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The FreeStyle InsuLinx Blood Glucose Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood samples drawn from the fingertip. The FreeStyle InsuLinx Blood Glucose Monitoring System is intended to be used by a single person and should not be shared.

The FreeStyle InsuLinx Blood Glucose Monitoring System is intended for self testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid to monitor the effectiveness of diabetes control. The FreeStyle InsuLinx Blood Glucose Monitoring System should not be used for the diagnosis of or screening for diabetes or for neonatal use.

The FreeStyle InsuLinx Blood Glucose Test Strips are for use with the FreeStyle InsuLinx Blood Glucose Meter to quantitatively measure glucose in capillary whole blood samples drawn from the fingertip.

The FreeStyle InsuLinx Meter, in conjunction with the FreeStyle InsuLinx Test Strips works on the principal of coulometric biosensor technology, measuring glucose by its reaction with Glucose Dehydrogenase (GDH) in blood samples or control solutions, through electrochemical mediation.

The device automatically logs blood glucose results and other events to create a customized logbook. The FreeStyle InsuLinx System has a large touch screen and a user interface designed for an easy user experience.

Patient and Healthcare Professionals can pre-program audible and visual reminders for blood glucose testing, or other individual needs.

Weekly messages feature assist the patient in identifying patterns in their blood glucose results. Using a rolling report, the measured glucose values are summarized according to the proportion within, above. or below the predetermined target range entered by the patient or HCP. These results are displayed in a simple graphical format and include a count of the tests performed. An additional algorithm compares the prevailing blood glucose levels during the preceding week with simple messages relating to achievement versus target glucose levels.

The FreeStyle InsuLinx System has 'plug and play' software that automatically installs on a computer without the need for a CD or internet access (via the meter's USB port and a provided cable). It also provides access to the structured reports for both the healthcare professionals and patients.

The FreeStyle Auto-Assist software produces six different reports to facilitate discussion between patients and their health care professionals in the review, and evaluation of historical blood glucose test results to support an effective diabetes management program. The software also shows trends in blood glucose data in both graphical and text format for guided interpretation.

The Snapshot Report is a general summary of the data for a specified date range.

The Modal Day Report shows the daily patterns of blood glucose levels over a specified date range

The Logbook Report is a table of blood glucose for each day in the specified date range.

The Daily Statistics Report provides an overview of blood glucose over the date range in a series of charts and tables.

The Meal Event Averages Report compares the before and after meal blood glucose level averages for the morning, mid-day and evening times over the specified date range.

The Meter Settings Report shows current meter settings.

These reports provide detailed information on glucose monitoring, and are designed to enable healthcare professionals and patients to assess the effectiveness of diabetes management and then plan appropriate changes to therapy regimens.

Here's an analysis of the provided text regarding the FreeStyle InsuLinx Blood Glucose Monitoring System, focusing on acceptance criteria, studies, and ground truth:

The provided text (510(k) summary) does not contain detailed information about specific studies, sample sizes, or expert qualifications for the device's performance. The submission primarily focuses on establishing substantial equivalence to a predicate device for a modification (the inclusion of a lancing device and lancets). Therefore, much of the requested information cannot be extracted directly from this document.

However, based on the "Comparison to Predicate Device" table, we can infer the acceptance criteria for performance characteristics that the device is expected to meet, as they are listed as "Same" as the predicate device (K111874).

Here's the information that can be gleaned and assumptions made:

Acceptance Criteria and Device Performance

Study Details (Based on available information and common practices for this type of device)

1. Sample size used for the test set and the data provenance:

   • Test Set Sample Size: Not specified in the provided document. For glucose meters, clinical studies typically involve a few hundred subjects, and in-vitro studies involve a larger number of test strips and samples. Given that this submission is for a modification to an already cleared device, it's possible detailed performance data was presented in the original 510(k) (K111874) and not fully reiterated here.
   • Data Provenance: Not specified. For medical devices, studies are often conducted in multiple regions (e.g., North America, Europe) to ensure generalizability. It's almost certainly prospective data for the performance characteristics, as these are measured during specific studies designed to validate the device.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Number of Experts: Not applicable or specified. For blood glucose monitoring systems, the "ground truth" is typically established by laboratory reference methods (e.g., YSI glucose analyzer), not expert human interpretation.
   • Qualifications of Experts: N/A.

3. Adjudication method for the test set:

   • Not applicable. The ground truth for this type of device is an objective laboratory measurement.

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 meter, not an AI-powered diagnostic imaging or interpretation system. It does not involve "human readers" in the sense of interpreting complex cases, nor does it use AI in a way that would require an MRMC study to compare performance with and without AI assistance for human interpretation. The software provides summarized data and trends, which could assist users, but it's not an AI interpretive tool for a human reader.

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

   • Yes, implicitly. The precision and accuracy data ("95% of results should fall within...") refer to the performance of the device itself (the meter and test strips) when measuring glucose. This is a standalone performance assessment against a reference method.

6. The type of ground truth used:

   • Laboratory reference method: For blood glucose meters, the ground truth is established by a highly accurate and precise laboratory instrument, such as a YSI glucose analyzer. The device's measurements are compared against these reference values.

7. The sample size for the training set:

   • Not applicable/specified. This type of device does not typically use a "training set" in the context of machine learning algorithms. The device functions based on a biosensor technology and electrochemistry, whose parameters are determined during development, not "trained" on data in the AI sense.

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

   • Not applicable (as there's no "training set" in the machine learning sense).

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