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The InDuo™ Blood Glucose Meter is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood. The InDuo™ meter is intended for use outside the body ( in vitro diagnostic use) by healthcare professionals and by diabetics at home as an aid to monitor the effectiveness of diabetes control.

The InDuo™ Blood Glucose Meter also functions as the cap for the InDuo™ Insulin Doser. The two devices fit together to form a single unit for user convenience.

The InDuo™ Blood Glucose Meter is a Class II Device for home use, as per 21 CFR § 862.1345. The changes made to the meter were done under design controls, and include ergonomic changes to allow for inclusion of the InDuo™ Insulin Doser to form a single unit for user convenience. The modified device has the same technological characteristics as the legally marketed predicate. The InDuo™ Blood Glucose Meter also functions as the cap for the InDuo™ Insulin Doser. The two devices fit together to form a single unit for user convenience.

The provided 510(k) summary for the InDuo™ Blood Glucose Meter states that "Laboratory and clinical studies demonstrate that the InDuo™ Blood Glucose Meter provides equivalent performance to the ONE TOUCH® Ultra™ Blood Glucose Meter." However, it does not explicitly detail the acceptance criteria or the specific results from these studies. It only makes a general claim of equivalence to a predicate device (K002134).

Therefore, based solely on the provided text, many of the requested details cannot be extracted as they are not present.

Here's a breakdown of what can be extracted and what information is missing:

1. Table of Acceptance Criteria and Reported Device Performance

Acceptance Criteria: Not explicitly stated in the provided text. The submission claims "equivalent performance" to the predicate device, but the specific metrics for this equivalence (e.g., accuracy percentages, standard deviations) are not provided.

Reported Device Performance: Not explicitly stated in the provided text. The submission claims "equivalent performance" to the ONE TOUCH® Ultra™ Blood Glucose Meter, but no specific performance statistics (e.g., accuracy, precision, bias) are given for the InDuo™ meter.

2. Sample Size Used for the Test Set and Data Provenance

Sample Size: Not specified in the provided text.
Data Provenance: Not specified in the provided text. It mentions "Laboratory and clinical studies," which implies prospective data collection, but no details on country of origin are given.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

Not specified in the provided text. For a blood glucose meter, the "ground truth" would likely come from a reference laboratory method (e.g., YSI analyzer), not expert consensus.

4. Adjudication Method for the Test Set

Not applicable/specified in the provided text. Adjudication methods are typically used in studies where human interpretation of medical images or other subjective data is involved. For a blood glucose meter, the "ground truth" is typically an objective lab measurement.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

Not applicable. MRMC studies are relevant for medical imaging devices where multiple readers interpret cases. This is a blood glucose meter.

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

This is a standalone device (blood glucose meter). Its performance would inherently be "standalone" in how it measures glucose from a blood sample. The "human-in-the-loop" aspect would be the user performing the test, but the device's measurement function is automated. The document implies a standalone performance comparison to a predicate device.

7. The Type of Ground Truth Used

Not explicitly stated in the provided text. For blood glucose meters, the ground truth is typically established by reference laboratory methods (e.g., YSI glucose analyzer) that are considered the gold standard for glucose measurement.

8. The Sample Size for the Training Set

Not applicable/specified. This type of device (blood glucose meter) does not typically have a "training set" in the context of machine learning algorithms. Its design and calibration are based on established chemical and electrical engineering principles, not adaptive learning from data.

9. How the Ground Truth for the Training Set Was Established

Not applicable. See point 8.

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