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510(k) Data Aggregation

    K Number
    K210943
    Date Cleared
    2021-11-22

    (237 days)

    Product Code
    Regulation Number
    862.1355
    Reference & Predicate Devices
    Why did this record match?
    Reference Devices :

    K171941, K193371, K211102

    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 with the FreeStyle Libre 2 App -Android (herein referred to as the 'FreeStyle Libre 2 System' or 'System') is an integrated continuous glucose monitoring system (iCGM) 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 System requires a prescription and is intended for home use. The System consists of the following components: a Sensor which transmits yia Bluetooth Low Energy (BLE), a BLE enabled display device (Reader), and an Android or iOS mobile app (FreeStyle Libre 2 App) downloaded to a compatible smartphone. Scanning of the Sensor via Reader or App provides the user with real-time glucose measurements (glucose values) accompanied by trend information (glucose arrows) and historical glucose information (glucose graph). The user may make treatment decisions based in part on the Sensor glucose results provided by the System. The System also provides configurable alarms designed to warn the user of Low Glucose, High Glucose or Signal Loss.

    AI/ML Overview

    This 510(k) summary describes the FreeStyle Libre 2 Flash Glucose Monitoring System (with FreeStyle Libre 2 App), focusing on the addition of an Android application to the existing system. The document states that the Android app utilizes the identical algorithm and implements the same wireless interfaces with the sensor as the previously cleared Reader and iOS app. Therefore, no additional clinical data was used in this 510(k) to support a determination of substantial equivalence for clinical performance. The original clinical performance data was established in predicate devices K193371 and K211102.

    Since this 510(k) relies on the clinical performance data established in prior submissions (K193371 and K211102) and explicitly states that no new clinical performance data was generated for this specific submission (K210943) regarding the Android App, the detailed acceptance criteria and study information for clinical accuracy are not directly present within this provided text for K210943. The document focuses on non-clinical performance testing for the Android app.

    However, based on the information provided regarding the non-clinical performance of the Android App within this specific 510(k) (K210943):

    Table of Acceptance Criteria and Reported Device Performance (Non-Clinical)

    Acceptance Criteria CategoryReported Device Performance
    Software Verification and ValidationResults of executed protocols met the acceptance criteria, supporting that the Android App software is acceptable for its intended use. (Conducted in accordance with IEC 62304 and FDA Guidance "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices," May 11, 2005.)
    Human FactorsResults demonstrated that the System met usability requirements. (Conducted in accordance with ANSI/AAMI/IEC 62366, IEC 60601-1-6, and FDA Guidance "Applying Human Factors and Usability Engineering to Medical Devices," dated February 3, 2016.)
    Wireless CoexistenceTest results showed the System could tolerate interference generated by tested RF interfering devices and still meet the target performance criteria. (Consistent with AAMI TIR69 and ANSI C63.27, including in-band interference sources and other expected wireless interference sources from the intended use environment.)
    CybersecurityAppropriate risk mitigation controls have been implemented and tested. (Risk management documentation includes analysis of confidentiality, integrity, and availability for data, information, and software, with risk assessment and mitigation for identified threats and vulnerabilities.)
    Electrical Safety and Electromagnetic Compatibility (EMC)Results of the evaluation demonstrated that the System complies with electrical safety and EMC requirements. (Per IEC 60601-1:2005(r)2012 and IEC 60601-1-2:2014, respectively.)

    Due to the nature of this 510(k) being primarily for the addition of the Android app, the following information regarding clinical performance criteria, sample sizes, expert involvement, and ground truth would have been established in the predicate device studies (K193371 and K211102) and are not detailed in this document (K210943):

    • Sample size used for the test set and the data provenance: Not specified in K210943, as clinical data was referenced from predicate devices. For iCGM, clinical studies typically involve a significant number of participants (e.g., hundreds) across varied demographics to assess accuracy across the glycemic range. Data provenance would likely be from multi-center prospective clinical trials conducted in various regions.
    • Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not specified in K210943. In iCGM clinical trials, ground truth is usually established by highly precise laboratory reference methods (e.g., YSI glucose analyzer) rather than expert consensus on device readings.
    • Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable for iCGM clinical accuracy studies where the "ground truth" is typically a laboratory reference method.
    • 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 for iCGM clinical accuracy studies as described. The device provides direct glucose values, not interpretations requiring human reader assistance in the same way as imaging diagnostics. It replaces blood glucose testing for treatment decisions.
    • If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Yes, the core accuracy of the algorithm is evaluated in a standalone manner against laboratory reference values in the predicate device studies. The FreeStyle Libre 2 System itself, including the sensor and its algorithm, performs autonomously to produce glucose readings.
    • The type of ground truth used (expert consensus, pathology, outcomes data, etc): For iCGM devices, the gold standard ground truth for accuracy studies is typically laboratory reference methods, such as those performed by a YSI glucose analyzer, which measures glucose concentration in blood plasma.
    • The sample size for the training set: Not specified in K210943. Training data for the glucose algorithm would have been part of the original development and validation of the FreeStyle Libre 2 system (K193371 and K211102), and would involve a large, diverse dataset of sensor readings and corresponding reference glucose values.
    • How the ground truth for the training set was established: Not specified in K210943. Similar to the test set, the ground truth for training would have been established using highly accurate laboratory reference methods (e.g., YSI analyzer) from blood samples collected concurrently with sensor readings.
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