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510(k) Data Aggregation
(220 days)
FORA V10 BLOOD GLUCOSE MONITORING SYSTEM
FORA V10 No Code Blood Glucose Monitoring System, model TD-4244, is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and the following alternative sites: the palm, the forearm, the upper-arm, the calf and the thigh. It is intended for use by people with diabetes mellitus at home as an aid in monitoring the effectiveness of diabetes control program. The meter contains some speaking functions but has not been validated for use by visually impaired users. It is not intended for the diagnosis of or screening for diabetes mellitus, and is not intended for use on neonates.
This system is intended to be used by a single patient and should not be shared.
FORA V10 test strips are for use with FORA V10 No Code Blood Glucose meter model TD-4244 to quantitatively measure glucose (sugar) in fresh capillary whole blood samples drawn from fingertips, palm, forearm, upper arm calf and thigh.
The FORA control solutions can only be used with FORA V10 No Code Blood Glucose meter, model TD-4244 and the FORA V10 test strips to check that meter and test strips are working together properly.
The alternative site testing in FORA V10 No Code Blood Glucose Monitoring systems model TD-4244 can be used only during steady-state blood glucose conditions.
The system consists of three main products: the meter, test strips, and control solutions. These products have been designed, tested, and proven to work together as a system to produce accurate blood glucose test results. Use only FORA V10 test strips and FORA control solutions with the FORA V10 No Code Blood Glucose Monitoring System, model TD-4244.
Here's an analysis of the provided text regarding the acceptance criteria and study for the FORA V10 No Code Blood Glucose Monitoring System:
1. Table of Acceptance Criteria and Reported Device Performance
The provided text does not explicitly state specific acceptance criteria in terms of numerical thresholds (e.g., accuracy percentages, precision values) that the device must meet. Instead, the submission for the FORA V10 No Code Blood Glucose Monitoring System, model TD-4244, relies on demonstrating substantial equivalence to a predicate device (FORA V10 Blood Glucose Monitoring System, K093035).
The core of the "performance" claim is that it has the "same performance characteristics as the predicate device" and that "Software verification and validation testing confirmed that the performance, safety and effectiveness of the FORA V10 No Code Blood Glucose Monitoring System are equivalent to the predicate device."
Therefore, the implied acceptance criterion is that its performance is equivalent to the predicate. The "reported device performance" is essentially that it is equivalent to the predicate device, which would have had its performance demonstrated in its own 510(k) submission.
Table of (Implied) Acceptance Criteria and Reported Device Performance:
Acceptance Criteria (Implied) | Reported Device Performance |
---|---|
Performance of the FORA V10 No Code Blood Glucose Monitoring System (model TD-4244) is equivalent to the predicate device (FORA V10 Blood Glucose Monitoring System, K093035). | "The FORA V10 No Code Blood Glucose Monitoring System has the same performance characteristics as the predicate device." |
"Software verification and validation testing confirmed that the performance, safety and effectiveness of the FORA V10 No Code Blood Glucose Monitoring System are equivalent to the predicate device." | |
"Based on the information provided in this submission, the FORA V10 No Code Blood Glucose Monitoring System is substantially equivalent to the predicate FORA V10 Blood Glucose Monitoring System." |
2. Sample Size Used for the Test Set and Data Provenance
- Sample Size: The document does not specify the sample size used for any test set (accuracy, precision, etc.). It only mentions that the system was "compared to the YSI 2300 Glucose Analyzer in the Accuracy studies."
- Data Provenance: Not explicitly stated (e.g., country of origin, retrospective or prospective).
3. Number of Experts Used to Establish Ground Truth and Their Qualifications
- Number of Experts: This information is not provided in the document.
- Qualifications of Experts: This information is not provided in the document.
4. Adjudication Method for the Test Set
- Adjudication Method: This information is not provided in the document.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- MRMC Study Done? No. This device is a blood glucose meter, not an imaging or diagnostic device typically requiring MRMC studies for human reader performance. The "performance characteristics" typically refer to analytical accuracy and precision in comparison to a reference method, rather than human interpretation of results.
6. Standalone (Algorithm Only) Performance
- Standalone Performance Done? Yes, indirectly. The core of the performance evaluation is the device's ability to quantitatively measure glucose, which is its standalone analytical performance. The document states: "The FORA V10 No Code Blood Glucose Monitoring System is compared to the YSI 2300 Glucose Analyzer in the Accuracy studies." This confirms a standalone performance evaluation against a reference standard.
7. Type of Ground Truth Used
- Type of Ground Truth: The ground truth for the accuracy studies was established by the YSI 2300 Glucose Analyzer. This is a laboratory reference method widely accepted for determining glucose concentrations. The YSI itself is stated to be "calibrated with NIST (SRM) 917A reference material," confirming a traceable and high-quality reference standard.
8. Sample Size for the Training Set
- Sample Size: The document does not provide information on a training set sample size. This is common for devices like blood glucose meters, as their underlying electrochemical biosensor technology isn't "trained" in the same way a machine learning algorithm is. The "development" and "testing" would involve product development, calibration, and verification/validation, rather than a distinct "training set."
9. How the Ground Truth for the Training Set Was Established
- Ground Truth Establishment for Training Set: As there's no mention of a "training set" in the context of an algorithm that learns, this question is not directly applicable. The device's calibration and design would rely on established laboratory methods and reference materials (like the NIST (SRM) 917A) during its development and manufacturing, but not in the sense of a machine learning training process with ground truth labels.
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(85 days)
FORA V10 BLOOD GLUCOSE MONITORING SYSTEM, MODEL TD-4244
The FORA V10 Blood Glucose Monitoring System is intended for use in the quantitative measurement of glucose in fresh capillary whole blood from the finger and the following alternative sites: the palm, the forearm, the upper-arm, the calf and the thigh. It is intended for use by healthcare professionals and people with diabetes mellitus at home as an aid in monitoring the effectiveness of diabetes control program. It is not intended for the diagnosis of or screening for diabetes mellitus, and is not intended for use on neonates. The alternative site testing in the FORA V10 Blood Glucose Monitoring System can be used only during steady-state blood glucose conditions.
The FORA V10 Blood Glucose Monitoring System consists of Glucose meter, Test Strips, Two levels of Control Solution, commercially available Lancing Device and Sterile Lancets, User Manual, and Storage Pack.
The FORA V10 Blood Glucose Monitoring System (Model TD-4244) met the acceptance criteria by demonstrating substantial equivalence to its predicate device through performance characteristics, specifically by meeting the requirements of ISO 15197.
1. Table of acceptance criteria and the reported device performance:
Acceptance Criteria | Reported Device Performance |
---|---|
ISO 15197 Requirements | "the device met the requirements of ISO 15197." |
Precision | Demonstrated to be "substantially equivalent" to the predicate device. |
System Accuracy | Demonstrated to be "substantially equivalent" to the predicate device. |
2. Sample size used for the test set and the data provenance:
The document mentions "laboratory tests" and "software verification and validation testing," but does not specify the sample size used for the test set. It also does not specify the country of origin of the data or whether the study was retrospective or prospective.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
The document does not provide information on the number of experts used or their qualifications for establishing ground truth.
4. Adjudication method for the test set:
The document does not specify any adjudication method for the test set.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
A multi-reader multi-case (MRMC) comparative effectiveness study was not performed, nor is it relevant for a glucose monitoring system. The study focused on the device's accuracy against a known standard (ISO 15197) and comparison to a predicate device.
6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
Yes, the performance evaluation of the FORA V10 Blood Glucose Monitoring System appears to be a standalone assessment of the device's accuracy and precision, without human interpretation in the loop. The "laboratory tests" and "software verification and validation testing" confirm the device's inherent performance.
7. The type of ground truth used:
The ground truth used for performance comparison was likely based on reference glucose measurements obtained from a laboratory standard method against which the device's readings were compared to assess compliance with ISO 15197. This would involve a highly accurate and precise laboratory instrument with an established accuracy profile.
8. The sample size for the training set:
The document does not provide information regarding a training set sample size. This type of device (blood glucose monitor) typically undergoes calibration during manufacturing rather than a machine learning "training" phase.
9. How the ground truth for the training set was established:
As above, the concept of a "training set" and its associated ground truth establishment is not applicable in the context of this device's reported evaluation. The device would be calibrated against known glucose concentrations.
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