(15 days)
The Precision Link systems are intended to collect and report information to assist with diabetes management.
The MediSense Precision Link® Diabetes Data Management System lets you view and analyze results of a MediSense Products meter. It enables the users to upload blood glucose and blood ketone results from a MediSense Products meter, view the information, and print the information using various report formats. Precision Link is designed for use by people with diabetes and/or healthcare professionals that have a basic understanding of personal computers
The Precision Link Diabetes Data Management System is a blood glucose data management software system designed to operate on a Windows/Intel/IBM compatible platform. Data is transferred from the glucose meter via a serial cable to a PC, then processed and presented in various user selected graphical formats. Precision Link is available for home and professional use.
This looks like a 510(k) summary for a medical device called "Precision Link® Diabetes Data Management System". Let's break down the information to answer your questions.
It's important to note that this device is a data management software system, an accessory to a blood glucose testing system, not a diagnostic or therapeutic device itself. Therefore, the "acceptance criteria" and "study" described are focused on software functionality and equivalence to a predicate device, rather than clinical performance metrics typical of a diagnostic test.
Here’s the breakdown based on the provided text:
1. Table of Acceptance Criteria and the Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| System hardware and software verification testing confirms equivalence to predicate. | "System hardware and software verification testing confirms that the modified Precision Link Diabetes Data Management System is equivalent to the currently marketed Precision Link Blood Glucose Data Management System." |
| Changes do not adversely affect safety or effectiveness. | "The changes have been verified and do not adversely affect safety or effectiveness." |
| System verification testing confirms performance as intended with device labeling. | "System verification testing confirms that Precision Link will perform as intended when used in accordance with device labeling." |
| Performance, when used according to intended use, is acceptable and substantially equivalent to the predicate device. | "Test results demonstrate that the performance of the Precision Link Diabetes Data Management System, when used according to the intended use stated above, is acceptable and substantially equivalent to the performance and safety characteristics of the previously mentioned predicate device." |
2. Sample Size Used for the Test Set and the Data Provenance
- Sample Size for Test Set: The document does not specify a numerical sample size for "system hardware and software verification testing" or "system verification testing." It generally refers to these as "testing" without quantifying the number of test cases, data points, or scenarios.
- Data Provenance: The document does not explicitly state the country of origin or if the data used for verification testing was retrospective or prospective. Given it's a software system, the "data" would likely refer to simulated or real blood glucose data used to test the software's ability to process, display, and report this information.
3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts
This type of information is not provided in the document. For a data management software system, "ground truth" establishment in the sense of clinical expert consensus on diagnostic images or pathology slides is typically not applicable. The "ground truth" for this device would be its ability to correctly handle and display data according to specifications. The "experts" would likely be software testers and quality assurance personnel verifying functional requirements, but their number and specific qualifications are not detailed.
4. Adjudication Method for the Test Set
This information is not provided and is generally not applicable for software verification testing of this nature. Adjudication methods (like 2+1 or 3+1) are typically used in clinical studies where disagreement among human readers or experts needs to be resolved to establish a definitive diagnosis or assessment.
5. 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
No, an MRMC comparative effectiveness study was not done. This device is a data management software system, not an AI-powered diagnostic tool intended to assist human readers in interpreting clinical cases. Its purpose is to collect and report existing blood glucose data, not to interpret or provide diagnostic assistance.
6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) was done
The concept of "standalone performance" as typically applied to algorithms for diagnostic tasks (e.g., classifying images) is not directly applicable here. The device is a standalone software system in the sense that it performs its functions (data transfer, processing, display) automatically without real-time human intervention during data handling. Its "performance" is assessed through verification testing described as "system hardware and software verification testing" and "system verification testing," ensuring it functions as intended and is equivalent to the predicate. The "human-in-the-loop" for this type of device would be the user interpreting the reports generated by the software, but the software's performance itself is evaluated based on its functional correctness.
7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)
The document does not explicitly state the "type of ground truth" using these specific terms. For a data management system, the "ground truth" would be defined by the functional specifications and expected output of the software. This means:
- Correct transfer of data from the meter to the PC.
- Accurate processing and storage of that data.
- Correct generation and display of reports and graphical formats as per design documentation.
Verification testing would involve comparing the software's output against these predefined correct outcomes or against the known behavior of the predicate device.
8. The Sample Size for the Training Set
This information is not provided because the device is a data management software system, not a machine learning or AI algorithm that typically requires a "training set." The software is likely developed using traditional software engineering principles and tested against established functional requirements, rather than being "trained" on data.
9. How the Ground Truth for the Training Set Was Established
Since there is no mention of a "training set" or machine learning in the context of this device, this question is not applicable.
§ 862.1345 Glucose test system.
(a)
Identification. A glucose test system is a device intended to measure glucose quantitatively in blood and other body fluids. Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus, neonatal hypoglycemia, and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.(b)
Classification. Class II (special controls). The device, when it is solely intended for use as a drink to test glucose tolerance, is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to the limitations in § 862.9.