(214 days)
The Poly-Chem 90 Direct HDL-Cholesterol test system is an in vitro diagnostic procedure intended to measure high density lipoproteins quantitatively in human serum on the Poly-Chem 90 analyzer. HDL Cholesterol results are used in the diagnosis and treatment of lipid disorders (such as diabetes mellitus), atherosclerosis and various other liver and renal diseases, and for the assessment for the risk of developing cardiovascular disease.
The Poly-Chem 90 Direct LDL-Cholesterol test system is an in vitro diagnostic procedure intended to measure low density lipoprotens quantitatively in human serum on the Poly-Chem 90 analyzer. LDL Cholesterol results are used in the diagnosis and treatment of lipid disorders (such as diabetes mellitus), atherosclerosis and various other liver and renal diseases, and for the assessment for the risk of developing cardiovascular disease.
The Poly-Chem 90 Cholesterol test system is an in vitro diagnostic procedure intended to measure cholesterol quantitatively in human serum on the Poly-Chem 90 analyzer. Cholesterol measurements are used in the diagnosis and treatment of lipid disorders, lipoprotein metabolism disorders and atherosclerosis.
The Poly-Chem 90 Triglycerides test system is an in vitro diagnostic procedure intended to measure triglyceride quantitatively in human serum on the Poly-Chem 90 analyzer. Triglycerides measurements are used in the diagnosis and treatment of disease involving lipid metabolism and various endocrine disorders e.g. diabetes mellitus, nephrosis and liver obstruction.
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This document is a 510(k) premarket notification from the FDA for an in vitro diagnostic device (IVD) called "Poly-Chem 90 Direct HDL-Cholesterol, Direct LDL-Cholesterol, Cholesterol and Triglycerides tests."
It is important to note that a 510(k) notification primarily focuses on demonstrating substantial equivalence to a legally marketed predicate device. This typically involves performance data, but it does not usually include the level of detail regarding acceptance criteria, study design, and ground truth establishment that would be found in a full efficacy study for a novel device or a clinical trial for an AI/ML-based device.
The document does not contain the detailed study information required to fully answer the request, particularly regarding acceptance criteria and the specifics of a study proving the device meets them in the context of an AI/ML device. The device described here is a chemical assay kit, not an AI/ML-based diagnostic.
Therefore, many of the requested fields cannot be populated from the provided text.
Here's an attempt to answer based on the available information, with clear indications of what is not present:
1. A table of acceptance criteria and the reported device performance
This information is not present in the provided document. The 510(k) summary (which is not provided here, only the decision letter and indications for use) would typically contain performance characteristics like precision, accuracy, linearity, and interference studies compared to a predicate device. Acceptance criteria for these metrics would have been established by the manufacturer and accepted by the FDA for the substantial equivalence determination.
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 present in the provided document. For an IVD, the sample size would typically refer to the number of patient samples tested. The provenance and study type are also not mentioned.
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/relevant for this type of chemical IVD and is not present in the document. Ground truth for chemical assays like cholesterol levels is established through reference methods (e.g., gas chromatography-mass spectrometry, ultracentrifugation) or comparison to well-established, previously validated commercial assays, not typically by expert adjudication of images or clinical cases.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable/relevant for this type of chemical IVD and is not present in the document. Adjudication methods like 2+1 are used for interpreting qualitative or subjective data, often in imaging or pathology.
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 information is not applicable/relevant for this type of chemical IVD and is not present in the document. MRMC studies are used for evaluating diagnostic performance of systems involving human interpretation, often with AI assistance, which is not the case here.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable/relevant for this type of chemical IVD and is not present in the document. This concept applies to AI/ML algorithms, not to a chemical assay. The Poly-Chem 90 operates as a standalone analyzer for measuring these analytes.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
For this type of chemical IVD, the ground truth would typically be established through:
- Reference methods: Highly accurate and precise laboratory methods (e.g., GC-MS for cholesterol, ultracentrifugation for lipoproteins) used to assign true values to samples.
- Comparison to a legally marketed predicate device: The submitted 510(k) is based on demonstrating substantial equivalence to existing devices. Therefore, the predicate device's performance would serve as a de facto "ground truth" for comparison, provided the predicate itself was rigorously validated.
The specific ground truth method used is not detailed in this document.
8. The sample size for the training set
This information is not applicable/relevant as this is not an AI/ML device with a training set in the typical sense. For a chemical IVD, "training" might refer to calibration procedures, which involve a very small set of known standards. This information is not present in the document.
9. How the ground truth for the training set was established
This information is not applicable/relevant for the reasons stated above (not an AI/ML device). If considering "training" as calibration, the "ground truth" for calibration samples would be established by preparing precise concentrations of the analyte using primary reference materials. This information is not present in the document.
Summary of what the document DOES tell us:
The document is an FDA 510(k) clearance letter for the "Poly-Chem 90 Direct HDL-Cholesterol, Direct LDL-Cholesterol, Cholesterol and Triglycerides tests." This device is an in vitro diagnostic procedure intended to quantitatively measure these lipids in human serum on the Poly-Chem 90 analyzer.
- Indications for Use: The document clearly outlines the specific medical conditions for which each test's results are used (e.g., diagnosis and treatment of lipid disorders, assessment of cardiovascular disease risk).
- Regulatory Classification: Class I, falling under specific regulations for lipoprotein test systems.
- Device Type: This is a chemical assay kit designed to measure specific biomolecules in a laboratory setting, not an AI/ML-based diagnostic.
Therefore, the detailed questions about AI-specific study methodologies (MRMC, standalone AI performance, expert adjudication, training/test sets for algorithms, etc.) are fundamentally misaligned with the nature of the device described in the provided text.
§ 862.1475 Lipoprotein test system.
(a)
Identification. A lipoprotein test system is a device intended to measure lipoprotein in serum and plasma. Lipoprotein measurements are used in the diagnosis and treatment of lipid disorders (such as diabetes mellitus), atherosclerosis, and various liver and renal diseases.(b)
Classification. Class I (general controls). The device is exempt from the premarket notification procedures in subpart E of part 807 of this chapter subject to § 862.9.