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UniCAP Gliadin IgA/IgG ImmunoCAP™ is a device for the in vitro semi-quantitative measurement of IgA or IgG antibodies specific for gliadin in human serum. UniCAP Gliadin IgA/IgG ImmunoCAP is intended to be used with the instrument UniCAP together with reagents as stated in the Directions for Use provided with UniCAP Specific IgA/IgG. It is intended for in vitro diagnostic use as an aid in the diagnosis of patients with celiac disease.

UniCAP Specific IgA/IgG is an in vitro test system for the quantitative measurement of antigen specific IgA/IgG antibodies. The corresponding antigen for the specific antibody to be measured by UniCAP Specific IgA/IgG is bound to the Antigen ImmunoCAP solid phase component of the UniCAP Specific IgA/IgG system. UniCAP Specific IgA/IgG assay is to be used with the instrument UniCAP. It is intended for in vitro diagnostic use in conjunction with other clinical findings, and is to be used in clinical laboratories, as well as physician office laboratories.

UniCAP Immunodiagnostic System is a fully integrated and automated system for immunodiagnostic testing. UniCAP System is comprised of Instruments (UniCAP 100 Analyzer, Test System Modules and Assay Products (Fluororenzymeimmunoassays for the measurement of IgE, IgA), ImmunoCAPTM Antigens (solid phase components which contain the specific antigens to be measured), and Software Accessories.

UniCAP 100 Analyzer is designed to handle all steps from sample and reagents handling to processing of results. Reagents, requests, samples and ImmunoCAP are loaded into the instrument and the process, which takes 2.5 hours is started. A laboratory report is automatically printed when the process is ended.

UniCAP 100 can store a calibration curve to be used for up to one month. After an initial calibration curve is accepted by the software, subsequent assay runs may use the stored calibration curve for calculation of results. In these runs, Curve Controls are included to validate that the run is on the same response level as the stored curve. Limits for the response of the Curve Controls are defined in the UniCAP 100 Operator and Panel Software.

UniCAP® 100 RM External Software is intended to be used with a Windowsbased PC operating up to five UniCAP 100 instruments. The external software creates requests and assay runs, retrieves the test results from the instrument, and prints reports. It can also import requests from, and export requests to, a connected mainframe computer or network server.

UniCAP Specific IgA is a fluoroenzymeimmunoassay for the quantitative measurement of antigen specific IgA antibodies. The corresponding antigen for the specific antibody to be measured by UniCAP Specific IgA is bound to the Antigen ImmunoCAPTM solid phase component. Specific IgA antibodies in the patient serum or plasma specimen react with the antigens of interest, in this submission. Gliadin, which are covalently coupled to ImmunoCAP.

UniCAP Specific IgG is a fluoroenzymeimmunoassay for the quantitative measurement of antigen specific IgG antibodies. The corresponding antigen for the specific antibody to be measured by UniCAP Specific IgG is bound to the Antigen ImmunoCAP™ solid phase component. Specific IgG antibodies in the patient serum or plasma specimen react with the antigens of interest, in this submission, Gliadin, which are covalently coupled to ImmunoCAP.

Here's an analysis of the provided text to fulfill your request:

1. Acceptance Criteria and Reported Device Performance:

The document describes a comparison study against predicate devices to establish substantial equivalence. The acceptance criterion appears to be a certain level of "total agreement" with the predicate devices.

2. Sample Size Used for the Test Set and Data Provenance:

• Sample Size (Test Set):
  • 98 IgA positive and negative serum samples
  • 99 IgG positive and negative serum samples
• Data Provenance: The document states "serum samples were collected," but does not specify the country of origin. It is a retrospective study as samples were "collected" and then analyzed.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Their Qualifications:

The document does not explicitly mention the number of experts or their qualifications used to establish ground truth for the test set. Instead, the study relies on the performance of the legally marketed predicate devices (ImmuLisa™ IgA Anti-Gliadin Antibody and ImmuLisa™ IgG Anti-Gliadin Antibody) as the benchmark for comparison.

4. Adjudication Method for the Test Set:

No adjudication method is described. The comparison is made by determining the total agreement of positive and negative test results between the new device and the predicate device.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No MRMC study was done. The study compares a new assay device (UniCAP® Gliadin IgA/IgG) to existing predicate assay devices. It does not involve human readers interpreting results or comparing human performance with and without AI assistance.

6. Standalone (Algorithm Only) Performance:

Yes, a standalone study was done. The entire comparison is based on the performance of the UniCAP® Gliadin IgA/IgG Assays themselves (the "algorithm only," in this context referring to the automated immunoassay system) against the predicate ELISA assays. There is no human-in-the-loop component described in the performance evaluation.

7. Type of Ground Truth Used:

The "ground truth" for this study is the results obtained from the legally marketed predicate devices (ImmuLisa™ IgA Anti-Gliadin Antibody and ImmuLisa™ IgG Anti-Gliadin Antibody ELISA). The study aimed to show substantial equivalence, not to establish absolute diagnostic accuracy against a clinical gold standard like pathology or patient outcomes.

8. Sample Size for the Training Set:

The document does not mention any training set or its sample size. This type of device (an immunoassay) does not typically involve machine learning training in the same way an imaging AI algorithm would. Its development would involve analytical validation and process optimization, but the concept of a "training set" as understood in AI/ML is not applicable here.

9. How the Ground Truth for the Training Set Was Established:

As no training set is mentioned or relevant for this type of device, this point is not applicable.

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