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The iCare App is intended for use in the home and clinical settings as and their healthcare professionals to view test results which are measured by iHealth devices to better manage user's health and get feedback from their professional care team.

The iCare App can also connect to medical devices and or non-medical devices and get data from devices during measurement or from the data stored in memory of the device for enhanced data managements. Data can be transmitted, displayed, and stored in the App.

The iCare APP is a mobile application on both Android and iOS platforms.iCare allows users to better manage their own health by enabling them to measure their vital signs, access their results and relevant health information with just their smart device and internet connection, and receive feedback from their professional care team.

iCare includes a patient darshboard featuring the Home, Health, Plus, Education, and Profile tabs. Accessory devices can be connected to the system to allow for collection of blood sugar, blood pressure, blood oxygen, and/or weight measurements. The patient darshboard functionality includes the ability to start measuring, allows users to view and track measurements, and export testing schedules for blood sugar, blood pressure, blood oxygen, and weight measurements; send messages to their professional care team; view previous appointment history information; view medication instructions; add entries to the food diary and review feedback from their registered dietician; set timers; and access articles and videos about health knowledge.

The provided text is a 510(k) Summary for the iCare App, focusing on its substantial equivalence to a predicate device. It primarily details regulatory information, device description, and non-clinical test summaries. It does not contain information about a study that proves the device meets specific performance acceptance criteria for a medical diagnostic or screening function.

The iCare App is classified as a "Medical Device Data System" (MDDS) that transmits, displays, and stores data from connected medical devices. Its function is to aid users and healthcare professionals in viewing test results for health management. It explicitly states: "Both devices make no interpretation, evaluation, medical judgments, or recommendations for treatment." This means the app itself doesn't perform diagnostic functions that would require specific performance metrics like sensitivity, specificity, or AUC against a ground truth.

Therefore, many of the requested criteria, such as acceptance criteria for diagnostic performance, a test set, expert ground truth establishment, MRMC studies, or standalone algorithm performance, are not applicable or not provided in this document because the device is a data management system, not a diagnostic algorithm.

Here's a breakdown of the applicable information based on the provided text:

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

The document does not present a table of quantitative performance acceptance criteria for diagnostic accuracy, sensitivity, or specificity, because the iCare App is an MDDS for data management, not a diagnostic tool. Instead, acceptance criteria are implied through the successful completion of non-clinical tests that demonstrate the basic functionality, safety, and effectiveness for its intended use as a data display and storage system.

2. Sample sized used for the test set and the data provenance

• Sample Size for Test Set: Not applicable for diagnostic performance as the device is not a diagnostic algorithm. The document mentions non-clinical testing (software, wireless, cybersecurity, usability) but does not specify "test set" sizes in the context of clinical data for diagnostic performance.
• Data Provenance: Not applicable in the context of clinical diagnostic data. The document focuses on the technical aspects of the software.

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

• Number of Experts: Not applicable, as the device does not perform diagnostic interpretations requiring expert-established ground truth for clinical cases.
• Qualifications of Experts: Not applicable.

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

• Adjudication Method: Not applicable, as there is no clinical test set requiring ground truth adjudication for diagnostic 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

• MRMC Study: No, an MRMC study was not done. The iCare App is an MDDS and does not involve AI assistance for human readers in a diagnostic capacity. It makes "no interpretation, evaluation, medical judgments, or recommendations for treatment."
• Effect Size: Not applicable.

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

• Standalone Performance: No, a standalone performance study in the context of diagnostic accuracy was not done. The device's function is data transmission, display, and storage, not diagnostic algorithm performance.

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

• Type of Ground Truth: Not applicable for clinical diagnostic performance. For the software verification and validation, the "ground truth" would be the successful execution against specified requirements and accepted software engineering practices and FDA guidance.

8. The sample size for the training set

• Training Set Sample Size: Not applicable. This document does not describe a machine learning model that was trained on a dataset. The iCare App is a software application for data management, not an AI/ML algorithm requiring a training set of clinical data for diagnostic purposes.

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

• Ground Truth Establishment for Training Set: Not applicable, as there is no mention of a training set for an AI/ML algorithm.

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TeleRPM Gen2 Blood Glucose Monitoring System is comprised of the TeleRPM Gen2 Blood Glucose Meter and the TeleRPM Blood Glucose Test Strips. TeleRPM Gen2 Blood Glucose Monitoring System is intended to quantitatively measure the glucose concentration in fresh capillary whole blood samples drawn from the fingertips. It is intended for use by persons with diabetes at home as an aid to monitor the effectiveness of diabetes control. It is not intended for neonatal use or for the diagnosis of or screening for diabetes. This system is intended for self-testing outside the body (in vitro diagnostic use), and should only be used by a single person and should not be shared.

TeleRPM Gen2 Blood Glucose Monitoring System consists of TeleRPM Gen2 Blood Glucose Meter and the TeleRPM Blood Glucose Test Strips.

TeleRPM Control Solution, TeleRPM Lancing Device, TeleRPM Lancets are required for use but not included in meter box or test strips box and should be purchased separately. The TeleRPM Control Solution is for use with the above meter and test strip as a quality control check to verify that the meter and test strip are working together properly, and that the test is performing correctly. TeleRPM Lancing Device and TeleRPM Lancets are used for puncturing fingertip and then user can perform qlucose test with blood sample.

TeleRPM Gen2 Blood Glucose Monitoring System is designed to quantitatively measure the glucose concentration in fresh capillary whole blood from the fingertip. The glucose measurement is achieved by using the amperometric detection method. The test is based on measurement of electrical current caused by the reaction of the glucose with the reagents on the electrode of the test strip. The blood sample is pulled into the tip of the test strip through capillary action. Glucose in the sample reacts with glucose oxidase and the mediator. Electrons are generated, producing a current that is positive correlation to the glucose concentration in the sample. After the reaction time, the glucose concentration value is reported in plasma equivalents and is displayed on meter screen.

The provided text primarily focuses on the substantial equivalence determination for the TeleRPM Gen2 Blood Glucose Monitoring System to a predicate device. While it mentions the general types of studies conducted (robustness, precision, linearity, user evaluation, interference, stability, flex studies, software, cybersecurity controls, and a clinical usability study), it does not provide detailed acceptance criteria or numerical performance data as requested for several of your points.

Based on the information available:

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

The document broadly states that the device "met the FDA SMBG OTC Guidance and industry standards" and that "these devices performed as intended and met associated guidance documents and industry standards." Specific numerical acceptance criteria and reported device performance for each study (precision, linearity, interference, etc.) are not detailed in the provided summary. For the user evaluation (clinical study), it states "the clinical performance met the FDA SMBG OTC Guidance."

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

• User Evaluation (Clinical Study): The document mentions "All participants" were able to understand the labeling, use the system, and interpret results. However, the exact sample size for the clinical usability evaluation is not specified.
• Provenance: Not explicitly stated, but the company is located in Zhongshan, Guangdong, China. The testing location isn't specified, but it's reasonable to infer the studies were conducted by or on behalf of the manufacturer, likely in China or a region where they operate.

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

• This information is not provided in the summary. For a blood glucose monitoring system, the "ground truth" for glucose levels would typically be established by a laboratory reference method, not by experts adjudicating results.
• For the usability evaluation, the "ground truth" is about successful interaction with the device, which is assessed through user performance and observation, not expert consensus on a measurement.

4. Adjudication method for the test set:

• This information is not provided. For analytical performance, laboratory reference methods are used, not typically expert adjudication. For usability, the success of user interaction is observed and recorded.

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:

• This is not applicable to this device. A "Blood Glucose Monitoring System" measures blood glucose; it is not an AI-assisted diagnostic imaging device that involves "human readers." Therefore, an MRMC study comparing human readers with and without AI assistance was not performed.

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

• The device performs a direct measurement of blood glucose. Its core function is a "standalone" algorithmic interpretation of the electrochemical reaction to display a glucose reading. This is its fundamental operation. There isn't a separate "human-in-the-loop" component in the direct glucose measurement process that would necessitate a distinction here.

7. The type of ground truth used:

• For analytical performance (precision, linearity, interference), the ground truth for blood glucose concentration would be established using a laboratory reference method (e.g., YSI analyzer). This is standard for blood glucose meter validation.
• For the usability evaluation, the "ground truth" assesses whether users can successfully operate the device and interpret results, which is based on direct observation and participant feedback.

8. The sample size for the training set:

• This device is a physical blood glucose meter and test strips relying on electrochemical principles, not a machine learning or AI model that requires a "training set" in the computational sense. Therefore, the concept of a training set sample size is not applicable here.

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

• As above, the concept of a training set is not applicable.

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The ABL90 FLEX PLUS System is an in vitro diagnostic, portable, automated analyzer that quantitatively measures electrolytes (cK+, cNa+, cCa2+), glucose, and lactate in heparinized arterial and venous whole blood.

The ABL90 FLEX PLUS System is intended for use by trained technologists, nurses, physicians and therapists. It is intended for use in a laboratory environment, near patient, or point-of-care setting. These tests are only performed under a physician's order.

Potassium (cK+): Potassium measurements are used to monitor electrolyte balance in the diagnosis and treatment of disease conditions characterized by low or high blood potassium levels.

Sodium (cNa+): Sodium measurements are used in the diagnosis and treatment of aldosteronism, diabetes insipidus, adrenal hypertension, Addison's disease, delydration, inappropriate antidiuretic secretion, or other diseases involving electrolyte imbalance.

Calcium (cCa2+): Calcium measurements are used in the diagnosis and treatment of parathyroid disease, a variety of bone diseases, chronic renal disease and tetany.

Glucose (cGlu): Glucose measurements are used in the diagnosis and treatment of carbohydrate metabolism disorders including diabetes mellitus and idiopathic hypoglycemia, and of pancreatic islet cell carcinoma.

Lactate (cLac): The lactate measure the concentration of lactate. Lactate measurements are used to evaluate the acid-base status and are used in the diagnosis and treatment of lactic acidity of the blood).

The ABL90 FLEX PLUS System consists of the ABL90 FLEX PLUS analyzer, sensor cassette and solution pack consumables, and related accessories for the analyzers. The ABL90 FLEX PLUS is a portable, automated system intended for in vitro testing of samples of balanced heparinized whole blood for electrolytes (cK+, cNa*, cCa²), glucose, and lactate. The ABL90 FLEX PLUS System has an automated sample inlet mechanism, which can collect blood through two different measuring modes: the S65 syringe mode and the SP65 short probe mode.

The provided text is a 510(k) Summary for the ABL90 FLEX PLUS System, an in vitro diagnostic device. This document focuses on demonstrating substantial equivalence to a legally marketed predicate device (ABL90 FLEX) rather than proving the device meets specific acceptance criteria as might be defined for a novel AI/ML device.

Therefore, much of the requested information regarding acceptance criteria for AI/ML performance, study design (test set, ground truth establishment, expert adjudication, MRMC studies, standalone performance, training set details) is not applicable to this type of device and its regulatory submission.

The document primarily proves the analytical performance of the new device is comparable to the predicate device through various analytical studies.

Here's a breakdown of the applicable information based on the provided text, and an explanation of why other requested information is not present:

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

The document does not explicitly present "acceptance criteria" in a pass/fail table for each performance metric in the way it might for a novel AI/ML device. Instead, it presents analytical performance data (linearity, precision, detection, method comparison, interference) which is implicitly compared against pre-defined internal specifications or what is considered acceptable for the similar predicate device. The goal is to show the new device performs equivalently to the predicate.

Below is a summary of the reported device performance from the tables in the document. The "Acceptance Criteria" column cannot be fully populated as precise numerical thresholds are not explicitly stated as "acceptance criteria" in this 510(k) summary, but are rather implied by the successful demonstration of performance often within CLSI guidelines and comparable to the predicate.

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

• Test Set (for performance validation):
  • Linearity: The specific number of samples tested for linearity is not explicitly stated as 'N' values in Table 1 but ranges presented (e.g., 1.896-11.146 for cCa2+) imply a sufficient number of points across the range were used.
  • Detection (LoB, LoD, LoQ): Not explicitly stated as 'N' values in Table 2.
  • Precision (using stable, aqueous ampoule-based QC material): Varies per parameter/level, but generally 243-244 replicates (N) per parameter/level.
  • Precision (using blood): Varies per parameter/mode/interval, ranging from 2 to 202 replicates (N).
  • Method Comparison:
    • Arterial blood (S65 mode): 221-225 samples (N) across parameters.
    • Arterial blood (SP65 mode): 214-218 samples (N) across parameters.
    • Venous blood (S65 mode): 231-234 samples (N) across parameters.
    • Venous blood (SP65 mode): 219-225 samples (N) across parameters.
    • Combined (S65 mode): 436-441 samples (N) for combined arterial/venous.
    • Combined (SP65 mode): 420-425 samples (N) for combined arterial/venous.
  • Interference: "Large panel of likely interferents" for paired-difference study; dose-response studies for significant interferents. Specific sample sizes for each interferent are not detailed in the summary.
• Data Provenance: The document states that precision studies using QC material were conducted at "three external sites." Method comparison and precision studies using blood were conducted using both arterial and venous blood, and in both sample collection modes. The country of origin for the data (patients or samples) is not specified in this summary. The studies are described as "analytical performance testing," implying they are prospective or controlled laboratory studies rather than retrospective analysis of existing clinical data.

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: This device is an in vitro diagnostic (IVD) analyzer that quantitatively measures analytes. Its performance is evaluated against reference measurement procedures or highly controlled materials, not by expert interpretation of images or clinical cases requiring expert consensus or qualifications. Ground truth is established by the reference method itself or the known concentration of QC materials.

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

• Not Applicable: As this is an IVD device measuring quantitative analytes, there is no expert adjudication process in this context, unlike an AI/ML device interpreting medical images. Performance is determined by comparison to reference methods or statistical analysis against known values.

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 is an IVD analyzer, not an AI/ML device that assists human readers. Therefore, an MRMC study is not relevant to its regulatory approval process.

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

• Partially Applicable (in a different sense): The ABL90 FLEX PLUS System is a standalone automated analyzer. Its performance is measured directly (algorithm only, if you consider the device's internal measurement algorithm) against reference methods or known concentrations, without a human-in-the-loop interpretation being the primary output that's being evaluated for accuracy. The results presented (linearity, precision, method comparison) are representative of its standalone performance.

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

• Quantitative Reference Methods / Known Concentrations:
  • Linearity/Detection: Ground truth is established by preparing samples with known, precise concentrations across the measurement range, or by the inherent properties of the measurement system for LoB/LoD/LoQ.
  • Precision: Ground truth is the expected value of the quality control (QC) materials or the prepared blood samples, or simply the reproducibility of measurements on the same sample.
  • Method Comparison: Ground truth is the measurement from the legally marketed predicate device (ABL90 FLEX, specifically "ABL90 FLEX PLUS analyzer as it was designed at the time of the clearance of K160153") that the new device is being compared against. This device itself serves as the "reference method" for substantial equivalence.
  • Interference: Ground truth is the expected measurement of known samples, with and without the interferent, using a reference method, to identify if the interferent causes a clinically significant deviation.

8. The sample size for the training set

• Not Applicable (in the AI/ML sense): This document describes the analytical validation of a traditional IVD device, not an AI/ML algorithm. There is no "training set" in the machine learning sense for this type of submission. The device is a physical instrument with established chemical/electrochemical measurement principles.

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

• Not Applicable: As there is no "training set" in the AI/ML context, this question is not relevant. The device's internal parameters and calibration would be established through a manufacturing and calibration process, not through a "training" phase with a ground truth dataset in the way an AI model is trained.

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AIM is a bite block intended for use in patients 18 years and older who require supplemental oxygen and CO2 monitoring during procedures where the patient is expected to be minimally or moderately sedated. AIM is not indicated for use during procedures that are expected to require deep sedation.

AIM is a single-use, non-sterile bite block with integrated oxygen (O2) delivery and expired gas sampling tubing for patients undergoing procedures where supplemental oxygen and expired gas sampling is required expired. When paired with an oxygen supply and a capnography monitor, AIM can be left in place after the procedure to deliver oxygen and monitor CO2 levels.

AIM consists of a bite block, an attached oxygen delivery line and an attached CO2 sampling line. It delivers oxygen and samples exhaled CO2 in the oropharynx.

The provided text describes a 510(k) summary for a medical device named AIM, which is a bite block with integrated oxygen delivery and expired gas sampling tubing. The summary compares AIM to a predicate device, DualGuard™ (K140473), to demonstrate substantial equivalence.

Here's an analysis of the acceptance criteria and study proving the device meets these criteria, based on the provided document:

Acceptance Criteria and Device Performance Study for AIM

1. Table of Acceptance Criteria and the Reported Device Performance

The document describes performance tests by comparing the AIM device to its predicate, DualGuard™. The acceptance criteria appear to be equivalent or better performance than the predicate device.

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The XPER Technology PREMIUM Pro Blood Glucose Monitoring System is intended for point-of-care, in vitro diagnostic, multiple-patient use for the quantitative determination of glucose in fresh capillary whole blood samples from the fingertips in endocrinology clinic laboratories and physician office laboratories.

The system should only be used with single-use, auto-disabling lancing devices when performing a fresh capillary whole blood sample from the fingertip.

The system is not intended for the screening or diagnosis of diabetes mellitus but is indicated for use in determining dysglycemia.

The system is not intended for use on patients receiving intensive medical intervention/therapy.

The system is not intended for use in acute care, nursing facilities, skilled nursing facilities or hospital settings. The system is not intended for use on neonates.

The XPER Technology PREMIUM Pro Blood Glucose Monitoring System consists of the XPER Technology PREMIUM Pro Blood Glucose Meter, the XPER Technology PREMIUM Pro Blood Glucose Test Strips, and the TaiDoc Blood Glucose Control Solutions. This system is a multiplepatient use for the quantitative determination of glucose in capillary whole blood samples from the fingertips in endocrinology clinic laboratories and physician office laboratories as an aid in monitoring the effectiveness of glucose control. The TaiDoc Blood Glucose Control Solutions are used to check that the meter and test strips are working together properly.

Here's a breakdown of the acceptance criteria and study details for the XPER Technology PREMIUM Pro Blood Glucose Monitoring System, based on the provided FDA 510(k) summary:

Acceptance Criteria and Device Performance

The acceptance criteria are implicitly defined by the statement "all test results were within acceptance criteria" in various sections. The reported performance is the achievement of these criteria. The specific numerical targets for each criterion are not always explicitly stated (e.g., for precision, linearity, hematocrit, interference), but the document confirms that the device met these criteria.

Table of Acceptance Criteria and Reported Device Performance

Study Details

This document describes a medical device, a Blood Glucose Monitoring System, which does not utilize AI or involve human readers for image interpretation. Therefore, questions related to AI models, human reader improvement with AI assistance, expert adjudication for ground truth related to image analysis, or MRMC studies are not applicable to this device.

Here's the relevant information based on the provided text:

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

   • Clinical Accuracy (Capillary Blood): 414 patients.
     • Provenance: Clinical study conducted at 3 U.S. sites and 6 Taiwan sites. Data is prospective as it was collected during an active clinical study with patients.
   • Accuracy at Extremes: 100 samples (50 for 300 mg/dL).
     • Provenance: "Blood samples were collected and allowed to glycolyze or were spiked with high concentration glucose solution". Implies a laboratory-controlled, prospective or specially prepared sample set.

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

   • Not Applicable in the traditional sense of 'experts' interpreting data. For blood glucose monitoring systems, the "ground truth" is established by a highly accurate reference method.
   • The ground truth for the clinical and extreme glucose value studies was the YSI Model 2300 Glucose Analyzer. This is a laboratory-based, well-established, and highly accurate reference method for glucose measurement, not human experts.

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

   • Not Applicable. As ground truth is established by an automated reference analyzer (YSI-2300), there is no human interpretation or adjudication process involved in setting the ground truth for glucose values.

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:

   • Not Applicable. This is a blood glucose monitoring system, not an AI-assisted diagnostic imaging device. There are no human readers or AI assistance in the interpretation of results from this device in the same way as an imaging study.

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

   • Yes, in essence. Blood glucose meters are inherently "standalone" in their function of measuring glucose. The clinical study directly compares the device's numerical output (algorithm's result) to the YSI-2300 reference method without human interpretation of the device's output influencing the direct comparison. The "human-in-the-loop" for this device is the user taking and reading the measurement, but the performance evaluation is on the accuracy of the numerical reading itself, independent of user interpretation for the primary outcome.

6. The type of ground truth used:

   • Reference Method: The YSI Model 2300 Glucose Analyzer, a laboratory-based, highly accurate method for quantitative glucose determination. Comparisons are quantitative.

7. The sample size for the training set:

   • Not directly applicable/not explicitly stated in terms of an "AI training set." This device is a traditional electrochemical biosensor, not an AI/machine learning model that undergoes a distinct "training" phase with a large dataset in the way a deep learning algorithm would. The development and calibration of such a device involve extensive laboratory testing and optimization, which could be considered an analogous "training" or development process for its internal algorithms, but it's not described as a separate, quantifiable "training set" with ground truth in the context of AI regulatory submissions.

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

   • Not applicable in the AI context. For this type of device, ground truth for development/calibration (analogous to "training") would be established through a combination of:
     • Highly controlled laboratory experiments using reference solutions of known glucose concentrations.
     • Comparisons to established reference methods (like YSI-2300) with well-characterized samples.
     • Controlled studies to characterize and mitigate interferences (e.g., hematocrit, medications).

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RIGHTEST Blood Glucose Monitoring System Max Tel is intended to the quantitative measurement of glucose (sugar) in fresh capillary whole drawn from the fingertips, forearm, or palm. It is intended to be used by a single person and should not be shared.

RIGHTEST Blood Glucose Monitoring System Max Tel is intended for self- testing outside the body (in vitro diagnostic use) by people with diabetes at home as an aid to montor the effectiveness of diabetes control. It should not be used for the diagnosis of, or screening for diabetes or for neonatal use. Alternative site testing should be done only during steady-state times (when glucose is not changing rapidly).

The RIGHTEST Blood Glucose Monitoring System Max Tel is comprised of the RIGHTEST Meter Max Tel and the RIGHTEST Blood Glucose Test Strip Max.

RIGHTEST Blood glucose monitoring System Max Tel consists of the following devices: Blood Glucose Meter, Blood Glucose Test Strip, Control Solution, Lancing Device and Sterile Lancets. The Blood Glucose Meter, Blood Glucose Test Strips, and Lancing Device are manufactured by BIONIME Corporation.

RIGHTEST Blood Glucose Meter Max Tel, when used with the RIGHTEST Blood Glucose Test Strips Max, quantitatively measure glucose in fresh whole blood samples from capillary. The performance of RIGHTEST Blood Glucose Monitoring System Max Tel is verified by the RIGHTEST Control Solution GC700.

The glucose measurement is achieved by using the amperometric detection meth test is based on measurement of electrical current caused by the reaction of the glucose with the reagents on the electrode of the test strip. The blood sample is pulled into the tip of the test strip through capillary action. Glucose in the sample reacts with FAD-glucose dehydrogenase and the mediator. Electrons are generated, producing a current that is positive correlation to the glucose concentration in the sample. After the reaction time, the glucose concentration in the sample is displayed.

The provided FDA 510(k) summary for the RIGHTEST Blood Glucose Monitoring System Max Tel focuses on demonstrating substantial equivalence to a predicate device, as opposed to providing detailed clinical study results typical of a de novo or PMA submission. Therefore, much of the requested information regarding a comprehensive study proving acceptance criteria for an AI/device for diagnostic purposes (e.g., number of experts, MRMC studies, ground truth establishment for a training set) is not directly present in this document because it is not an AI/Software as a Medical Device (SaMD) submission for a diagnostic algorithm.

This document describes a glucose monitoring system, which is a medical device rather than an AI-powered diagnostic system that typically involves image analysis or complex algorithmic interpretations of patient data for diagnosis. The "Software Safety Analysis" refers to enabling LTE functionality and adjusting the measurement range, alongside cybersecurity considerations, not the performance of a diagnostic AI.

However, I can extract the acceptance criteria and performance as described in the document for this specific device:

Device: RIGHTEST Blood Glucose Monitoring System Max Tel
Intended Use: Quantitative measurement of glucose (sugar) in fresh capillary whole blood samples for self-testing by people with diabetes at home, as an aid to monitor the effectiveness of diabetes control.

1. Table of Acceptance Criteria and Reported Device Performance

Based on the "Discussion of Non-Clinical Tests Performed for Determination of Substantiability" (Section 8) and the "Comparison to Predicate Devices" (Section 7), the acceptance criteria are generally implied by the successful completion and compliance with relevant FDA guidelines for glucose monitoring systems. The performance is reported in terms of demonstrating compliance.

Overall Conclusion: "Results of performance evaluation of RIGHTEST Blood Glucose Monitoring System Max Tel that had no impacts to BGM measurement was conducted to support substantially equivalent to the predicate device..." |
| Measurement Range: Correct display of "Hi" or "Lo" for out-of-range results. | Hi Lo Display: "The measurement range has been adjusted, and the system displayed a notification indicating 'Hi' or 'Lo'—for results that fall outside the established range." The specific numerical range is 20 - 600 mg/dL (1.1 - 33.3 mmol/L). |
| Software Functionality and Safety:

• Successful implementation and validation of LTE functionality.
• Compliance with FCC testing.
• Compliance with FDA's cybersecurity guidance. | Software Safety Analysis: "Software adjustments were made to enable LTE functionality and adjusted the measurement range. The LTE function was validated through both FCC compliance testing and laboratory testing. As LTE functionality introduced cybersecurity considerations, we ensured compliance with the FDA's guidance on the Content of Premarket Submissions for Management of Cybersecurity in Medical Devices." |
  | Interference: Performance maintained in the presence of specified interferents. | Interference Data Points: Ascorbic Acid ≥ 3 mg/dL, Conjugated Bilirubin ≥ 30 mg/dL, Uric Acid ≥ 12 mg/dL, Xylose ≥ 8 mg/dL. (Implies performance within specification despite these levels, though the exact outcome of the testing is not described beyond listing the tested interferents) |
  | Other Functional Parameters: Measurement technology, sample type, minimum sample volume, test time, control solution compatibility, operating conditions, storage conditions, shelf life, reagent composition, power saving, coding, monitor, backlight, color, power supply, memory capacity, meter dimension, LCD display area, meter weight, data transmission. | All these parameters are listed as characteristics of the new device, implicitly meeting the predicate device's standards or being deemed acceptable (e.g., LTE network for data transmission is a new feature). |
  | General Acceptance: All laboratory studies met acceptance criteria. | "All laboratory studies that the acceptance criteria were met. Therefore, the performances from these laboratory studies were acceptable." |

Regarding the other requested points (relevant for AI/SaMD):

• 2. Sample sized used for the test set and the data provenance: Not specified in the provided document. The reference to "natural and modified blood samples" in "The Extreme Glucose Study" suggests lab-based testing, but no specific sample size or provenance is given.
• 3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. This is not an AI/diagnostic imaging device requiring expert ground truth for interpretation. Ground truth for a glucose meter is typically established by laboratory reference methods (e.g., YSI analyzer).
• 4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable. This type of adjudication is usually for subjective interpretations by multiple human readers, not for a highly objective measurement device like a glucose meter.
• 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 is not an AI system assisting human readers.
• 6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The device itself is a "standalone" measurement device. Its performance is measured directly against laboratory reference standards, but there is no "algorithm only" in the sense of an AI interpreting complex data that a human would usually interpret.
• 7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): For glucose meters, the ground truth is typically a laboratory reference method (e.g., a YSI analyzer), rather than expert consensus or pathology, as the measurement is quantitative. This is implied by the nature of the device, although not explicitly stated as "YSI" in the document.
• 8. The sample size for the training set: Not applicable. This device does not use machine learning with a distinct training set in the typical sense of an AI/ML algorithm. Its functionality is based on established electrochemical principles, not pattern recognition learned from a dataset.
• 9. How the ground truth for the training set was established: Not applicable, for the same reason as point 8.

In summary, the provided document is a 510(k) summary for a blood glucose monitoring system, emphasizing its substantial equivalence to a predicate device and compliance with general FDA guidelines for such devices. It does not contain the detailed study results and AI-specific ground truth methodologies that would be found in a submission for an AI-powered diagnostic device.

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The Sejoy Blood Glucose Monitoring System is composed of the Sejoy Blood Glucose Meter and Sejoy Blood Glucose Test Strips. The Sejoy Blood Glucose Monitoring System is intended to be used for the quantitative measurement of glucose in fresh capillary whole blood collected from the fingertip. The Sejoy Blood Glucose Monitoring System is intended for self-testing outside the body (in-vitro diagnostic use), by individuals with diabetes at home as an aid to monitor the effectiveness of diabetes control. This system is intended to be used by a single person and should not be shared. The system should not be used for the diagnosis of, or screening for diabetes or for neonatal use.

The Sejoy Advance Link Blood Glucose Monitoring System is composed of the Sejoy Advance Link Blood Glucose Meter and Sejoy Blood Glucose Test Strips. The Sejoy Advance Link 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 Sejoy Advance Link Blood Glucose Monitoring System is intended for self-testing outside the body (in-vitro diagnostic use), by individuals with diabetes at home as an aid to monitor the effectiveness of diabetes control. This system is intended to be used by a single person and should not be shared. The system should not be used for the diagnosis of, or screening for diabetes or for neonatal use.

The Sejoy Advance Link Blood Glucose Monitoring System is composed of the Sejoy Advance Link Blood Glucose Meter and Sejoy Blood Glucose Test Strips, and the Sejoy Blood Glucose Monitoring System is composed of the Sejoy Blood Glucose Meter and Sejoy Blood Glucose Test Strips. The Sejoy Blood Glucose Control Solutions, and the Sejoy Lancing Device with Sejoy disposable safety lancets (K222034, manufactured independently by Beijing Ruicheng Medical Supplies Co. Ltd. and cleared under 510(k)) are for use with the system and could sold separately.

The Sejoy Advance Link Blood Glucose Meter and Sejoy Blood Glucose Meter differ only in Bluetooth functionality which is present only in the Sejoy Advance Link Blood Glucose Meter.

The system measures glucose using amperometric technology and features glucose dehydrogenase in the test strip, interacting with glucose in the blood to produce an electrical current. This current is directly proportional to the blood glucose concentration, converted into values by the system software. The result is displayed on the meter's LCD in plasma value equivalence (mg/dL) and is automatically stored.

The provided document describes the Sejoy Blood Glucose Monitoring System and Sejoy Advance Link Blood Glucose Monitoring System and their substantial equivalence to a predicate device. Information relevant to acceptance criteria and study proving performance is extracted below.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for blood glucose monitoring systems are primarily based on accuracy compared to a lab reference method. The document specifies accuracy levels at various percentage tolerances.

| Accuracy Tolerance | Acceptance Criterion (Implicit) | Reported Device Performance (Overall) | Reported Device Performance (Glucose 250 mg/dL) |
|---|---|---|---|---|
| Within ±5% | N/A (Often implies higher percentages) | 56.8% (200/352) | 54.0% (27/50) | 60.0% (30/50) |
| Within ±10% | N/A (Often implies higher percentages) | 90.3% (318/352) | 92.0% (46/50) | 96.0% (48/50) |
| Within ±15% | N/A (Often implies higher percentages) | 98.3% (346/352) | 100.0% (50/50) | 100.0% (50/50) |
| Within ±20% | N/A (Often implies higher percentages) | 100% (352/352) | 100.0% (50/50) | 100.0% (50/50) |

Note: The document states "Sejoy Blood Glucose Monitoring System and Sejoy Advance Link Blood Glucose Monitoring System were designed and tested in accordance with FDA Guidance: Self-Monitoring Blood Glucose Test Systems for Over-the-Counter Use (September 2020)." This guidance typically sets specific accuracy criteria (e.g., within ±15% for a certain percentage of samples). While the exact numerical criteria from the FDA guidance are not explicitly stated in the provided text, the reported performance metrics clearly indicate the device's adherence to such guidelines, as implied by the phrase "sufficiently accurate."

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

• Overall Test Set Sample Size: 352 lay persons (for the user evaluation study).
• Extreme Glucose Concentrations Test Set Sample Size: 50 subjects for low blood glucose (250 mg/dL), totaling 100 subjects for this specific sub-study.
• Data Provenance: The document does not explicitly state the country of origin for the data, but it refers to "lay persons representative of the age, gender, education of the intended users in the US," suggesting the study subjects were recruited in the US. The study was a prospective user performance evaluation where subjects self-tested their capillary whole blood.

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

The ground truth was established using a laboratory reference method, the YSI 2300 STAT PLUS glucose analyzer, which is a highly accurate and standardized instrument. There is no mention of experts being used to establish the ground truth for the test set, as the YSI analyzer itself serves as the gold standard.

4. Adjudication Method for the Test Set

Not applicable. The ground truth was established by a laboratory reference instrument (YSI 2300), not by human readers requiring adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was Done, 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 or interpretation tool. The study involved users operating the device, not interpreting images with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, analytical performance testing was conducted which can be considered analogous to "standalone" performance for such a device. This included:

• Repeatability
• Intermediate precision
• Hematocrit effect
• Short sample volume
• Perturbation
• Interference
• Linearity testing

These tests evaluate the intrinsic performance of the device's measurement algorithm and hardware components, independent of human operation variability.

7. The Type of Ground Truth Used

The ground truth was established using a laboratory reference method: the Yellow Springs Instrument (YSI 2300 STAT PLUS glucose analyzer). The document specifies "capillary plasma" for the YSI 2300 reference, indicating a highly accurate and controlled measurement.

8. The Sample Size for the Training Set

The document describes performance evaluation studies (user evaluation and extreme glucose concentration studies) which are typically "test set" studies for device clearance. It does not provide information on the sample size used for the training set of the device's internal algorithms, as this detail is generally considered proprietary to the manufacturer and not typically included in a 510(k) summary unless the device heavily relies on a continuously learning AI model that requires explicit training data disclosure in the submission. For a blood glucose meter, the "training" (calibration and optimization) of its algorithms is usually done during the device's development phase rather than through a distinct "training set" in the context of machine learning.

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

Since information about a specific "training set" is not provided, the method for establishing its ground truth is also not detailed. However, for a device like a blood glucose meter, the internal algorithms and calibration are established using highly controlled laboratory experiments and reference methods (like YSI 2300) during the design and development phase to ensure accuracy across the measurement range and various physiological conditions.

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The YSI 2900C Biochemistry Analyzer is intended for use by trained medical professionals as an in vitro diagnostic device for the quantitative testing of venous whole blood samples, fingerstick capillary whole blood samples, serum and plasma in the laboratory.

For in vitro diagnostic use.

Glucose measurements from the YSI 2900C Biochemistry Analyzer are used in the diagnosis and treatment of carbohydrate metabolism disorders, including diabetes mellitus and idiopathic hypoglycemia, and of pancreatic islet cell tumors. The YSI 2900C Biochemistry Analyzer is not intended for use in the screening or quantitative analysis on neonates. The YSI 2900C Biochemistry Analyzer is not intended for point of care (POC) use.

This test is for prescription use only.

The device under review, the 2900C Biochemistry Analyzer, is a laboratory instrument and In Vitro Diagnostic Device for determining glucose in human whole blood, plasma and serum taken from venous or capillary samples. The 2900C Biochemistry Analyzer is a semi-automated electronic device that incorporates fluidics for sampling, calibrating, and flushing, a membrane-immobilized enzyme-coupled electrochemical detection system with digital electronic control and has graphical user and data interfacing. It is designed for ambient indoor use in a technical laboratory environment.

The system is not intended to be a point of care product and is intended only for professional laboratory use.

The provided text describes the 510(k) premarket notification for the YSI 2900C Biochemistry Analyzer, which is a device for quantitative testing of glucose. It aims to demonstrate substantial equivalence to a predicate device, the YSI 2300 STAT PLUS Analyzer.

Here's a breakdown of the acceptance criteria and study information, based on the provided document:

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

The document does not explicitly present a table of "acceptance criteria" alongside specific numerical "reported device performance" in the format typically seen for algorithm performance (e.g., sensitivity, specificity, AUC thresholds). Instead, the studies aim to demonstrate substantial equivalence to a predicate device. The performance metrics discussed are related to the analytical performance of a biochemistry analyzer.

However, we can extract the precision acceptance criterion and its comparison to the predicate device:

It's important to note that for other tests like Method Comparison, Linearity, Specificity/Interference, etc., the "acceptance criteria" would be met by demonstrating that the new device's performance is comparable to the predicate, often through statistical equivalence testing within defined analytical limits, rather than fixed numerical thresholds for a specific algorithm output. The document states: "The results of the performance testing confirmed that the YSI 2900C Biochemistry Analyzer demonstrates substantial equivalence to the YSI 2300 StatPlus Analyzer."

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 provides details on the types of studies performed but does not specify the sample sizes used for the test sets in any of the performance studies (Method Comparison, Precision/Reproducibility, Linearity, Specificity/Interference, etc.).

There is no information provided regarding data provenance (e.g., country of origin, retrospective or prospective nature of the samples). The samples are stated to be "human whole blood, plasma and serum taken from venous or capillary samples."

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

This section is not applicable in the context of this device. The YSI 2900C Biochemistry Analyzer is an in vitro diagnostic device that quantitatively measures glucose in biological samples. The "ground truth" for its performance is established by comparing its measurements against reference methods or the predicate device, not by expert interpretation of images or clinical data. Therefore, there's no mention of experts establishing a ground truth for a test set in the way one would for an AI-powered diagnostic imaging device.

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

This section is not applicable for this type of device. Adjudication methods like "2+1" or "3+1" are typically used in studies involving expert readers interpreting medical images or clinical data, where consensus is needed to establish a "ground truth" when individual expert opinions might differ. For a biochemistry analyzer, the validation involves analytical comparisons to reference methods or a predicate device, not human interpretation requiring adjudication.

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

This section is not applicable to this device. An MRMC study is designed to evaluate how AI assists human interpretation, typically in diagnostic imaging. The YSI 2900C Biochemistry Analyzer is a laboratory instrument that provides quantitative measurements; it does not involve human "readers" interpreting output in the same way, nor does it provide "AI assistance" for human interpretation. Its performance is evaluated analytically against established methods.

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

The device itself is a "standalone" system in its operation for measuring glucose. It performs the analysis and provides quantitative results without direct human "interpretation" of a processed image or complex data set. The performance testing described (Method Comparison, Precision, Linearity, etc.) represents the device's inherent analytical capabilities, which is analogous to "standalone" performance for an IVD. There is no "human-in-the-loop" component for the actual glucose measurement process that would affect its analytical performance.

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

The "ground truth" in these performance studies is typically established by:

• Reference Methods: Highly accurate and precise analytical methods (e.g., isotope dilution mass spectrometry) that are considered the gold standard for glucose measurement, or
• Predicate Device: For demonstrating substantial equivalence, the performance of the new device (YSI 2900C) is compared against that of the legally marketed predicate device (YSI 2300 STAT PLUS) across various analytical parameters. The predicate device's established performance serves as the comparative "truth" for demonstrating equivalence.
• Known Concentrations: For linearity and limit studies, samples with precisely known glucose concentrations are used.

The document explicitly states: "A mirror of this testing was also performed concurrently on the predicate device, the YSI 2300 STAT PLUS Biochemistry Analyzer, for demonstration of substantial equivalence." This indicates the predicate device serves as the primary comparative "ground truth" for the equivalence assessment.

8. The sample size for the training set

This section is not applicable in the context of this traditional analytical device. The YSI 2900C Biochemistry Analyzer uses an "enzyme-mediated electrochemical detection" system, not a machine learning or AI algorithm that requires a "training set" of data. Its underlying technology is based on established biochemical and electrochemical principles.

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

As there is no "training set" for an AI or machine learning algorithm in this device, this question is not applicable. The device's operational parameters and calibration are based on physical chemistry principles and factory calibration/validation, not a data-driven training process.

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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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VivaChek™ Fad Blood Glucose Monitoring System is intended to quantitatively measure the glucose concentration in fresh capillary whole blood samples drawn from the fingertips. It is intended for use by persons with diabetes at home as an aid to monitor the effectiveness of diabetes control. It is not intended for neonatal use or for the diagnosis of or screening for diabetes. This system is intended for self-testing outside the body (in vitro diagnostic use), and should only be used by a single person and should not be shared.

VivaChek™ Fad Smart Blood Glucose Monitoring System is intended to quantitatively measure the glucose concentration in fresh capillary whole blood samples drawn from the fingertips. It is intended for use by persons with diabetes at home as an aid to monitor the effectiveness of diabetes control. It is not intended for neonatal use or for the diagnosis of or screening for diabetes. This system is intended for self-testing outside the body (in vitro diagnostic use), and should only be used by a single person and should not be shared.

VivaChek™ Fad Sync Blood Glucose Monitoring System is intended to quantitatively measure the glucose concentration in fresh capillary whole blood samples drawn from the fingertips. It is intended for use by persons with diabetes at home as an aid to monitor the effectiveness of diabetes control. It is not intended for neonatal use or for the diagnosis of or screening for diabetes. This system is intended for self-testing outside the body (in vitro diagnostic use), and should only be used by a single person and should not be shared.

VivaChek™ Fad Blood Glucose Monitoring System consists of VivaChek™ Fad Blood Glucose Meter and the VivaChek™ Fad Blood Glucose Test Strips. The glucose meter and test strips are packaged separately.

VivaChek™ Fad Smart Blood Glucose Monitoring System consists of VivaChek™ Fad Smart Blood Glucose Meter and the VivaChek™ Fad Blood Glucose Test Strips. The glucose meter and test strips are packaged separately.

VivaChek™ Fad Sync Blood Glucose Monitoring System consists of VivaChek™ Fad Sync Blood Glucose Meter and the VivaChek™ Fad Blood Glucose Test Strips. The glucose meter and test strips are packaged separately.

VivaChek Fad Control Solution, VivaChek Lancing Device, VivaChek Lancets are required for use but not included in meter box or test strips box and should be purchased separately. The VivaChek Fad Control Solution is for use with the above meter and test strip as a quality control check to verify that the meter and test strip are working together properly, and that the test is performing correctly. VivaChek Lancing Device and VivaChek Lancets are used for puncturing fingertip and then user can perform qlucose test with blood sample.

VivaChek™ Fad Blood Glucose Monitoring System, VivaChek™ Fad Smart Blood Glucose Monitoring System and VivaChek™ Fad Sync Blood Glucose Monitoring System are designed to quantitatively measure the glucose concentration in fresh capillary whole blood from the fingertip. The ducose measurement is achieved by using the amperometric detection method. The test is based on measurement of electrical current caused by the reaction of the glucose with the reagents on the electrode of the test strip. The blood sample is pulled into the tip of the test strip through capillary action. Glucose in the sample reacts with glucose dehydrogenase and the mediator. Electrons are generated, producing a current that is positive correlation to the glucose concentration in the sample. After the reaction time, the glucose concentration in the sample is displayed.

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

The document mentions meeting "FDA SMBG OTC Guidance and industry standards" for clinical performance. A specific detailed table of acceptance criteria and reported performance is not explicitly provided in the excerpt. However, based on the context of Blood Glucose Monitoring Systems, the primary acceptance criteria would relate to the accuracy of glucose readings compared to a reference method. The document states that the clinical studies data showed that the clinical performance met the FDA SMBG OTC Guidance, implying the device successfully passed these criteria. Without the specific guidance document referenced, a detailed table cannot be created from this text alone.

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

The document does not explicitly state the numerical sample size used for the test set in the clinical studies. It mentions "non-professional, inexperienced lay persons" were used for user evaluations.

• Data Provenance: The studies were conducted by Vivachek Biotech (Hangzhou) Co., Ltd, located in Zhejiang, China. The document does not explicitly state if the data was retrospective or prospective, but clinical studies (user evaluations) generally imply prospective data collection in a controlled environment.

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

This information is not provided in the document. For blood glucose monitoring systems, the ground truth is typically established using a laboratory reference method (e.g., YSI analyzer), rather than expert consensus on interpretation.

4. Adjudication Method for the Test Set

This information is not provided in the document. Given that the ground truth for blood glucose is typically a laboratory reference measurement, adjudication by experts wouldn't be directly applicable in the same way it would be for image-based diagnostics.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

This is not applicable to a Blood Glucose Monitoring System. MRMC studies are relevant for AI in diagnostic imaging where human readers interpret cases. This device is a direct measurement system.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

The device itself is a standalone system for glucose measurement. The "study" here refers to the overall performance of the device in the hands of the intended users. The clinical studies (user evaluations) assess the device's performance when used by individuals (humans in the loop). The "algorithm only" concept doesn't apply as it's a physical meter and test strip system.

7. The Type of Ground Truth Used

While not explicitly stated for all studies, for blood glucose monitoring systems, the ground truth for accuracy studies is typically established using a laboratory reference method (e.g., YSI Glucose Analyzer) on venous blood samples. The document implies this by stating that clinical performance met FDA SMBG OTC Guidance, which mandates comparison to such reference methods.

8. The Sample Size for the Training Set

This information is not provided. For a physical device like a blood glucose meter, there isn't a "training set" in the same sense as machine learning algorithms. The device's calibration and performance characteristics are established during its design and manufacturing process, and then validated through laboratory and clinical studies.

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

Not applicable as there is no traditional "training set" for an AI algorithm here. The performance is validated against established reference methods and clinical guidelines.

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