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510(k) Data Aggregation
(111 days)
The Rightest Blood Glucose Monitoring System is intended for in vitro diagnostic use (outside of body). It is indicated to be used by professional healthcare personnel or people with diabetes at home to measure the glucose concentration for aiding diabetes management. The glucose concentration is measured with quantitative capillary whole blood from fingertip, palm and forearm by using Rightest Blood Glucose Monitoring System. This test device is not intended for testing neonate blood samples.
Our Blood Glucose Monitoring System consists of a Meter, Blood Glucose Test Strips, Two Control Solutions, Lancing Device and lancets. The Rightest Meter, Blood Glucose Test Strips are manufactured by BIONIME Corporation. The Rightest Meter, when used with the Rightest Test Strips, quantitatively measures glucose in fresh capillary whole blood. The performance of the Rightest Blood Glucose Monitoring System is verified by the Control Solution.
Here's an analysis of the provided text to extract the acceptance criteria and study details:
Acceptance Criteria and Device Performance
The document does not explicitly state formal "acceptance criteria" in a typical numerical or statistical format (e.g., all results within X% of reference). Instead, it relies on demonstrating substantial equivalence to a predicate device and showing suitable performance through linear regression parameters. The primary performance metric presented is the linear relationship between the device's readings and a reference method (Olympus AU2700).
Table of Performance for Rightest Blood Glucose Monitoring System, Model GM110
Test Site | Reference Test Range (mg/dL) | Number of Tests | Slope | Intercept | Correlation Coefficient (r) |
---|---|---|---|---|---|
Fingerstick | 35-586 | 164 | 0.98 | 2.13 | 0.991 |
Palmstick | 35-589 | 164 | 0.96 | 9.80 | 0.990 |
Armstick | 35-566 | 164 | 0.95 | 2.82 | 0.990 |
Interpretation of "Acceptance Criteria": The reported performance, particularly the high correlation coefficients (r > 0.99), slopes close to 1, and small intercepts demonstrate a strong linear relationship and agreement with the reference method across various alternative testing sites. This performance is implicitly presented as meeting the substantial equivalence requirements for a glucose monitoring system. The text states: "The 'Alternative Site Test' clinical evaluation shows substantial equivalence to Rightest used in finger, palm and arm position. They all have similar slope and intercept of Rightest value versus Olympus AU2700. So the result tells us Rightest blood glucose monitoring system, model GM110 is suitable to be used in fingertip, palm and forearm."
Study Details
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Sample size used for the test set and the data provenance:
- Sample Size: 164 tests for each alternative site (fingerstick, palmstick, armstick).
- Data Provenance: Not explicitly stated regarding country of origin. The study is described as "Clinical Tests Performed," implying prospective data collection for the purpose of the submission. The submitter is BIONIME CORPORATION NO 694, RENHUA ROAD, DALI CITY, TAICHUNG COUNTY, TAIWAN.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Not applicable/Not provided. The ground truth was established using a clinical chemistry analyzer (Olympus AU2700) rather than expert consensus on images or clinical assessments.
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Adjudication method for the test set:
- Not applicable/Not provided. Adjudication methods like 2+1 or 3+1 are typically used for assessing qualitative or subjective outcomes, often in imaging studies. For quantitative measurements like blood glucose, a reference standard instrument is used, and the device's readings are compared directly to it.
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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, an MRMC comparative effectiveness study was not done. This type of study is relevant for AI systems assisting human interpretation, particularly in diagnostic imaging. This submission concerns a quantitative blood glucose monitoring device.
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If a standalone (i.e. algorithm only without human-in-the loop performance) was done:
- Yes, the study describes the standalone performance of the Rightest Blood Glucose Monitoring System. The results provided (slope, intercept, r-value) directly reflect the device's accuracy against a reference method. It's a "device only" performance evaluation.
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The type of ground truth used:
- Reference Standard: The ground truth was established by comparing the device's readings to measurements from an Olympus AU2700 clinical chemistry analyzer (referred to as "Olympus-Plasma"). This is a recognized laboratory reference method for blood glucose measurement.
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The sample size for the training set:
- Not applicable/Not provided. This device is a traditional electro-chemical blood glucose meter, not an AI/machine learning algorithm that requires a separate training set. The performance is based on the inherent physical and chemical properties of the system (meter and test strips).
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How the ground truth for the training set was established:
- Not applicable. As noted above, there is no "training set" in the context of an AI/ML algorithm.
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