(110 days)
This product permits the quantitative in vitro diagnostic determination of Immunoglobulin M in serum and plasma on the ILab Clinical Chemistry System by turbidimetric immunoassay method. Measurement of IgM aids in the diagnosis of abnormal protein metabolism and the body's lack of ability to resist infectious agents.
quantex IgM: 8 x 6 mL anti-human IgM P/N 3000-22135; 2 x 100 mL Buffer P/N 3000-22130
This document is a 510(k) summary for a medical device called "quantex IgM" which is used to measure Immunoglobulin M (IgM) levels. It is a submission to the FDA for market clearance.
Here's an analysis of the provided information, framed as acceptance criteria and study details:
1. A table of acceptance criteria and the reported device performance
| Acceptance Criteria (Implied) | Reported Device Performance |
|---|---|
| Substantial equivalence in performance to predicate device (IL Test™ IgM) | Correlation (r) of 0.9912 between quantex IgM and IL Test™ IgM |
Explanation of Implied Acceptance Criteria: The document doesn't explicitly state numerical acceptance criteria in the format of "Device must achieve X performance metric Y." Instead, the core acceptance criterion for a 510(k) submission is to demonstrate "substantial equivalence" to a legally marketed predicate device. The performance data provided is intended to prove this substantial equivalence. The correlation coefficient (r = 0.9912) is the key metric presented to support this claim for the "quantex IgM" device compared to the "IL Test™ IgM."
2. Sample sized used for the test set and the data provenance
- Sample Size for Test Set: 48 serum samples
- Data Provenance: Not explicitly stated (e.g., country of origin, retrospective or prospective). It is described as a "comparative performance study."
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- This information is not applicable/not provided for this type of device and study. The "ground truth" in this context is the measurement obtained from the predicate device (IL Test™ IgM) and the quantex IgM device itself. There isn't an "expert" interpreting images or making a diagnosis that requires consensus. The measurements are quantitative.
4. Adjudication method for the test set
- This information is not applicable/not provided. Adjudication methods (like 2+1, 3+1) are typically used when multiple experts are interpreting complex data (e.g., medical images) and need to reach a consensus. For a quantitative measurement device, the "truth" is the measured value itself, and the comparison is statistical.
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/not provided. An MRMC study assesses the impact of a device (often AI-powered) on human reader performance (e.g., dermatologists reading scans). This submission is for an in vitro diagnostic (IVD) device that measures a biomarker. There are no "human readers" interpreting the output in a diagnostic sense that would be assisted by AI in this context.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Yes, this study represents a standalone performance evaluation. The "quantex IgM" device (essentially an automated analyzer with its reagents) is being compared directly to another standalone device ("IL Test™ IgM") based on their quantitative measurements of IgM. There's no human "in the loop" making primary interpretations that the device is assisting; the device itself is performing the measurement.
7. The type of ground truth used
- The "ground truth" in this comparative study is the measurements obtained from the predicate device (IL Test™ IgM). The goal is to show that the new device (quantex IgM) produces results that are substantially in agreement with the established and already-cleared predicate device.
8. The sample size for the training set
- This information is not provided. For an IVD device like this, there isn't typically a "training set" in the machine learning sense. The device's calibration and internal algorithms are developed by the manufacturer, but the 510(k) submission describes a verification/validation study comparing performance to a predicate, not the internal development or training of the device's measurement method itself.
9. How the ground truth for the training set was established
- This information is not applicable/not provided as there is no mention of a "training set" in this context for this 510(k) summary.
§ 866.5550 Immunoglobulin (light chain specific) immunological test system.
(a)
Identification. An immunoglobulin (light chain specific) immunological test system is a device that consists of the reagents used to measure by immunochemical techniques both kappa and lambda types of light chain portions of immunoglobulin molecules in serum, other body fluids, and tissues. In some disease states, an excess of light chains are produced by the antibody-forming cells. These free light chains, unassociated with gamma globulin molecules, can be found in a patient's body fluids and tissues. Measurement of the various amounts of the different types of light chains aids in the diagnosis of multiple myeloma (cancer of antibody-forming cells), lymphocytic neoplasms (cancer of lymphoid tissue), Waldenstrom's macroglobulinemia (increased production of large immunoglobulins), and connective tissue diseases such as rheumatoid arthritis or systemic lupus erythematosus.(b)
Classification. Class II (performance standards).