(24 days)
The intended use of ACS LH2 is for the quantitative determination of LH in serum using the Ciba Corning Automated Chemiluminescence Systems.
The Ciba Corning ASC LH2 assay is a two-site chemilumometric (sandwhich) assay which uses constant amounts of two antibodies that have specificity for the intact LH molecule. The first antibody or Lite Reagent is a monoclonal mouse anti-LH antibody labeled with acridinium ester. The second antibody or solid phase is a monoclonal mouse anti-LH antibody covalently coupled to paramagnetic particles. A direct relationship exists between the LH in a sample and the relative light units (RLUs) detected by the ACS:180 systems.
The provided text describes a medical device called the ACS LH2 Immunoassay but does not contain information typically associated with acceptance criteria and study designs for AI-powered devices or complex imaging analysis. Instead, it focuses on the analytical performance characteristics of a laboratory immunoassay.
Therefore, many of the requested categories for AI/ML device studies cannot be answered directly from the provided text.
Here's an attempt to extract and interpret the available information in the context of the questions asked, acknowledging the limitations:
1. Table of Acceptance Criteria and Reported Device Performance
| Performance Characteristic | Acceptance Criteria (Implied/Standard) | Reported Device Performance |
|---|---|---|
| Sensitivity (Detection) | Minimum Detectable Concentration (MDC) is acceptably low for clinical use. | 0.07 mIU/mL |
| Accuracy (Correlation) | Strong correlation to a reference method (e.g., r > 0.95, slope close to 1, intercept close to 0) | ACS LH2 = 0.93 (reference method) + 0.87; r = 0.97 |
| Precision (Reproducibility) | Acceptable coefficient of variation (CV) for clinical laboratory assays (e.g., typically 0.95"). Instead, it presents the results, implying that these results met internal or regulatory expectations for analytical performance for this type of assay. For an immunoassay, the reported values are generally considered excellent. |
2. Sample size used for the test set and the data provenance
- Sample Size for Test Set: 689 samples were used for the accuracy assessment against a reference method.
- Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). Since this is a lab assay, samples would likely be from clinical specimens.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- This question is not applicable in the context of this immunoassay. The "ground truth" for an immunoassay is typically established by a reference method assay, which is itself a laboratory test, not human expert consensus on an image or clinical observation.
4. Adjudication method for the test set
- Not applicable. The "ground truth" is a measurement from a reference assay, not a subjective interpretation 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
- No. This is an automated immunoassay, not an AI-powered diagnostic imaging or decision support tool that uses human readers.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Yes, in a sense. The performance data (sensitivity, accuracy, precision) describes the standalone performance of the ACS LH2 immunoassay system without human interpretation affecting the measurement itself. A human will interpret the final numerical result, but the device's performance characteristics are measured intrinsically.
7. The type of ground truth used
- Reference Method Assay: The accuracy was determined by comparing the ACS LH2 assay results to a "reference method assay" for LH. The specific nature of this reference method is not detailed but implies a well-established and validated laboratory procedure for LH quantification.
8. The sample size for the training set
- Not explicitly stated. For an immunoassay, "training set" doesn't strictly apply in the same way it does for machine learning models. Instead, the assay is developed and optimized using various reagents, calibrators, and internal validation samples. The 689 samples mentioned appear to be for validation/testing of the developed assay's performance rather than training a model.
9. How the ground truth for the training set was established
- Not applicable in the AI/ML context. For an immunoassay, development and optimization involve extensive analytical testing to ensure reagent stability, calibration linearity, matrix effects, etc., which is a different process than establishing "ground truth" for a training set in AI/ML.
§ 862.1485 Luteinizing hormone test system.
(a)
Identification. A luteinizing hormone test system is a device intended to measure luteinizing hormone in serum and urine. Luteinizing hormone measurements are used in the diagnosis and treatment of gonadal dysfunction.(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.