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The Oh' Care Lite Smart Blood Glucose Monitoring System is intended for the quantitative measurement of glucose (sugar) in fresh capillary whole blood from the fingertips, ventral palm, dorsal hand, upper arm, forearm, calf and thigh. The Oh'Care Lite Smart Blood Glucose Monitoring System is intended to be used by a single patient and should not be shared.

The Oh' Care Lite Smart Blood Glucose Monitoring System is intended for testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid to monitor the effectiveness of diabetes control. It should not be used for the diagnosis of or screening of diabetes or for neonatal use. Alternative site testing should be done only during steady state times (when glucose is not changing rapidly).

The Oh'Care Lite Smart Blood Glucose Test Strips are for use with the Oh'Care Lite Smart Meter to quantitatively measure glucose in fresh capillary whole blood. Fresh capillary whole blood samples may be drawn from the fingertips, ventral palm, dorsal hand, upper arm, forearm, calf and thigh.

The proposed Oh'Care Lite Smart Blood Glucose Monitoring System consists of a meter, test strips, control solution and a lancing device. This blood glucose test system is an in vitro diagnostic device designed for measuring the concentration of glucose in blood by means of an electrical current produced in the test strip and sent to the meter for measurement.

The provided text describes the 510(k) submission for the Oh'Care Lite Smart Blood Glucose Monitoring System. However, it does not contain the detailed acceptance criteria, reported device performance (precision, accuracy, etc.), or study results needed to complete most of your requested information. The document primarily focuses on regulatory approval based on substantial equivalence to a predicate device and mentions general performance data without specifics.

Therefore, for many of your points, I can only state that the information is not provided in the given text.

Here's an attempt based on the information available:

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

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

• Sample size for test set: Not provided in the document.
• Data provenance: Not provided in the document.

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)

• Not applicable/Provided: For a blood glucose meter, ground truth is typically established using a laboratory reference method (e.g., YSI analyzer), not human experts for interpretation. The document does not specify the reference method used.

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

• Not applicable/Provided: Adjudication by human experts is not typically part of the ground truth establishment for a blood glucose meter's analytical performance.

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

• Not applicable: This device is a blood glucose monitoring system, not an AI-assisted diagnostic imaging device. Therefore, an MRMC study comparing human readers with and without AI assistance is not relevant or applicable.

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

• Standalone performance was done (implied): The document states "Verification, validation and testing activities were conducted to establish the performance, functionality and reliability characteristics of the modified devices" and that "The device passed all of the tests based on pre-determined Pass/Fail criteria." This implies that the device's analytical performance was assessed on its own. Specific results are not detailed.

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

• Implied ground truth: For blood glucose monitoring systems, the ground truth is typically established by laboratory reference methods, such as a YSI glucose analyzer, which provides a highly accurate measurement of glucose concentration in blood samples. This document does not explicitly state the reference method, but it is standard practice.

8. The sample size for the training set

• Not applicable/Provided: This device is a traditional medical device (blood glucose meter) and does not appear to involve machine learning or AI models with distinct "training sets" in the conventional sense. The "training set" concept is typically for AI algorithm development.

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

• Not applicable/Provided: As there's no mention of a training set for an AI model, this question is not relevant.

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