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510(k) Data Aggregation
(208 days)
The NoCoding1 Plus Blood Glucose Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood samples drawn from the fingertips. The NoCoding1 Plus Blood Glucose Monitoring System is intended for self testing outside the body (in vitro) by people with diabetes at home as an aid to monitor the effectiveness of diabetes control. The system is intended to be used by a single person and should not be shared. It is not intended for use on neonates and is not for the diagnosis or screening of diabetes.
The NoCoding1 Blood Glucose Test Strips are for use with the NoCoding1 Plus Blood Glucose Meters to quantitatively measure glucose in fresh capillary whole blood samples drawn from the fingertip.
The VeraSens Blood Glucose Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood samples drawn from the fingertips. The VeraSens Blood Glucose Monitoring System is intended for self testing outside the body (in vitro) by people with diabetes at home as an aid to monitor the effectiveness of diabetes control. The system is intended to be used by a single person and should not be shared. It is not intended for use on neonates and is not for the diagnosis or screening of diabetes.
The VeraSens Blood Glucose Test Strips are for use with the VeraSens Blood Glucose Meters to quantitatively measure glucose in fresh capillary whole blood samples drawn from the fingertip.
The NoCoding1 Plus BGMS and VeraSens BGMS is a derivation from the same design file as its predicate device, NoCoding1 Plus Blood Glucose Monitoring System with the addition of a Bluetooth module. This Premarket Notification (510(k) is intended to demonstrate that the candidate devices to be marketed is safe and effective as the predicate device, NoCoding1 Plus Blood Glucose Monitoring System, K160742.
The NoCoding1 Plus BGMS and VeraSens BGMS consist of a blood glucose meter, single use test strips, and control solutions with two different glucose concentrations ("Control A" and "Control B" ranges).
The NoCoding1 Plus BGMS and VeraSens BGMS is based on an electrochemical biosensor technology (electrochemical). The System measures the glucose level in whole blood samples using a small electrical current generated in the test strips.
The provided text describes the i-SENS NoCoding1 Plus Blood Glucose Monitoring System and VeraSens Blood Glucose Monitoring System. The document is a 510(k) Summary, which typically focuses on demonstrating substantial equivalence to a predicate device rather than presenting a full study with acceptance criteria and detailed performance data.
However, I can extract information related to acceptance criteria and device performance based on the type of device and the context provided. The non-clinical section states that "Verification, validation and testing activities were conducted to establish the performance, functionality characteristics of the modified devices. The device passed all of the tests based on pre-determined Pass/Fail criteria." This indicates that acceptance criteria were defined, and the device met them.
Here's a breakdown of the requested information based on the provided text:
1. A table of acceptance criteria and the reported device performance
The document does not explicitly present a table of acceptance criteria with corresponding performance data for glucose measurement accuracy. However, it implicitly refers to established "pre-determined Pass/Fail criteria" for verification, validation, and testing activities. Given the device type (blood glucose monitoring system), these criteria would typically refer to accuracy standards like those set by ISO 15197 (e.g., specific percentages of results within +/- certain mg/dL or %). The document does not provide the specific numerical acceptance criteria or the reported device performance in terms of accuracy metrics (e.g., mean absolute relative difference, percentage within limits).
The provided non-clinical summary focuses more on functional aspects related to the addition of a Bluetooth module, cleaning/disinfection, and cybersecurity.
| Acceptance Criteria Category (Implied) | Reported Device Performance (as described) |
|---|---|
| Glucose Measurement Accuracy | "Verification, validation and testing activities were conducted to establish the performance, functionality characteristics of the modified devices. The device passed all of the tests based on pre-determined Pass/Fail criteria." (Specific numerical accuracy metrics (e.g., % within +/- 15 mg/dL) are not detailed in this summary.) |
| Cleaning and Disinfection Effectiveness | "Results demonstrated complete inactivation of live virus inoculated on the materials of the meter and lancing device." |
| Durability after Cleaning/Disinfection | "260 each of pre-cleaning and disinfection cycles for meter... has no effect on the performance or the external materials of the meter and lancing device." |
| Cybersecurity (Bluetooth connection to unintended device) | "Passkey entry and short display time of showing Passkey was adopted to prevent that situation and software function test was done to verify this." "Residual risk falls from AFAP to ACC region." |
| Cybersecurity (Data transmission without encryption) | "Product design which meets Bluetooth SIG standard." "Bluetooth SIG certification was received." |
| Cybersecurity (Outside intrusion during UART communication) | "Connect with a device using the protocol designed by i-SENS, Inc." "User Manual pg. 10, 41." "Residual risk falls from AFAP to ACC region." |
| Software Function (Error of download function using UART/Bluetooth) | "Memory Test was done to verify the memory function of the meter and lower the probability of the risk." "Residual risk falls from AFAP to ACC region." |
| Electromagnetic Field Compatibility | "EMC test report, Caution indication (Manual)." "R&TTE and FCC test was done to verify that there is no problem of meter's electromagnetic field effect." "Residual risk falls from AFAP to ACC region." |
| User Errors/Unawareness (Human Factor Study) | "Human Factor Study was done to verify the user convenience of using the meter." "Residual risk still exists, it is not in the non-acceptable region." |
| User Errors/Unawareness (Bluetooth pairing difficulties) | "Use instruction in the user manual." "Residual risk falls from AFAP to ACC region." |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: This information is not explicitly provided in the summary for the core glucose measurement accuracy testing. For cleaning and disinfection, it states "260 each of pre-cleaning and disinfection cycles."
- Data Provenance: Not specified. The document is from i-SENS, Inc. in Seoul, Korea, which is the manufacturer's location, but this does not confirm the origin of patient data (if any was used for core performance studies).
- Retrospective or Prospective: Not specified.
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)
This information is not provided in the document. For blood glucose monitoring systems, ground truth is typically established by laboratory-reference methods (e.g., YSI analyzer) rather than expert consensus on images.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided and is generally not applicable for direct blood glucose measurement devices; it's more relevant to image-based diagnostic systems.
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 comparative effectiveness study was not done. This type of study is relevant to AI-assisted interpretation of medical images, which is not the function of a blood glucose monitoring system.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The device is a standalone blood glucose meter. Its performance is evaluated by comparing its readings to a reference method, not by an algorithm's performance in abstract. The "standalone" performance is the device's performance in generating a glucose reading. The document confirms "Verification, validation and testing activities were conducted to establish the performance, functionality characteristics of the modified devices," indicating standalone performance evaluation.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc)
The document does not explicitly state the ground truth method. For blood glucose monitoring systems, the ground truth for glucose measurements is almost universally established by a traceable laboratory reference method (e.g., using a YSI glucose analyzer), not expert consensus, pathology, or outcomes data.
8. The sample size for the training set
This information is not provided. As this device is based on electrochemical biosensor technology and likely uses fixed algorithms, the concept of a "training set" in the context of machine learning (as often seen with AI devices) may not directly apply or is not detailed in this type of 510(k) summary for a blood glucose meter.
9. How the ground truth for the training set was established
This information is not provided, and as noted above, the concept of a "training set" with ground truth in the AI sense might not be applicable here. If internal calibration/development involved a "training set" of samples, the ground truth would typically be established by a laboratory reference method.
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(274 days)
The NoCoding1 Plus Blood Glucose Monitoring System is intended for the quantitative measurement of glucose in fresh capillary whole blood samples drawn from the fingertip. The NoCoding1 Plus Blood Glucose Monitoring System is intended for self-testing outside the body (for in vitro diagnostic use) by people with diabetes at home as an aid to monitor the effectiveness of diabetes control. The system is intended to be used by a single person and should not be shared. It is not intended for use on neonates and is not for the diagnosis or screening of diabetes.
The NoCoding1 Blood Glucose Test Strips are for use with the NoCoding1 Plus Blood Glucose Meters to quantitatively measure glucose in fresh capillary whole blood samples drawn from the fingertip.
The NoCoding1 Glucose Control Solutions are for use with the NoCoding1 Plus Blood Glucose Meters and NoCoding1 Blood Glucose Test Strips to check that the meter and the test strips are working together properly and that the test is performing correctly.
The NoCoding1 Plus Blood Glucose Monitoring System (BGMS) consists of a blood glucose meter, single use test strips, and control solutions with two different glucose concentrations (“Control A" and "Control B" ranges). The NoCoding1 Plus BGMS is based on an electrochemical biosensor technology (electrochemical). The System measures the glucose level in whole blood samples using a small electrical current generated in the test strips.
The following items are included in the NoCoding1 Plus Blood Glucose Monitoring system:
- 1 NoCoding1 Plus Blood Glucose Meter
- 10 NoCoding1 Blood Glucose Test Strips
- 1 Lancing device
- 10 Lancets
- 1 Owner's Booklet
- 1 Quick Reference Guide
- 2 Batteries (3.0V lithium batteries)
The following items are compatible with the NoCoding1 Plus BGMS and are available separately.
NoCoding1 Glucose Control Solution (cleared in K080923)
Here's a breakdown of the acceptance criteria and study details for the NoCoding1 Plus Blood Glucose Monitoring System, based on the provided document:
Acceptance Criteria and Reported Device Performance
The document states that the NoCoding1 Plus BGMS was tested in accordance with ISO 15197, which would define the acceptance criteria for its analytical performance. While specific numerical acceptance criteria from ISO 15197 are not explicitly listed in detail for each test alongside the device's reported performance, the summary consistently states that the device met the acceptance criteria for each test. For tests where specific numerical acceptance criteria are mentioned (e.g., linearity, hematocrit effect), they are presented alongside the observed performance.
Note: The provided text refers to "Primary and Reference criteria" being met for user performance, which likely corresponds to the ISO 15197 accuracy requirements (e.g., within ±15 mg/dL or ±15%).
| Acceptance Criteria (from ISO 15197, or implied from context) | Reported Device Performance (NoCoding1 Plus BGMS) |
|---|---|
| Repeatability Test: | The pooled SD for concentration intervals 1 and 2 were 1.9 and 2.1 mg/dL, respectively (below 5.0 mg/dL). The pooled CV% for concentration intervals 3, 4, and 5 were 2.8%, 2.6%, and 3.2%, respectively (below 5.0%). All three lots met the acceptance criteria. |
| Intermediate Precision: | The pooled SD for concentration interval 1 was 1.4 mg/dL. The pooled CV for concentration intervals 2 and 3 were 3.0% and 2.4%, respectively. Met the acceptance criteria. |
| Linearity Test: | Acceptance Criteria: Within ±10 mg/dL for glucose concentrations <100 mg/dL and within 10% for glucose concentrations ≥100 mg/dL. Precision maintained under 5 mg/dL for <100 mg/dL (SD) and 5% for ≥100 mg/dL (CV). Linear correlation coefficient (r²) well above 0.98. Reported Performance: All data points were within ±10 mg/dL for <100 mg/dL and within 10% for ≥100 mg/dL. Precision was maintained under 5 mg/dL (SD) for <100 mg/dL and 5% (CV) for ≥100 mg/dL. Linear correlation coefficients (r²) for all strip lots were well above 0.98. |
| Hematocrit Effect Test: | Acceptance Criteria: Less than 10 mg/dL bias for glucose <80 mg/dL and less than 10% for glucose >100 mg/dL. Reported Performance: Biases of individual BGMS measurements from YSI were less than 10 mg/dL and 10% below 80 mg/dL and above 100 mg/dL, respectively. No significant interference within 15% to 65% hematocrit levels. |
| Interference Test: | Acceptance Criteria: No significant effect on glucose measurement from interferents. Reported Performance: The 24 interferents studied showed no effect on glucose measurement at both low and high glucose concentration intervals. |
| Altitude Test: | Acceptance Criteria: Individual results not showing significant difference (±10%) with respect to reference equipment or different altitudes. Reported Performance: Individual results did not show significant difference (±10%) with respect to the reference equipment, nor with different altitudes at all glucose concentrations. No systematic response to altitudes up to 10,000 feet (3,048m). |
| Operating Condition Test: | Acceptance Criteria: Individual meter measurements giving less than 10 mg/dL or 10% bias from YSI reference results. Reported Performance: Individual meter measurements gave less than 10 mg/dL or 10% bias from YSI reference results. Operates normally at presented conditions (6°C to 44°C and 10% to 90% RH). |
| Sample Volume Test: | Acceptance Criteria: Meter bias from YSI within acceptance criteria. Reported Performance: The smallest volume required for accurate measurement was 0.5 uL, and the meter bias from YSI was all within the acceptance criteria. |
| User Performance (Accuracy): | Acceptance Criteria (implied from meeting "Primary and Reference criteria," likely based on ISO 15197): - For glucose concentration < 75 mg/dL: likely a high percentage within ±5 mg/dL, ±10 mg/dL, etc. - For glucose concentration ≥ 75 mg/dL: likely a high percentage within ±5%, ±10%, etc. Reported Performance: - Glucose < 75 mg/dL (n=41): 61.0% within ±5 mg/dL, 97.6% within ±10 mg/dL, 100% within ±15 mg/dL. - Glucose ≥ 75 mg/dL (n=330): 70.0% within ±5%, 96.1% within ±10%, 100% within ±15%, 100% within ±20%. |
| User Performance (Usability): | Acceptance Criteria: Users find the device easy to follow and use. Reported Performance: 100% of data met Primary and Reference criteria. More than 100% of subjects gave scores above 3 (neither easy nor difficult) on the questionnaire, confirming the User's Guide is easy to follow and the device is easy to use. |
Study Information:
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Sample sizes used for the test set and the data provenance:
- Analytical Performance Tests (Repeatability, Intermediate Precision, Linearity, Hematocrit, Interference, Altitude, Operating Condition, Sample Volume): The specific number of individual samples (e.g., blood solutions) tested varies per experiment. For example, linearity involved 9 concentration intervals, tested once with 5 meters per lot across 3 lots. Hematocrit effect involved 3 glucose intervals x 7 hematocrit levels, tested for 3 lots of strips.
- User Performance Study:
- Test Participants: 371 diabetic and pre-diabetic individuals.
- Provenance: The study was conducted at "three clinical sites," implying a prospective study. The country of origin is not explicitly stated for the participant data, but the manufacturer is based in Seoul, Korea, so it's likely Korean or a similar demographic.
- Naive Subjects: Approximately 10% to 15% were "naive subjects" (never exposed to using BGMS on their own).
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- For the analytical performance tests (linearity, hematocrit, interference, altitude, operating condition, sample volume), the ground truth was established by a Yellow Springs Instrument (YSI), which is a laboratory comparator method known for its accuracy in glucose measurement. This is a highly accurate chemical analysis method, not an expert human interpretation.
- For the user performance study, the blood glucose measurements from the NoCoding1 Plus BGMS were compared against an unstated "reference" (likely also a YSI or similar high-accuracy lab method, as implied by other tests and typical BGMS validation). The ground truth was based on these objective reference measurements, not expert human assessment of BGMS readings.
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Adjudication method for the test set:
- Not applicable in the traditional sense of image interpretation or clinical diagnosis. The tests involved objective analytical measurements (device reading vs. YSI reference) and user questionnaire responses. There was no mention of human expert adjudication of results for accuracy.
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If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
- No, a multi-reader multi-case (MRMC) comparative effectiveness study in the context of diagnostic imaging (which often involves human reader performance with and without AI assistance) was not done. This device is a Blood Glucose Monitoring System, which does not involve human interpretation of complex data for diagnosis in the same way imaging AI does. The user performance study involved users operating the device and comparing its readings to a reference, not human readers interpreting device-generated "cases."
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Yes, the majority of the analytical performance tests (Repeatability, Intermediate Precision, Linearity, Hematocrit Effect, Interference, Altitude, Operating Condition, Sample Volume Tests) represent standalone performance of the device (meter + strip) without human-in-the-loop decision-making. The measurements are automated, and the results are compared against a laboratory reference standard (YSI).
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The type of ground truth used:
- Laboratory Reference Standard: The primary ground truth for all analytical accuracy assessments (Linearity, Hematocrit, Interference, Altitude, Operating Condition, Sample Volume, and the underlying accuracy of Repeatability and Intermediate Precision) was a Yellow Springs Instrument (YSI), described as a "laboratory comparator method."
- For the user performance study, the device's measurements were compared against an unstated "reference" which, given the context, is also likely a YSI or similar high-accuracy laboratory method.
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The sample size for the training set:
- The document describes performance testing for regulatory submission (510(k)) and does not mention a training set in the context of machine learning or AI. This is a traditional medical device (blood glucose meter) validation, not an AI/ML-based device that typically requires a large training dataset.
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How the ground truth for the training set was established:
- Not applicable, as no training set for an AI/ML algorithm was mentioned or appears to be part of this device's validation.
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