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510(k) Data Aggregation
(78 days)
The CareSens N Meter is used for the quantitative measurement of glucose level in capillary whole blood as an aid in monitoring the effectiveness of diabetes management at home or in clinical settings. CareSens N Blood Glucose System should be used only for testing outside the body (in vitro diagnostic use only). Do not use the system for the diagnosis or screening of diabetes. Testing sites include the traditional fingertip testing along with alternate sites testing on forearm, palm, thigh and calf.
CareSens N Test Strip is used with the CareSens N Blood Glucose Meter for quantitatively measuring glucose in capillary whole blood. The CareSens N Test Strip is intended for selftesting outside the body (in vitro diagnostic use only). Do not use the system for the diagnosis of diabetes without the guidance of healthcare professional. Testing sites include the traditional fingertip testing along with alternate sites testing on forearm, palm, thigh and calf.
CareSens Control A&B Solutions are a red liquid to check that both the meters and test strips are working together properly. It contains a known range of glucose as written on the bottle.
CareSens N Blood Glucose Monitoring System ("CareSens N BGMS") is an in vitro diagnostic device designed to measure the concentration of glucose in capillary whole blood with CareSens N Test Strips. The CareSens N model consists of the CareSens N meter (Model GM505IA, GM505IB, GM505IC: IA, IB and IC indicates the color of the devices, respectively, black, white, and light blue.), CareSens N test strips, and CareSens control solutions for two different glucose concentration ranges (called "Normal" and "Middle" ranges), lancing device, lancets, user manual, quick reference guide and a logbook.
The provided document describes the CareSens N Blood Glucose Monitoring System, a modification of the previously cleared CareSens Blood Glucose Monitoring System. The modifications include automatic code identification, alarms, and post-meal flagging. The document presents performance evaluation summaries for both the original and modified features.
1. A table of acceptance criteria and the reported device performance
| Test | Pre-determined Acceptance Criteria | Reported Device Performance |
|---|---|---|
| Performance Evaluation (Original Features) | ||
| PE-01 Repeatability Test | <100 mg/dL: SD<7.7 mg/dL; ≥100 mg/dL: CV<7.5% | Satisfactory |
| PE-02 Intermediate Precision test | <100 mg/dL: SD<7.7 mg/dL; ≥100 mg/dL: CV<7.5% | Satisfactory |
| PE-03 Linearity Study | Linear response within 20~600mg/dL | Satisfactory |
| PE-05 System Accuracy Test (CareSens N vs. YSI) | <75 mg/dL: within ±15 mg/dL; ≥75mg/dL: within ± 20% | Satisfactory |
| PE-06 Hematocrit Effect Test | Hct range 20-60%: Bias within ±15% | Satisfactory |
| PE-07 Interference Test | Deviations are within ±15% of the measurement for samples with no interferent. | Satisfactory |
| PE-08 Substantial Equivalence | Distribution of test results in A-region of the Error Grid is over 95%. | Satisfactory |
| PE-09 Consumer Study | Distribution of test results in A-region of the Error Grid is over 95%. | Satisfactory |
| PE-10 Point-of-Care (POC) Study | Distribution of test results in A-region of the Error Grid is over 95%. | Satisfactory |
| PE-11 Temperature Study | Temp. range 10-40°C: Bias within ±10% | Satisfactory |
| PE-12 Humidity Study | Humidity range 10-90%: Bias within ±10% | Satisfactory |
| PE-13 Altitude Test | Distribution of test results in A-region of the Error Grid is over 95%. | Satisfactory |
| PE-14 Alternate site Study | Distribution of test results in A-region of the Error Grid is over 95%. | Satisfactory |
| PE-15 Drop Test | Height 0.5, 1.0, 1.5m: Acceptance within ±5 mg/dL | Satisfactory |
| PE-16 Vibration Test | RPM (50~60Hz), 300, 600, 1200: Acceptance within ±5 mg/dL | Satisfactory |
| Validation Activities for Modified Features | ||
| Code Identification Test | 100% correct recognition of 15 types of code marks printed on the backside of the strip. | Satisfactory |
| Test of self-diagnosis of code identification | The meter should recognize any malfunction in the code-reading sensors. If the code recognition sensor is faulty, meter should detect the malfunction and display Er6 message. | Satisfactory |
| Alarm Test | The meter should alarm at preset times within ± 1 min. | Satisfactory |
| Time Test | The meter clock should display correct time within ± 1 min after an extended period of observation (120 hours). | Satisfactory |
| Data Average Test | The averages (for 14-day, and before and after meal) calculated by meter software should be same as those calculated manually with spreadsheet. | Satisfactory |
| ADC Function Test | Within 2152 ~ 2406 (12bit ADC) | Satisfactory |
| Memory Test | All test results saved on meter memory (as many as 250 data) should exactly match the manually recorded data. | Satisfactory |
| Electromagnetic Compatibility Report | Should meet the EMC test regulations. | Satisfactory |
| Electrical Safety Report | Should comply with the test regulations. | Satisfactory |
2. Sample sizes used for the test set and the data provenance
The document does not explicitly state the sample sizes used for each specific test in the performance evaluation section (PE-01 to PE-17). It refers to the report numbers PE-01 to PE-17 from the unmodified device (K080923) and states that the methods used for these tests can be found in that prior application. The actual reports for these tests repeated for CareSens N are not included in this submission. For the modified features, such as the Code Identification Test, the acceptance criterion mentions "15 types of code marks," but the specific sample size of strips tested is not provided.
The provenance of the data (e.g., country of origin, retrospective or prospective) is not explicitly stated for these studies. However, the submitter, i-SENS, Inc., is based in Seoul, Korea, suggesting the studies likely originated from there. The studies appear to be prospective performance evaluations.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
The document does not provide details on the number or qualifications of experts used to establish ground truth for the various tests. For the System Accuracy Test (PE-05), it compares the CareSens N to a YSI (likely a YSI glucose analyzer, which is a laboratory reference method), implying the YSI results serve as the ground truth. Similarly, for the "Substantial Equivalence," "Consumer Study," and "Point-of-Care (POC) Study," the ground truth involves the "A-region of the Error Grid," which is a clinically accepted method for evaluating glucose meter accuracy, typically against a reference method (like YSI).
4. Adjudication method for the test set
The document does not describe any specific adjudication methods, such as 2+1 or 3+1, for the test sets. For accuracy-related studies like System Accuracy, the comparison is directly against a reference method (YSI), which implies no human adjudication beyond the reference measurement itself.
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. The device under review is a blood glucose monitoring system, not an AI-assisted diagnostic imaging or interpretation device that would involve "human readers" in the context of an MRMC study.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done
This concept is not directly applicable in the same way it would be for an AI algorithm interpreting an image. The CareSens N Blood Glucose Monitoring System inherently performs its measurement automatically (algorithm only) without human interpretation of the glucose value by the device itself. Human interaction is primarily for applying the blood sample and reading the displayed result. The "System Accuracy Test" (PE-05) essentially represents a standalone performance evaluation against a reference standard. The new features like automatic code identification are also standalone functions of the device.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The primary type of ground truth used for accuracy and precision studies (e.g., PE-01, PE-02, PE-05) is comparison against a laboratory reference method, specifically implied by the "CareSens N vs. YSI" test (PE-05). YSI glucose analyzers are widely considered a gold standard for glucose measurement in clinical settings. For the linearity study, known glucose concentrations would be used. For the functional tests of modified features (e.g., code identification, alarms, memory), the ground truth is established by design specifications and manual verification of expected behavior.
8. The sample size for the training set
The document does not explicitly mention a "training set" in the context of machine learning. Blood glucose monitoring systems typically do not involve machine learning models that require distinct training sets in the way AI algorithms do. Their performance is based on electrochemical principles and calibration, not learned patterns from data.
9. How the ground truth for the training set was established
As there is no explicit mention of a training set for a machine learning model, this question is not applicable. The 'training' for such a device involves factory calibration and quality control procedures using known glucose concentrations, rather than a data-driven training set.
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