholds for stability or precision). It lists the types of performance studies conducted but does not detail the pass/fail criteria used. Similarly, it does not provide detailed reported device performance in terms of specific values (e.g., actual stability ranges, precision CV%).

However, based on the general information, we can infer that the acceptance criteria would be linked to demonstrating substantial equivalence to the predicate devices. This implies that the performance (stability, precision) of the Liberty Control Solutions should be comparable to or better than that of the predicate devices.

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

The document does not specify the sample size used for the test set for any of the performance studies (stability, open vial stability, microbial stress stability, test precision).

The document does not provide information on the data provenance (e.g., country of origin, retrospective or prospective nature of data collection).

3. Number of Experts Used to Establish Ground Truth and Qualifications of Experts

This information is not applicable to this device. The Liberty Control Solutions are quality control materials, and their performance is assessed against established analytical methods and specifications, not against expert interpretation of biological samples or images. Therefore, there is no "ground truth" in the sense of expert consensus on patient diagnoses or pathology for this type of device.

4. Adjudication Method for the Test Set

This information is not applicable for the same reasons as #3. Adjudication methods are typically used in studies involving human interpretation or subjective assessments, which are not relevant to the evaluation of a quality control solution.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study is relevant for diagnostic devices that involve human interpretation (e.g., radiologists reading images) to assess the impact of AI assistance on reader performance. The Liberty Control Solutions are quality control materials for blood glucose monitoring systems and do not involve human readers in this context.

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

No, a standalone (algorithm only) performance study was not done in the context of an AI algorithm. The device is a chemical control solution, not an AI algorithm. Its performance is inherent to its chemical composition and manufacturing, assessed through laboratory tests.

7. The Type of Ground Truth Used

For quality control materials like the Liberty Control Solutions, the "ground truth" for performance studies would be:

• Reference Method/Standard Measurements: For glucose concentration, the accurate measurement of glucose using a highly precise and validated reference method (e.g., hexokinase-based methods) would serve as the ground truth.
• Established Specifications: Manufacturers define specifications for stability (e.g., acceptable percentage change over time) and precision (e.g., maximum coefficient of variation). The "ground truth" for these tests is whether the measured performance falls within these predefined acceptable ranges.

The document does not explicitly detail the specific reference methods or internal specifications used to establish ground truth for each performance study.

8. The Sample Size for the Training Set

This information is not applicable. The Liberty Control Solutions are chemical control solutions, not machine learning algorithms or AI models that require a "training set."

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

This information is not applicable for the same reasons as #8.

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For in vitro diagnostic use (i.e. for external use only) by healthcare professionals and in the home by people with diabetes mellitus to assess the performance of the Roche Accu-chek Active, the Bayer Ascensia Microfill, and the LifeScan OneTouch Ultra and FastTake Blood Glucose Monitors.

The Liberty Normal Glucose Control consists of a viscosity-adjusted, aqueous liquid control solution containing a known quantity of glucose. The product is packaged in plastic dropper tipped bottles for easy application of the control solutions to the test strips and a red coloration to aid the user to visually confirm application of the control. The product is non-hazardous and contains no human or animal derived materials.

The provided document describes a Quality Control Material for blood glucose monitors, not an AI/ML-powered diagnostic device. Therefore, many of the requested categories for AI/ML device studies (such as sample size for test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, training set data, etc.) are not applicable.

The document focuses on demonstrating substantial equivalence to existing predicate devices based on comparable characteristics and performance studies relevant to control solutions.

Here's a breakdown of the available information relevant to acceptance criteria and performance, alongside an explanation of why certain AI/ML-specific questions cannot be answered:

1. Table of Acceptance Criteria and Reported Device Performance

Explanation of Applicability/Non-Applicability to AI/ML Questions:

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

  • Not applicable for a control solution. This device is a consumable quality control material, not a diagnostic algorithm. Performance is assessed through chemical stability and precision testing, not diagnostic accuracy on a patient dataset. The "test set" here would refer to vials of the control solution and measurements taken by various blood glucose meters.

• 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):

  • Not applicable. Ground truth for a glucose control solution is established by precise chemical formulation and analytical testing, not by expert interpretation of medical images or patient data.

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

  • Not applicable. Adjudication methods are relevant for ambiguous diagnostic interpretations, not for the chemical properties and performance of a control solution.

• 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 pertains to AI-assisted diagnostic reads, which is not what this device is.

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

  • Not applicable. This device is a control solution, not an algorithm.

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

  • Ground truth: For a glucose control solution, the ground truth is the known, precisely manufactured concentration of glucose within the solution, verified through analytical chemistry methods.

• 8. The sample size for the training set:

  • Not applicable. This device is not an AI/ML algorithm that requires a training set. Its formulation is based on chemical engineering and existing predicate control solutions.

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

  • Not applicable. As above, no training set for this type of device.

Conclusion:

The Liberty Normal Glucose Control is a chemical control solution designed to verify the performance of blood glucose monitors. Its acceptance criteria and performance are established through demonstrating substantial equivalence to legally marketed predicate devices by comparing their physical characteristics, chemical matrix, intended use, and through standard performance studies for such products (stability, open vial, microbial stress, and test precision). The 510(k) summary indicates that these comparisons and studies support the claim of substantial equivalence. The document is not for an AI/ML diagnostic device, so questions related to AI/ML specific study designs are not relevant.

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