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The Precision/Optium Point of Care Blood Glucose Test Strip with True Measure Technology is intended for in vitro diagnostic use. The test strip quantitatively measures glucose (D-glucose) in fresh neonatal, venous, arterial and fingertip capillary whole blood. The test strip is indicated for use by health care professionals in health care facilities. The test strip is to be used for monitoring diabetes mellitus. This strip may be used with the Precision Xtra and Optium meters.

The Precision/Optium Point of Care Blood Glucose Test Strips with True Measure Technology is to be used for blood glucose testing with the Precision Xtra/Optium and Precision PCx Blood Glucose Meters. These systems utilize amperometric biosensor technology to generate a current. The size of the current is proportional to the amount of glucose present in the sample, providing a quantitative measure of glucose in fresh whole blood and control solutions.

The provided text describes information about a 510(k) submission for a blood glucose test strip device, but it lacks specific details regarding acceptance criteria, direct performance metrics, or detailed study methodologies that would allow for a comprehensive answer to all the requested points.

However, based on the available information, I can provide the following:

1. A table of acceptance criteria and the reported device performance

The document doesn't explicitly state quantitative acceptance criteria or a detailed performance table. It broadly states that the studies "demonstrated that healthcare professionals could obtain blood glucose results that are substantially equivalent to a comparative method" and that the performance is "acceptable and comparable to the performance to a comparative method." To create a specific table, detailed performance data (e.g., bias, precision, correlation to a reference method) and their corresponding acceptance limits would be required. This information is typically found in the full 510(k) summary or appended study reports, which are not included in the provided snippets.

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 states "The performances of the Precision/Optium Point of Care Blood Glucose Test Strip with True Measure Technology was studied in the laboratory and in clinical settings by healthcare professionals." There is no specific sample size mentioned for the test set, nor is there information about the country of origin of the data or whether it was retrospective or prospective.

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)

For a blood glucose test strip, the "ground truth" is typically established by measurements from a highly accurate laboratory reference method (e.g., YSI analyzer, hexokinase method), not by expert consensus in the same way it would be for an imaging diagnostic. Therefore, the concept of "experts used to establish ground truth" with specific qualifications (like radiologists) does not directly apply here. The "experts" involved would be the clinical laboratory personnel performing the reference method and the healthcare professionals using the device in the clinical study. No specific number or qualifications of these individuals are provided.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

Adjudication methods like 2+1 or 3+1 are primarily relevant for subjective assessments (e.g., image interpretation where multiple readers might disagree). For objective measurements like blood glucose, adjudication as described is generally not applicable. Instead, comparisons are made directly to a reference method. No adjudication method is mentioned.

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

MRMC studies and the concept of AI assistance improving human reader performance are relevant for diagnostic devices that involve human interpretation, particularly in imaging. This is not applicable to a blood glucose test strip, which provides a direct quantitative measurement.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done

A blood glucose test strip is inherently a "standalone" device in that it produces a result directly from a biochemical reaction on the strip, interpreted by a meter. The performance described would be the "algorithm only" or device-only performance compared to a reference standard. The document confirms studies were done to demonstrate performance.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

The ground truth for this device would be established by a highly accurate laboratory reference method for glucose measurement (e.g., hexokinase method, YSI analyzer). The document mentions comparison to a "comparative method," which strongly implies such a laboratory reference standard.

8. The sample size for the training set

The document does not provide any information about a specific training set or its sample size. This type of information is typically more relevant for devices employing machine learning or AI algorithms with distinct training and test phases. For a biosensor test strip, the "training" (calibration and algorithm development) would be an integral part of its original design and development, rather than a separate, explicitly defined "training set" in the context of clinical validation data.

9. How the ground truth for the training set was established

As with point 8, the document does not distinguish a "training set" in this context. The "ground truth" for the development and calibration of the device's measurement algorithm would have been established using laboratory reference methods to correlate the electrochemical signal from the strip to actual glucose concentrations across a wide range.

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