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510(k) Data Aggregation

    K Number
    K211102
    Date Cleared
    2021-08-11

    (120 days)

    Product Code
    Regulation Number
    862.1355
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The FreeStyle Libre 2 Flash Glucose Monitoring System is a continuous glucose monitoring (CGM) device with real time alarms capability indicated for the management of diabetes in persons age 4 and older. It is intended to replace blood glucose testing for diabetes treatment decisions, unless otherwise indicated.

    The System also detects trends and tracks patterns and aids in the detection of episodes of hyperglycemia and hypoglycemia, facilitating both acute and long-term therapy adjustments. Interpretation of the System readings should be based on the glucose trends and several sequential readings over time.

    The System is also intended to autonomously communicate with digitally connected devices. The System can be used alone or in conjunction with these digitally connected devices where the user manually controls actions for therapy decisions.

    The System can be used with the FreeStyle Libre 2 Sensor (14 day) or the FreeStyle Libre 2 MediRx Sensor (10 day).

    Device Description

    The FreeStyle Libre 2 Flash Glucose Monitoring System is an integrated continuous glucose monitoring (iCGM) system that provides continuous glucose measurements every minute to provide glucose levels, trends, and real-time alarms capability to aid in the management of diabetes. The FreeStyle Libre 2 System consists of two primary components: a Sensor that transmits via Bluetooth Low Energy (BLE), and a BLE enabled display device (Reader). User initiated RFID scanning of the Sensor via Reader provides the user with real-time glucose measurements (glucose values) accompanied by trend information (glucose arrows) and historical glucose information (glucose graph). Users may use the Sensor glucose results and information provided by the System in making treatment decisions. The System also provides configurable alarms designed to warn the user of Low Glucose, High Glucose or Signal Loss. The system is intended for single-patient use at home and requires a prescription.

    The Sensor is single use, disposable, and powered by a silver oxide battery. The Sensor is provided as two secondary components, Sensor Applicator and Sensor Pack (electron beam sterilized device) which are used to assemble and apply the Sensor to the back of the user's arm. During Sensor application, the sensor tail is inserted about 5.5 millimeters below the surface of the skin through the guidance of a needle. The needle is retracted back into the applicator after insertion, and the Sensor remains attached to the skin with a medical grade adhesive. The Sensor continuously measures glucose concentration in interstitial fluid and has an 8-hour memory capacity. The Sensor is factory calibrated, does not require fingerstick calibration, and can be worn for up to 14 days.

    The Reader is a small handheld device that is powered by a lithium-ion rechargeable battery and uses RFID communication to start new Sensors and to scan Sensors to display and record data and uses BLE communication to issue alarms that notify the user to scan his/her sensor when glucose values pass a high or low glucose threshold. The Reader also has a built-in strip port with blood glucose functionality (that is intended to work with the FreeStyle Precision Neo Blood Glucose test strips, cleared under K171941), and a user interface that includes event logging features.

    The proposed subject device is a modified FreeStyle Libre 2 Flash Glucose Monitoring System that adds compatibility with the FreeStyle Libre 2 MediRx Sensor, which can be worn for up to 10 days. The FreeStyle Libre 2 MediRx Sensor design is unchanged from that of the predicate FreeStyle Libre 2 Sensor, which remains compatible with the modified System. In addition, the Sensor glucose algorithm and Reader design of the modified System remain unchanged from those of the predicate.

    The alternate 10-day wear duration of the FreeStyle Libre 2 MediRx Sensor is achieved by changing a Sensor configuration parameter at manufacturing, which is detected by the predicate Reader to automatically determine the wear duration and accordingly adjust the user interface display of remaining Sensor wear time and ensure the Sensor cannot report data beyond the configured wear duration. In addition, each Sensor type has an end of life parameter, which determines when the Sensor will automatically shut down. This functionality is already built into the Sensor and Reader and was validated as part of previously conducted software validation under K193371.

    Other than the differences related to wear duration, the FreeStyle Libre 2 MediRx Sensor is identical to the predicate Sensor, and the predicate Reader functions as intended with either the predicate FreeStyle Libre 2 Sensor (14 day) or FreeStyle Libre 2 MediRx Sensor (10 day).

    AI/ML Overview

    The provided text is related to a 510(k) premarket notification for the FreeStyle Libre 2 Flash Glucose Monitoring System, specifically for a modification to include compatibility with a 10-day wear sensor (FreeStyle Libre 2 MediRx Sensor).

    The document does not describe an AI/ML-based device where the performance is presented in terms of AI metrics (e.g., accuracy, precision, recall, AUC, etc.) or a multi-reader multi-case (MRMC) study. Instead, it concerns a medical device for continuous glucose monitoring (CGM). The "algorithm" mentioned (Sensor Glucose Algorithm) refers to the internal processing of sensor signals to derive glucose values, not an AI/ML model in the context of clinical decision support or image analysis.

    Therefore, many of the requested criteria (e.g., sample size for test/training set in AI context, number of experts for ground truth, adjudication method, MRMC study, standalone performance for AI, type of ground truth for AI) are not applicable to this device's submission.

    However, I can extract information related to the device's clinical performance evaluation based on the provided text, which supports its substantial equivalence.

    Here's a summary of the relevant information:

    1. Acceptance Criteria and Device Performance:

    The document states: "Clinical data from the adult and pediatric iCGM clinical studies that supported clearance of the predicate device were re-analyzed to show that use of the subject device with the FreeStyle Libre 2 MediRx Sensor for a 10-day wear duration meets the iCGM special controls for clinical performance set forth in 21 CFR 862.1355."

    This indicates that the acceptance criteria are based on the iCGM special controls outlined in 21 CFR 862.1355. The document does not provide a specific table of numerical acceptance criteria or reported device performance metrics (e.g., MARD values, clinical accuracy zones) for the FreeStyle Libre 2 MediRx Sensor in this specific 510(k) submission. It relies on the re-analysis of data from the predicate device's clearance.

    Acceptance Criteria (General)Reported Device Performance (as stated)
    Meets iCGM special controls for clinical performance set forth in 21 CFR 862.1355 for 10-day wear duration."Clinical data from the adult and pediatric iCGM clinical studies that supported clearance of the predicate device were re-analyzed to show that use of the subject device with the FreeStyle Libre 2 MediRx Sensor for a 10-day wear duration meets the iCGM special controls..."

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

    • Sample Size Used for Test Set: Not explicitly stated for this particular 510(k). The clinical performance is based on "re-analyzed" data from "clinical studies that supported clearance of the predicate device (K193371)." To find specific sample sizes, one would need to refer to the original K193371 submission.
    • Data Provenance: Not explicitly stated regarding country of origin. The data is based on "clinical studies that supported clearance of the predicate device." It's retrospective in the sense that existing data was re-analyzed for the new sensor configuration.

    3. Number of Experts and Qualifications for Ground Truth:

    • This question is not applicable in the context of this device. The "ground truth" for a glucose monitoring system is typically a high-accuracy reference method for blood glucose (e.g., YSI analyzer in a controlled lab setting), not expert consensus from radiologists or similar.

    4. Adjudication Method for the Test Set:

    • Not applicable for this type of device. Adjudication methods like '2+1' or '3+1' are common in image analysis studies where human readers provide interpretations and discrepancies are resolved. This is a continuous glucose monitoring device where performance is measured against reference glucose values.

    5. MRMC Comparative Effectiveness Study:

    • No, an MRMC comparative effectiveness study was not done as described for AI assistance. This device is a direct-to-patient glucose monitoring system, not an AI-assisted diagnostic tool that human readers would use to improve their performance.

    6. Standalone Performance:

    • Yes, in essence, standalone performance was done. The device itself provides glucose readings without human interpretation or intervention in the measurement process. The "re-analysis" of clinical data to meet iCGM special controls essentially evaluates this standalone performance of the FreeStyle Libre 2 MediRx Sensor. The output of the device (glucose value) is directly compared against a reference method.

    7. Type of Ground Truth Used:

    • The ground truth used for glucose monitoring devices is typically central laboratory reference glucose measurements (e.g., from a YSI glucose analyzer) taken from blood samples during clinical studies. The document states a re-analysis of "clinical studies," implying the use of such a reference method from the predicate device's trials.

    8. Sample Size for the Training Set:

    • Not explicitly stated/applicable in the context of AI/ML training. The "Sensor Glucose Algorithm" mentioned is likely a deterministic or model-based algorithm, not a trainable deep learning model in the sense of a "training set" for AI. If the algorithm involves parameters that were "trained" or optimized, the document does not specify the sample size used for this internal process. The primary evaluation here is of the modified sensor with an unchanged algorithm.

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

    • Not explicitly stated/applicable in the context of AI/ML training. As above, the ground truth for any underlying algorithm development would refer to the reference glucose measurements used to build or validate that algorithm, but this is not typically referred to as a "training set" in the AI sense for this type of device. The document explicitly states: "the Sensor glucose algorithm... of the modified System remain unchanged from those of the predicate."
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