(184 days)
The Libre Rio Continuous Glucose Monitoring System is an over-the-counter (OTC) integrated continuous glucose monitoring (iCGM) device indicated for non-insulin using persons age 18 and older. The System detects trends and tracks patterns and aids in the detection of euglycemia, and hypoglycemia. The System is also intended to autonomously communicate with digitally connected devices.
The Libre Rio Continuous Glucose Monitoring System (herein referred to as the 'System') is an integrated continuous glucose monitoring system (iCGM) that provides continuous glucose measurements every minute to facilitate calculation of glucose values accompanied by trend information (glucose arrows) and historical glucose information (glucose graph). The System is intended for over-the-counter use in a home setting. The System consists of the following components: a Sensor which transmits via Bluetooth Low Energy (BLE), and a mobile application Libre Rio App that is downloaded to a compatible smartphone running iOS and Android operating system.
Here are the details regarding the acceptance criteria and the study that proves the device meets them, based on the provided text:
1. Table of Acceptance Criteria and Reported Device Performance
The provided document does not explicitly present a table of acceptance criteria with corresponding performance metrics for the Libre Rio Continuous Glucose Monitoring System. It primarily focuses on the device's substantial equivalence to a predicate device and summarizes various performance testing categories. The "Reported Device Performance" for each category usually states that acceptance criteria were met, without detailing the specific metrics or thresholds.
However, based on the type of testing mentioned and common practices for CGM devices, we can infer some general areas where acceptance criteria would have been established and reportedly met:
Area of Performance Testing | Implied Acceptance Criteria (General) | Reported Device Performance (Summary) |
---|---|---|
Software Verification & Validation | Adherence to IEC 62304 and FDA guidance for software functions, no critical bugs, software performs as intended. | "Results of executed protocols met the acceptance criteria and therefore support that the System software is acceptable for its intended use." |
Cybersecurity | Adherence to FDA guidance for cybersecurity in medical devices, identification and mitigation of threat/vulnerability risks, protection of confidentiality, integrity, and availability of data. | "Appropriate risk mitigation controls have been implemented and tested." |
Interoperability | Compliance with FDA guidance for interoperable medical devices, successful communication with digitally connected devices. | Approach "developed in alignment with FDA guidance," implying successful implementation. |
Human Factors | Adherence to ANSI/AAMI/IEC 62366, IEC 60601-1-6, and FDA guidance for human factors, demonstrating usability and safety for intended users. | "The analysis and the study performed demonstrated that the changes implemented for the subject device meet the usability requirement for its intended use." |
Bench Testing (CT, MRI, X-ray compatibility) | Device maintains functionality and accuracy under specific CT, MRI, and X-ray conditions; no adverse effects. | "The test results showed all functionality testing acceptance criteria was met." |
Biocompatibility, Sterility, Shelf Life, Packaging, Electrical Safety, EMC, Mechanical Design, Clinical Performance | Each established for the predicate device, implying they met relevant standards and criteria. | "The Libre Rio Sensor is identical to the predicate FreeStyle Libre 2 Sensor and no design changes were introduced to allow compatibility to the Libre Rio App. Therefore, the following supportive performance characteristics established for the predicate device (K222447) is applicable to the subject device and is not impacted." These were implicitly met by the predicate and thus deemed met for the subject device. |
2. Sample Size Used for the Test Set and Data Provenance
The document does not explicitly state the sample sizes for the test sets used in the listed performance tests. It mentions "studies" and "testing" but does not quantify the number of participants or data points.
The data provenance is not explicitly mentioned for the reported tests. However, the study is for the Libre Rio Continuous Glucose Monitoring System, which appears to be a new device (or an updated version) from Abbott Diabetes Care, Inc., located in Alameda, CA, USA. This suggests the data would likely be generated in the USA, and primarily from prospective testing conducted specifically for this submission, especially for areas like human factors, bench testing for new contraindications, and software validation. The clinical performance data is stated to be derived from the predicate device (K222447), which would have its own provenance details.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and Their Qualifications
The document does not provide information on the number of experts used or their qualifications for establishing ground truth for any of the mentioned test sets. It broadly refers to "studies" and "testing" but does not detail the methodology of ground truth establishment for specific components like software, cybersecurity, or human factors.
4. Adjudication Method for the Test Set
The document does not specify any adjudication methods (e.g., 2+1, 3+1, none) used for establishing ground truth in the performance testing.
5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done
No, the document does not mention a Multi-Reader Multi-Case (MRMC) comparative effectiveness study. The device is a continuous glucose monitoring system, which typically involves direct measurement and user interaction, not interpretation by multiple human readers of clinical cases. The "Human Factors" testing mentioned focuses on usability and user interface, not on comparative effectiveness with human interpretation of readings.
6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done
Yes, implicit in the description of the device and testing, especially for "Software Verification and Validation" and the "Sensor glucose algorithm," is that standalone algorithm performance testing was conducted. The device's "Sensor glucose algorithm" is stated to be the "ADC Glucose Algorithm established for the predicate device," which would have undergone rigorous standalone validation. The "Libre Rio App" is designed to autonomously receive and display glucose data, suggesting the algorithm operates independently of immediate human intervention for value generation. The bench testing of the sensor's compatibility with CT, MRI, and X-ray would also involve objective measurements without human interpretation in the loop to assess the sensor's function.
7. The Type of Ground Truth Used
The document does not explicitly state the type of ground truth used for each specific test. However, based on the nature of the device and the tests:
- Clinical Performance (inherited from predicate): For CGM devices, the gold standard for ground truth is typically blood glucose measurements obtained from a laboratory reference method (e.g., YSI analyzer) at various glucose levels.
- Software Verification and Validation: Ground truth would be based on functional specifications and expected outputs for given inputs.
- Cybersecurity: Ground truth involves adherence to security protocols and identified risk mitigations.
- Human Factors: Ground truth is established through user task completion rates, error rates, and subjective feedback against predefined usability goals and safety requirements.
- Bench Testing (CT, MRI, X-ray): Ground truth would be based on physical and electrical performance standards and expected device behavior under specific environmental conditions, potentially using calibrated instruments to verify sensor output accuracy.
8. The Sample Size for the Training Set
The document does not provide information about the sample size for the training set. Given that the sensor glucose algorithm is "ADC Glucose Algorithm established for the predicate device," the training data would be associated with the development of that original algorithm, not necessarily new training for the Libre Rio specifically (unless modifications were made, which is not indicated for the algorithm itself).
9. How the Ground Truth for the Training Set Was Established
The document does not specify how the ground truth for the training set (for the inherited "ADC Glucose Algorithm") was established. For glucose monitoring algorithms, ground truth for training data is typically established through paired comparisons with laboratory reference methods (e.g., YSI blood glucose measurements) across a diverse range of glucose values, patient populations, and physiological conditions.
§ 862.1355 Integrated continuous glucose monitoring system.
(a)
Identification. An integrated continuous glucose monitoring system (iCGM) is intended to automatically measure glucose in bodily fluids continuously or frequently for a specified period of time. iCGM systems are designed to reliably and securely transmit glucose measurement data to digitally connected devices, including automated insulin dosing systems, and are intended to be used alone or in conjunction with these digitally connected medical devices for the purpose of managing a disease or condition related to glycemic control.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Design verification and validation must include the following:
(i) Robust clinical data demonstrating the accuracy of the device in the intended use population.
(ii) The clinical data must include a comparison between iCGM values and blood glucose values in specimens collected in parallel that are measured on an FDA-accepted laboratory-based glucose measurement method that is precise and accurate, and that is traceable to a higher order (
e.g., an internationally recognized reference material and/or method).(iii) The clinical data must be obtained from a clinical study designed to fully represent the performance of the device throughout the intended use population and throughout the measuring range of the device.
(iv) Clinical study results must demonstrate consistent analytical and clinical performance throughout the sensor wear period.
(v) Clinical study results in the adult population must meet the following performance requirements:
(A) For all iCGM measurements less than 70 milligrams/deciliter (mg/dL), the percentage of iCGM measurements within ±15 mg/dL of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 85 percent.
(B) For all iCGM measurements from 70 mg/dL to 180 mg/dL, the percentage of iCGM measurements within ±15 percent of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 70 percent.
(C) For all iCGM measurements greater than 180 mg/dL, the percentage of iCGM measurements within ±15 percent of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 80 percent.
(D) For all iCGM measurements less than 70 mg/dL, the percentage of iCGM measurements within ±40 mg/dL of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 98 percent.
(E) For all iCGM measurements from 70 mg/dL to 180 mg/dL, the percentage of iCGM measurements within ±40 percent of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 99 percent.
(F) For all iCGM measurements greater than180 mg/dL, the percentage of iCGM measurements within ±40 percent of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 99 percent.
(G) Throughout the device measuring range, the percentage of iCGM measurements within ±20 percent of the corresponding blood glucose value must be calculated, and the lower one-sided 95 percent confidence bound must exceed 87 percent.
(H) When iCGM values are less than 70 mg/dL, no corresponding blood glucose value shall read above 180 mg/dL.
(I) When iCGM values are greater than 180 mg/dL, no corresponding blood glucose value shall read less than 70 mg/dL.
(J) There shall be no more than 1 percent of iCGM measurements that indicate a positive glucose rate of change greater than 1 mg/dL per minute (/min) when the corresponding true negative glucose rate of change is less than −2 mg/dL/min as determined by the corresponding blood glucose measurements.
(K) There shall be no more than 1 percent of iCGM measurements that indicate a negative glucose rate of change less than −1 mg/dL/min when the corresponding true positive glucose rate of change is greater than 2 mg/dL/min as determined by the corresponding blood glucose measurements.
(vi) Data demonstrating similar accuracy and rate of change performance of the iCGM in the pediatric population as compared to that in the adult population, or alternatively a clinical and/or technical justification for why pediatric data are not needed, must be provided and determined by FDA to be acceptable and appropriate.
(vii) Data must demonstrate that throughout the claimed sensor life, the device does not allow clinically significant gaps in sensor data availability that would prevent any digitally connected devices from achieving their intended use.
(2) Design verification and validation must include a detailed strategy to ensure secure and reliable means of iCGM data transmission to provide real-time glucose readings at clinically meaningful time intervals to devices intended to receive the iCGM glucose data.
(3) Design verification and validation must include adequate controls established during manufacturing and at product release to ensure the released product meets the performance specifications as defined in paragraphs (b)(1) and (b)(2) of this section.
(4) The device must demonstrate clinically acceptable performance in the presence of clinically relevant levels of potential interfering substances that are reasonably present in the intended use population, including but not limited to endogenous substances and metabolites, foods, dietary supplements, and medications.
(5) The device must include appropriate measures to ensure that disposable sensors cannot be used beyond its claimed sensor wear period.
(6) Design verification and validation must include results obtained through a usability study that demonstrates that the intended user can use the device safely and obtain the expected glucose measurement accuracy.
(7) The labeling required under § 809.10(b) of this chapter must include a separate description of the following sensor performance data observed in the clinical study performed in conformance with paragraph (b)(1) of this section for each intended use population, in addition to separate sensor performance data for each different iCGM insertion or use sites (
e.g., abdomen, arm, buttock):(i) A description of the accuracy in the following blood glucose concentration ranges: less than 54 mg/dL, 54 mg/dL to less than 70 mg/dL, 70 to 180 mg/dL, greater than 180 to 250 mg/dL, and greater than 250 mg/dL.
(ii) A description of the accuracy of positive and negative rate of change data.
(iii) A description of the frequency and duration of gaps in sensor data.
(iv) A description of the true, false, missed, and correct alert rates and a description of the available glucose concentration alert settings, if applicable.
(v) A description of the observed duration of iCGM life for the device.