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This product is to be used in a diagnostic laboratory setting, by qualified laboratory technologists, for the quantitative determination of amylase in human serum. It is intended for in vitro diagnostic use only. The determination of amylase in serum is most commonly performed for the diagnosis and treatment of diseases of the pancreas.

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The document provided is a premarket notification (510(k)) letter from the FDA to Pointe Scientific, Inc. regarding their Amylase EPS-G7 (Liquid) Reagent Set. This type of document declares "substantial equivalence" to a predicate device, which allows the product to be marketed, but does not typically include detailed studies proving performance against acceptance criteria in the way a clinical trial for a novel AI device would.

Therefore, many of the specific details requested in the prompt, such as sample sizes for test and training sets, expert qualifications for ground truth, adjudication methods, or MRMC studies, are not applicable to this 510(k) submission for an in vitro diagnostic reagent kit.

However, I can extract the relevant information about the device and its intended use, and explain why other sections are not present:

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

This document (a 510(k) clearance letter) does not typically contain a table of detailed performance characteristics and acceptance criteria in the way a clinical study report for an AI device might. For in-vitro diagnostic products like this, the demonstration of "substantial equivalence" to a legally marketed predicate device is the primary regulatory hurdle. This means the device is shown to perform as well as, or comparably to, an existing device on the market.

While the letter doesn't explicitly state "acceptance criteria," the intended performance of the device is for the "quantitative determination of amylase in human serum" for the "diagnosis and treatment of diseases of the pancreas." Substantial equivalence implies that its performance (e.g., sensitivity, specificity, accuracy, precision, linearity, interfering substances) is comparable to, and not worse than, the predicate device.

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

This information is not provided in the 510(k) clearance letter. For in vitro diagnostic reagents, performance studies are conducted, but their detailed results (including sample sizes, study design, and data provenance) are typically submitted to the FDA in a separate dossier and summarized or referenced in the 510(k) submission, rather than being fully reproduced in the publicly available clearance letter.

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 applicable/provided in this context. For a reagent test determining a quantitative analyte (amylase), the "ground truth" is typically established by reference methods, standard assays, or certified reference materials, not by expert consensus in the way a diagnostic imaging interpretation would be.

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

This information is not applicable/provided. Adjudication methods are relevant for subjective interpretations (like radiology reads) where multiple experts might disagree. For quantitative assays, the "ground truth" is determined by objective laboratory measurements, not expert consensus 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 is not applicable. This device is a reagent set for laboratory testing, not an AI-assisted diagnostic tool that aids human readers. Therefore, an MRMC study comparing human performance with and without AI assistance is irrelevant.

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

This is not applicable. This is a laboratory reagent kit, not an algorithm. Its performance is inherent to the chemical reaction and analytical equipment, not an AI algorithm.

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

For an amylase reagent test, the "ground truth" would typically be established through:

• Reference methods: Highly accurate and validated analytical methods.
• Standardized calibrators: Materials with known, certified concentrations of amylase.
• Interlaboratory comparisons: Performance against other established and trusted assays.

The specific type of ground truth used is not detailed in this 510(k) clearance letter.

8. The sample size for the training set

This information is not applicable/provided. This device is a chemical reagent, not a machine learning model, so there is no "training set" in the AI sense. Performance validation involves testing the reagent's characteristics (e.g., linearity, precision, accuracy, reproducibility) across a range of samples and conditions, but this is distinct from training an AI model.

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

This information is not applicable/provided for the reasons stated in point 8.

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