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The BroadMaster HealthCare System is a software accessory compatible with legally marketed BroadMaster Biotech glucose meters, such as the Glucose Shepherd Blood Glucose Monitoring System and ADVOCATE® Redi-Code* BMB-EA001S Blood Glucose Monitoring System and is intended for use in the home setting by people with diabetes. It is intended to aid in the review, analysis, and evaluation of patient data to support diabetes management. The BroadMaster HealthCare System receives via USB, stores, and uses patient data for display and reporting, sets meter date, time and alarm. The software is designed for multiple users use and only compatible with personal computer. It's not compatible with other devices such as PDAs or smartphones.

The BroadMaster HealthCare System is a software designed to collect user glucose raw data, analyze results with easy-to-read trend graphs and save glucose raw data to .csv file for report. This system is very easy and friendly to use, even if user has a little computer experience. The BroadMaster HealthCare System Software works with its own behind-the-scene database to store glucose raw data from the glucose device. Glucose raw data downloaded to the software system are stored under the user profile that was selected before the download. In short, the BroadMaster HealthCare System will help user to store the blood glucose device readings, analyze results with easy-to-read trend graphs, and save glucose raw data to .csv file for report.

The provided text describes a software device, the BroadMaster HealthCare System, an accessory to glucose meters. The document asserts that the device meets performance requirements but does not provide specific acceptance criteria or detailed results from a study proving these criteria are met.

Here is an analysis based on the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document states: "The performance of the BroadMaster HealthCare System Software was studied in the laboratory settings. The studies have demonstrated that this system meets the performance requirements of its intended use."

However, no specific acceptance criteria (e.g., accuracy metrics, specific thresholds for data integrity, speed of processing, or reliability measures) are listed, nor are any quantitative performance results reported. Therefore, such a table cannot be constructed from the provided text.

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

The document mentions "laboratory settings" for performance studies. However, it does not specify the sample size used for any test set or the provenance of the data (e.g., country of origin, retrospective or prospective).

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

The document describes a software system that processes glucose meter data. In this context, "ground truth" would likely refer to the accuracy of the glucose meter readings themselves or the correct interpretation of data for display and reporting. The text does not mention the use of any human experts to establish ground truth for the test set, nor does it detail their qualifications.

4. Adjudication Method for the Test Set:

Given that there's no mention of experts establishing ground truth, there is no information provided on any adjudication method (e.g., 2+1, 3+1, none) for a test set.

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

The BroadMaster HealthCare System is a data management and analysis software for glucose readings. It is not an AI-assisted diagnostic tool that would typically involve human readers interpreting images or complex data with and without AI assistance. Therefore, it is highly unlikely that an MRMC comparative effectiveness study was done, and the document does not report any such study or effect size related to human reader improvement with AI assistance.

6. Standalone Performance Study:

The document states, "The performance of the BroadMaster HealthCare System Software was studied in the laboratory settings." This implies a standalone study of the algorithm's performance in processing and presenting data. However, no specific performance metrics or outcomes of such a study are provided beyond the general statement that it "meets the performance requirements."

7. Type of Ground Truth Used:

For a system that handles glucose data, the "ground truth" would be the actual glucose readings from the connected meters, and the software's ability to accurately store, display, and report these values. The document does not explicitly state how this "ground truth" was established, but it implicitly relies on the accuracy of the legally marketed glucose meters it interfaces with. It is not expert consensus, pathology, or outcomes data in the usual sense.

8. Sample Size for the Training Set:

The document does not mention a training set sample size. This type of software, performing data storage, display, and basic trend analysis, is typically rule-based or uses standard data processing algorithms rather than machine learning that requires large training datasets.

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

As there's no mention of a training set, there's no information provided on how ground truth for a training set was established.

Summary of Missing Information:

The provided document offers a high-level overview of the BroadMaster HealthCare System and its intended use but lacks specific technical details regarding its performance studies, including:

• Quantitative acceptance criteria.
• Actual performance results against these criteria.
• Sample sizes of test and training data.
• Methods for establishing ground truth or expert involvement.
• Details on study design (e.g., retrospective/prospective).
• Any mention of AI, MRMC studies, or specific standalone performance metrics beyond a general statement of compliance.

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A.) Glucose Shepherd Blood Glucose Monitoring System is intended for use outside the body (in vitro diagnostic use) at home. It is used for quantitative measurement of glucose level in fresh capillary whole blood samples (from the finger, the palm, the forearm, the upper arm, the calf and the thigh). The alternative site testing can be only used during steady-state blood glucose monitoring. The Glucose Shepherd Blood Glucose Monitoring System is intended for use by a single person and should not be shared. In addition, it is intended for use at home as an aid in monitoring the effectiveness of diabetes control program. It should not be used for the diagnosis or screening of diabetes, nor for the testing of neonates.

The Glucose Shepherd Blood Glucose Monitoring System consists of the Glucose Shepherd Blood Glucose meter and the Glucose Shepherd Blood Glucose test strips. The Glucose Shepherd Blood Glucose meter is used only with Glucose Shepherd Blood Glucose test strips to quantitatively measure glucose in fresh capillary whole blood samples drawn from finger tips, the palm, the forearm, the upper arm, the calf and the thigh.

The Glucose Shepherd Control Solutions are for use with the Glucose Shepherd Blood Glucose Monitoring System as a quality control check to verify the accuracy of blood glucose test results.

B.) Glucose Shepherd Pro Blood Glucose Monitoring System is intended for use outside the body (in vitro diagnostic use). It is used for quantitative measurement of glucose level in fresh capillary whole blood samples (from the finger, the palm, the forearm, the upper arm, the calf and the thigh). The alternative site testing can be only used during steady-state blood glucose monitoring. The Glucose Shepherd Pro Blood Glucose Monitoring System may be used for multiple patients in a professional healthcare setting. I is intended for use as an aid in monitoring the effectiveness of diabetes control program. This system is only used with single-use, auto-disabling lancing devices. It should not be used for the diagnosis or screening of diabetes, for the testing of neonates, or for testing of arterial blood.

The Glucose Shepherd Pro Blood Glucose Monitoring System consists of the Glucose Shepherd Pro Blood Glucose meter and the Glucose Shepherd Pro Blood Glucose test strips. The Glucose Shepherd Pro Blood Glucose meter is used only with Glucose Shepherd Pro Blood Glucose test strips to quantitatively measure glucose in fresh capillary whole blood samples drawn from finger tips, the palm, the forearm, the upper arm, the calf and the thigh.

The Glucose Shepherd Pro control solutions are for use with the Glucose Shepherd Pro Blood Glucose Monitoring System as a quality control check to verify the accuracy of blood glucose test results.

A.) Glucose Shepherd Blood Glucose Monitoring System consists of a blood glucose meter, test strips, control solutions(Level 1, 2 and 3), lancing device, and commercially available sterilized lancets. This system utilizes amperometric method to generate a current. The size of the current is proportional to the amount of glucose presented in the sample, providing a quantitative measure of glucose level in whole blood.

B.) Glucose Shepherd Pro Blood Glucose Monitoring System consists of a blood glucose meter, test strips, control solutions(Level 1, 2 and 3) and single-use lancing devices. This system utilizes amperometric method to generate a current. The size of the current is proportional to the amount of glucose level presented in the sample, providing a quantitative measure of glucose level in whole blood.

This 510(k) summary provides limited information regarding the performance studies. Therefore, a comprehensive description of acceptance criteria and the entire study that proves the device meets those criteria cannot be fully extracted.

However, based on the provided text, here's what can be gathered and inferred:

1. Table of Acceptance Criteria and Reported Device Performance

The document states that both the Glucose Shepherd Blood Glucose Monitoring System and the Glucose Shepherd Pro Blood Glucose Monitoring System were studied in laboratory and clinical settings, and these studies "have demonstrated that this system meets the performance requirements of its intended use."

While explicit numerical acceptance criteria are not detailed in this summary, in the context of blood glucose monitoring systems, "performance requirements" typically refer to accuracy standards. For example, ISO 15197 (In vitro diagnostic test systems - Requirements for blood glucose monitoring systems for self-testing in managing diabetes mellitus) is a commonly referenced standard. A key part of this standard's accuracy requirement is that a certain percentage of results (e.g., 95%) must fall within a defined range of a reference method (e.g., within ±15 mg/dL for glucose concentrations <100 mg/dL and within ±15% for glucose concentrations ≥100 mg/dL).

Given the submission is for a 510(k), the device must demonstrate substantial equivalence to a predicate device. This implies that its performance (including accuracy) is at least as good as, if not better than, the predicate. Therefore, the "reported device performance" is essentially that the device meets relevant accuracy standards and is substantially equivalent to the predicate device.

Since no specific numerical acceptance criteria or detailed performance data are provided in the summary, we can only state the general claim.

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

The document mentions "clinical settings" and "clinical testing results" but does not specify:

• The exact sample size for the test set.
• The country of origin of the data.
• Whether the data was retrospective or prospective.

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

This information is not provided in the 510(k) summary. For blood glucose monitoring systems, ground truth is typically established by laboratory reference methods (e.g., using a YSI glucose analyzer) rather than reliance on human expert consensus, so the concept of "experts establishing ground truth" as it applies to image-based diagnostic systems might not be directly applicable here.

4. Adjudication Method for the Test Set

This information is not provided in the 510(k) summary. Adjudication methods (like 2+1, 3+1) are typically relevant for studies where human interpretation of data is being assessed, often in imaging or subjective diagnostic tasks. For objective measurements like blood glucose, adjudication would refer to how discrepancies between the device and the reference method or across multiple device measurements were handled, which is not detailed here.

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

• No, an MRMC comparative effectiveness study was not done.
• This type of study is not relevant for a blood glucose monitoring system, which is a quantitative measurement device rather than an AI-driven image interpretation or diagnostic system that assists human readers.

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

• A standalone performance study was done.
• The entire premise of a blood glucose monitoring system is its standalone performance (the meter and test strip system providing a direct quantitative measurement). The document states, "The performance... was studied in the laboratory and in clinical settings. The studies have demonstrated that this system meets the performance requirements of its intended use." This confirms a standalone performance evaluation.

7. The Type of Ground Truth Used

• The ground truth for blood glucose monitoring systems is typically established by a highly accurate laboratory reference method, such as a YSI glucose analyzer. While not explicitly stated in the summary, this is the standard practice for evaluating such devices. The document refers to "laboratory testing results" which would involve comparison against such a reference.

8. The Sample Size for the Training Set

• This information is not provided in the 510(k) summary. For a blood glucose monitoring system based on an amperometric method, the "training set" concept (as used in machine learning) is generally not directly applicable. The device's calibration and algorithm are developed through engineering and chemical principles, then validated through testing. If the question refers to the samples used to establish the initial calibration curve or internal algorithms, that detail is not disclosed.

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

• As mentioned in point 8, the concept of a "training set" for ground truth (in the machine learning sense) is not directly applicable to this type of device. The accuracy of the device's measurement is established through rigorous internal development and external validation against highly precise laboratory reference instruments, which would serve as the "ground truth" for evaluating the system's accuracy. These reference instruments are themselves calibrated and maintained according to strict laboratory standards.

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