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The CONTOUR® NEXT GEN Blood Glucose Monitoring System consists of the CONTOUR® NEXT GEN meter, CONTOUR® NEXT blood glucose test strips and the CONTOUR® Diabetes app.

The CONTOUR® NEXT GEN Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood drawn from the fingertips. The CONTOUR® NEXT GEN Blood Glucose Monitoring System is intended to be used by a single person and should not be shared. The CONTOUR® NEXT GEN Blood Glucose Monitoring System is intended for self-testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid in monitoring the effectiveness of a diabetes control program.

The CONTOUR® NEXT GEN Blood Glucose Monitoring System should not be used for the diagnosis of or screening for diabetes or for neonatal use.

The system is intended for in vitro diagnostic use only.

The CONTOUR® PLUS BLUE Blood Glucose Monitoring System consists of the CONTOUR® PLUS BLUE meter, the CONTOUR® PLUS blood qlucose test strips, and the CONTOUR® Diabetes app.

The CONTOUR® PLUS BLUE Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood drawn from the fingertips. The CONTOUR® PLUS BLUE Blood Glucose Monitoring System is intended to be used by a single person and should not be shared. The CONTOUR® PLUS BLUE Blood Glucose Monitoring System is intended for self-testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid in monitoring the effectiveness of a diabetes control program.

The CONTOUR® PLUS BLUE Blood Glucose Monitoring System should not be used for the diagnosis of or screening for diabetes or for neonatal use. The CONTOUR® PLUS blood glucose test strips are for use with the CONTOUR® PLUS BLUE meter to quantitatively measure glucose in fresh capillary whole blood drawn from the fingertips.

The system is intended for in vitro diagnostic use only.

CONTOUR® NEXT GEN and CONTOUR® PLUS BLUE Blood Glucose Meters have Bluetooth Low Energy technology built in so that the meters can communicate wirelessly to smart phones and tablets. The CONTOUR® NEXT GEN meter uses the CONTOUR® NEXT blood glucose test strips and CONTOUR® NEXT control solution and CONTOUR® PLUS BLUE meter uses CONTOUR® PLUS blood glucose test strips and CONTOUR® PLUS control solution respectively. The meters can be connected to the CONTOUR® Diabetes app. Both the meters use two replaceable coin cell batteries. Both the meters' shape is a traditional oval form factor. The CONTOUR® NEXT GEN and CONTOUR® PLUS BLUE meters have smartLIGHT® and smartCOLOR® indicator features respectively to see if a glucose result is above, within, or below target range.

Here's an analysis of the provided text regarding the acceptance criteria and study for the CONTOUR® PLUS BLUE and CONTOUR® NEXT GEN Blood Glucose Monitoring Systems.

It's important to note that the provided FDA 510(k) clearance letter and summary primarily focus on demonstrating substantial equivalence to a predicate device, specifically for a minor modification (change in Bluetooth Low Energy microprocessor). As such, the documentation does not contain exhaustive details about the initial validation studies that established the device's fundamental accuracy and performance. Instead, it leverages previous clearances and focuses on showing that the change doesn't negatively impact performance.

Therefore, for several points requested in the prompt, the information is not available in the provided text, as the submission is for a modification rather than an entirely new device's initial clearance.

Acceptance Criteria and Device Performance

The document states that "Bench testing showed that the CONTOUR® NEXT GEN Blood Glucose Monitoring System and CONTOUR® PLUS BLUE Blood Glucose Monitoring System performed as intended and met the relevant standards (ANSI IEEE C63.27-2021, IEEE UL Std 2621.2-2022, IEC 60601-1-2 Edition 4.1 2020-09 CONSOLIDATED VERSION), performance testing and software testing applicable to this change."

While specific numerical acceptance criteria (e.g., accuracy percentages) and detailed reported performance metrics are not explicitly listed in this 510(k) summary, the mention of "relevant standards" and "performance testing" implies that the device met the established performance requirements for blood glucose monitoring systems. For the purpose of this specific modification submission, the critical acceptance criterion was demonstrating that the measurement function was not impacted by the change.

Given the nature of the submission (a change in microprocessor), the primary 'acceptance criteria' in this context are:

Note: For a full, initial clearance of a blood glucose meter, specific accuracy criteria (e.g., ISO 15197) would be provided, often specifying percentages of readings within a certain deviation from a reference method (e.g., laboratory analyzer) for different glucose ranges. These details are not in the provided modification summary.

Study Details

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not specified for this particular submission's testing. The document states "Bench testing including reliability testing, software verification and validation, and confirmation of no impacts to BGM measurement was conducted." This type of testing typically involves a set number of meters and strips, and controlled blood samples, but the exact quantities are not detailed in this summary.
   • Data Provenance: Not explicitly stated (e.g., country of origin). The testing described is "bench testing," implying laboratory-based evaluation. The document also states "The modified devices also relied on previously conducted analytical testing to support substantial equivalence." This suggests some data would be retrospective from prior clearances. The "clinical testing was leveraged from the previous clearances," meaning no new clinical trials were conducted for this specific modification.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not Applicable / Not Specified. For a blood glucose meter, "ground truth" for accuracy is typically established by comparative measurements against a laboratory reference method (e.g., a YSI Glucose Analyzer) using blood samples with known glucose concentrations, not by expert consensus on visual review as might be the case for imaging devices. The document does not describe the specific ground truth establishment method for the bench testing beyond stating "confirmation of no impacts to BGM measurement." For the leveraged clinical testing (from previous submissions), the ground truth would have been established using a laboratory reference method, but the details are not provided here.

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

   • Not Applicable. Adjudication methods like 2+1 or 3+1 are used in studies involving human interpretation of data (e.g., radiology reads) to resolve discrepancies. This document describes bench testing for a physical/electrical device modification and leveraging prior clinical data, neither of which involves such adjudication processes.

4. 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. This is a blood glucose monitoring system, not an AI-powered image analysis or diagnostic tool involving human readers. Therefore, an MRMC study is not relevant or performed for this device.

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

   • Partially Applicable. Blood glucose meters are essentially standalone algorithms (or systems) that provide a numerical output. The "bench testing" and "confirmation of no impacts to BGM measurement" assessed the device's performance directly, independent of a human "in the loop" for the measurement itself, beyond the act of sampling. The focus was on the performance of the meter and strips, and the impact of the new microprocessor on that performance.

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

   • Analytical Reference Method. For blood glucose meters, the ground truth for accuracy is established by a highly accurate laboratory reference method (e.g., YSI Glucose Analyzer) that measures glucose concentration in blood samples. This is a scientific, analytical measurement, not based on expert consensus or pathology. While not explicitly detailed for this submission's testing, it would have been the ground truth for the "previously conducted analytical testing" and "clinical testing leveraged from the previous clearances."

7. The sample size for the training set:

   • Not Applicable / Not Specified. This document describes a modification to an existing, cleared device, not the development of a new device or an AI/machine learning model that would have a traditional "training set." The performance assessments are validation efforts, not model training.

8. How the ground truth for the training set was established:

   • Not Applicable. See point 7.

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The Contour® next GEN Blood Glucose Monitoring System consists of the Contour® next GEN meter, Contour® next blood glucose test strips and the Contour® Diabetes app.

The Contour® next GEN Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood drawn from the fingertips. The Contour® next GEN Blood Glucose Monitoring System is intended to be used by a single person and should not be shared. The Contour® next GEN Blood Glucose Monitoring System is intended for self-testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid in monitoring the effectiveness of a diabetes control program.

The Contour® next GEN Blood Glucose Monitoring System should not be used for the diagnosis of or screening for diabetes or for neonatal use.

The system is intended for in vitro diagnostic use only.

CONTOUR® NEXT GEN Blood Glucose Monitoring System is a blood glucose meter with Bluetooth Low Energy technology built in so that the meter can communicate wirelessly to smart phones and tablets. The meter uses the CONTOUR® NEXT blood glucose test strips and CONTOUR® NEXT control solution. The meter can be connected to the CONTOUR® Diabetes app. It uses two replaceable CR2032 or DL2032 coin cell batteries. The meter's shape is a traditional oval form factor, and it includes an illuminated strip port with colors indicating if a glucose result is above, within, or below target.

The provided text describes a 510(k) summary for the CONTOUR® next GEN Blood Glucose Monitoring System. This submission focuses on demonstrating substantial equivalence to a predicate device due to minor modifications (e.g., changes to internal meter circuitry due to component end-of-life, changes to packaging, user guide format, and test strip packaging from bottled to foil-packed).

The information provided is typical for a 510(k) submission of a blood glucose monitoring system, which primarily relies on analytical performance data (accuracy of glucose measurements) to demonstrate that the device performs as intended and is substantially equivalent to a predicate. This type of device does not involve an AI algorithm with a training or test set, nor does it involve expert reviews, ground truth establishment through consensus, or MRMC studies.

Therefore, the requested information regarding AI acceptance criteria and study details (sample sizes for training/test sets, data provenance, number of experts, adjudication methods, MRMC studies, standalone performance, and ground truth types) is not applicable to this specific device submission. The device described is a physical medical device (blood glucose meter and test strips), not an AI-powered diagnostic system.

However, I can extract information related to the performance testing mentioned, even if it's not structured around AI-specific criteria.

Key takeaway: This document does not describe an AI medical device.

Information applicable to the device (even without AI context):

1. A table of acceptance criteria and the reported device performance:
   The document states: "Verification testing against well-established methods showed that the modified CONTOUR® NEXT GEN Blood Glucose Monitoring System, with the proposed changes outlined herein, performed as intended and met the system specifications."
   It also mentions: "Validation testing with the proposed black and white pamphlet User Guide demonstrated that the CONTOUR® NEXT GEN Blood Glucose Monitoring System continued to be easy to use by typical customers."
   However, the specific numerical acceptance criteria and reported performance data are not detailed in this 510(k) summary. For a blood glucose meter, this would typically involve accuracy metrics (e.g., % of results within ±X% of reference, ISO 15197 compliance). This summary only states that they were met.

2. Sample sizes used for the test set and the data provenance:
   Not explicitly stated in the provided text. For a blood glucose meter, validation studies would involve a sufficient number of blood samples (from various glucose concentrations) and potentially human subject testing for usability/accuracy. The provenance would likely be from clinical sites where these tests were performed.

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, as this is not an AI diagnostic device. Ground truth for blood glucose meters is established by reference laboratory methods (e.g., YSI or hexokinase method) on the same blood samples.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set:
   Not applicable.

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, as this is not an AI diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
   Not applicable, as this is not an AI algorithm. The device itself is the "standalone" entity that performs the glucose measurement.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):
   For a blood glucose monitoring system, the ground truth for glucose levels is established using a highly accurate and precise laboratory reference method (e.g., YSI 2300 STAT Plus Glucose & Lactate Analyzer, or a hexokinase enzymatic method).

8. The sample size for the training set:
   Not applicable, as this is not an AI device with a training set.

9. How the ground truth for the training set was established:
   Not applicable, as this is not an AI device.

In summary, the provided document is a 510(k) premarket notification for a blood glucose monitoring system, which is a physical diagnostic device. It does not contain information about AI algorithm development, training, or testing, and therefore, most of the requested details are not relevant to this specific submission.

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The Contour® next GEN Blood Glucose Monitoring System contour® next GEN meter, Contour® next test strips and the Contour® Diabetes app.

The Contour® next Gen Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood drawn from the fingertips. The Contour® next GEN Blood Glucose Monitoring System is intended to be used by a single person and should not be shared. The Contour® next GEN Blood Glucose Monitoring System is intended for self-testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid in monitoring the effectiveness of a diabetes control program.

The Contour® next GEN Blood Glucose Monitoring System should not be used for the diagnosis of or screening for diabetes or for neonatal use.

The system is intended for in vitro diagnostic use only.

Contour® next GEN Blood Glucose Monitoring System is a blood glucose meter with Bluetooth Low Energy technology built in so that the meter can communicate wirelessly to smart phones and tablets. The meter uses the Contour® next test strips and Contour® next control solution. The meter can be connected to the Contour® Diabetes app. It utilizes a similar algorithm as the one used in the Contour® next ONE blood glucose meter. It uses two replaceable CR2032 coin cell batteries. The meter's shape is a traditional oval form factor and it includes an illuminated strip port with colors indicating if a glucose result is above, within, or below target.

The document provides information on the Contour® next GEN Blood Glucose Monitoring System, a medical device for quantitative measurement of glucose in fresh capillary whole blood. The device has been reviewed by the FDA and determined to be substantially equivalent to a legally marketed predicate device.

Here's an analysis of the provided text, addressing your specific questions about acceptance criteria and the study proving the device meets these criteria:

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

The document does not explicitly provide a table of acceptance criteria for glucose measurement accuracy with specific numerical targets (e.g., % of readings within +/- X mg/dL or %). However, it states that "Clinical trials and bench testing showed that the Contour® next GEN Blood Glucose Monitoring System performed as intended and met the system specifications."

For glucose meters, the generally accepted accuracy standards are often based on ISO 15197 (or similar national standards). The FDA might have specific internal or guidance-based acceptance criteria for substantial equivalence claims. Given the context of a 510(k) submission, the device is being compared to a predicate, implying that its performance is equivalent to, or better than, the predicate device which presumably met relevant accuracy standards at its time of clearance.

Without direct quantitative performance data in this specific document, a table cannot be fully constructed. However, the qualitative "reported device performance" is that it "performed as intended and met the system specifications."

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 mentions "Clinical trials and bench testing" and "Usability testing" but does not specify the sample sizes used for these test sets.
Similarly, data provenance (country of origin, retrospective or prospective) is not detailed in this summary. These details would typically be found in the full submission, which is not provided here.

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 monitoring system, the "ground truth" for glucose concentration is typically established by laboratory reference methods (e.g., using a YSI glucose analyzer) rather than expert radiographic review. The document does not specify details about the personnel or their qualifications involved in establishing this reference ground truth.

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

Adjudication methods like 2+1 or 3+1 are typically for human reader studies involving subjective interpretations (e.g., radiology). For a blood glucose meter, the "ground truth" is a quantitative measurement from a reference laboratory instrument, which doesn't involve human interpretation directly or require adjudication in the same way. Therefore, this concept is not applicable in the context of a glucose meter's accuracy testing, and 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

An MRMC study is relevant for AI-assisted diagnostic imaging, where human readers interpret cases with or without AI assistance. This is not applicable to a blood glucose monitoring system, which provides a direct numerical measurement and is used by individuals for self-monitoring. The device itself is not an AI system assisting human interpretation of images. Consequently, no MRMC study or effect size for human reader improvement is mentioned or expected.

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

For a blood glucose meter, the "standalone performance" is essentially the device's accuracy in measuring glucose values against a reference method. The document states that "Clinical trials and bench testing showed that the Contour® next GEN Blood Glucose Monitoring System performed as intended and met the system specifications." This implies that the device's ability to measure glucose values accurately was assessed, which is its standalone performance. The system's algorithm (mentioned as "similar algorithm as the one used in the Contour® next ONE blood glucose meter" and having "Modified terms in the equations") is intrinsic to its measurement process.

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

The ground truth for a blood glucose monitoring system is established by highly accurate laboratory reference methods for glucose measurement, typically performed on venous blood samples. These reference methods are considered the gold standard for quantifying glucose concentration. The document does not explicitly state "laboratory reference method" but this is the standard practice for such devices.

8. The sample size for the training set

The document does not provide information on the sample size for the training set. Blood glucose meters typically use algorithms (the document mentions "similar algorithm as the one used in the Contour® next ONE" and "Modified terms in the equations"), which might be developed using extensive calibration data. Details about this data (size, characteristics) are not available in this summary.

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

Similar to the test set, the ground truth for any data used in training/calibration of the glucose meter's algorithm would have been established by highly accurate laboratory reference methods for glucose measurement. The document does not provide specifics on how this was established for the training data.

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