(108 days)
The software is intended for use in home and clinical settings to aid people with diabetes and their health care professionals in review, analysis and evaluation of historical blood glucose test results to support effective diabetes management, including providing direction within the scope of a pre-planned treatment program for adjustments to prescribed insulin, similar to the directions physicians provide to patients as a part of routine clinical practice. The device is not intended to provide any diagnosis on patient results.
An accessory software that enables the person with diabetes and their health care professionals in review, analysis and evaluation of historical blood glucose test results to support effective diabetes management, including providing direction within the scope of a pre-planned treatment program for adjustments to prescribed insulin, similar to the directions physicians provide to patients as a part of routine clinical practice.
The provided document is a 510(k) summary for the ACCU-CHEK® Advisor Insulin Guidance Software, which received clearance in 2005. It focuses on establishing substantial equivalence to a predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria with quantifiable metrics. Therefore, much of the requested information cannot be extracted directly from this document.
Here's an analysis based on the available information:
1. A table of acceptance criteria and the reported device performance
The document does not provide a table of acceptance criteria with specific performance metrics such as accuracy, sensitivity, or specificity. The 510(k) summary primarily asserts substantial equivalence based on features and intended use.
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
The document does not mention a specific 'test set' or 'sample size' for performance evaluation. It describes a comparison to a predicate device based on features and functionality. There is no information on data provenance.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
This information is not provided in the document. The clearance is based on comparison to a predicate device, not on an independent clinical performance study involving expert-established ground truth.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided.
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
The document does not mention an MRMC study or any study evaluating the comparative effectiveness with and without AI assistance for human readers. The device is software for managing blood glucose data and providing guidance within a pre-planned treatment program, not a diagnostic AI system for image interpretation.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
While the software provides "guidance" and "direction," the indication for use states it is "to aid people with diabetes and their health care professionals in review, analysis and evaluation of historical blood glucose test results." This implies a human-in-the-loop scenario. The document does not describe a standalone performance study of the algorithm without human involvement. The "Insulin Guidance Software" itself is the "algorithm only" in the sense that it processes data and provides recommendations, but its ultimate use is in conjunction with patient and healthcare professional review. No specific standalone performance metrics are provided.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The document does not specify the type of ground truth used for performance validation. Given the nature of the device (insulin guidance software), ground truth would likely relate to the accuracy of calculations, the appropriateness of guidance based on input data according to established medical guidelines, or correlation with patient outcomes, but no details are provided.
8. The sample size for the training set
The document does not mention a training set or its sample size. This type of detail is usually associated with machine learning or AI model development, which is not explicitly discussed in this 2005 510(k) summary focused on substantial equivalence to a predicate.
9. How the ground truth for the training set was established
Not applicable, as a training set and its ground truth are not mentioned.
Summary of Acceptance Criteria and the Study that Proves the Device Meets the Acceptance Criteria:
Based on the provided 510(k) summary, the "acceptance criteria" and "study" are primarily focused on demonstrating substantial equivalence to a predicate device rather than presenting detailed performance metrics from a specific clinical study with defined acceptance criteria.
The core of the documentation provided is a comparison table that highlights similarities in features and claims between the ACCU-CHEK® Advisor Insulin Guidance Software and the predicate device, Diacare Monitoring System Software.
Acceptance Criteria (Implicitly based on Substantial Equivalence):
The implied acceptance criteria revolve around the device possessing similar technological characteristics and having the same intended use as a legally marketed predicate device. The features outlined in the "Comparison to Predicate Device" section serve as the basis for this:
| Feature/Claim | Implicit Acceptance Criteria (Demonstrated Similarity) | Reported Device Performance (as stated in document) |
|---|---|---|
| Meter data upload | Ability to upload meter data | Yes. |
| Support | Provision of support mechanisms | Yes; through call center support, labeling and health care professionals. |
| Data storage | Ability to store data | On computer media. |
| Reports and graphs | Generation of similar reports and graphs | Similar graphs and reports can be generated for viewing on a display screen, and hard copy printout. |
| Manual Data Entry | Methods for manual data entry | Similar methods of manually entering data into the software. |
| Delete Data | Methods for deleting data | Similar methods of deleting data. |
| Track non-blood glucose data | Ability to track various patient data | Tracks similar data sets. (i.e. Carbohydrates, insulin, timeblocks, event codes). |
| Overall Intended Use | Aid in review, analysis, and evaluation of blood glucose results and provide insulin adjustment direction within a pre-planned program. | The software is intended for use in home and clinical settings to aid people with diabetes and their health care professionals in review, analysis and evaluation of historical blood glucose test results to support effective diabetes management, including providing direction within the scope of a pre-planned treatment program for adjustments to prescribed insulin, similar to the directions physicians provide to patients as a part of routine clinical practice. |
The Study that Proves the Device Meets the Acceptance Criteria:
The document describes a 510(k) premarket notification process where the device was reviewed for substantial equivalence. The "study" in this context is the detailed comparison to the legally cleared Diacare Monitoring System Software presented in the 510(k) summary. This comparison asserts that the ACCU-CHEK® Advisor Insulin Guidance Software has sufficient similarities in features, claims, and intended use as the predicate device to be substantially equivalent and therefore safe and effective. No independent clinical performance study with statistical endpoints is detailed in this regulatory submission.
§ 868.1890 Predictive pulmonary-function value calculator.
(a)
Identification. A predictive pulmonary-function value calculator is a device used to calculate normal pulmonary-function values based on empirical equations.(b)
Classification. Class II (performance standards).