Search Results

The VIDAS® D-Dimer New assay is intended for use as an aid in the diagnosis of deep venous thrombosis and pulmonary embolism disease.

The VIDAS® D-Dimer New (DD2) Assay is an automated quantitative test for use on the VIDAS instrument (K891385) for the immunoenzymatic determination of fibrin degradation products (FbDP) in human plasma using the enzyme-linked fluorescent immunoassay (ELFA) technique. The instrument controls all assay steps and assay temperatures. A pipette tip-like disposable device, the Solid Phase Receptacle (SPR), serves as the solid phase as well as a pipettor for the assay. Reagents for the assay are ready-to-use and pre-dispensed in the sealed DD2 Reagent Strips.

The assay principle combines a two-step enzyme immunoassay sandwich method with a final fluorescent detection (ELFA). The Solid Phase Receptacle (SPR) serves as the solid phase with the anti-FbDP monoclonal (mouse) antibodies P10B5E12C9 adsorbed on its surface, as well as the pipetting device for the assay.

The instrument performs all of the assay steps automatically. The reaction medium is cycled in and out of the SPR several times according to a specified protocol.

The sample is taken and transferred into the well containing the conjugate, which is an alkaline phosphatase-labeled anti-FbDP monoclonal (mouse) antibodies (P2C5A10) The sample/conjugate mixture is cycled in and out of the SPR several times to increase the reaction speed. The antigen binds to antibodies coated on the SPR and to the conjugate forming a "sandwich".

In the second step, the remaining free antigen sites are saturated by cycling the conjugate in the fifth well of the strip in and out of the SPR. Unbound components are eliminated during the washing steps.

Two detection steps are then performed successively. During each step, the substrate (4-Methyl-umbelliferyl phosphate) is cycled in and out of the SPR. The conjugate enzyme catalyzes the hydrolysis of this substrate into a fluorescent product (4-Methylumbelliferone), the fluorescence of which is measured at 450 nm. The intensity of the fluorescence is proportional to the concentration of antigen present in the sample.

At the end of the assay, results are automatically calculated by VIDAS in relation to two calibration curves stored in memory corresponding to the two detection steps. A threshold signal determines the choice of the calibration curve to be used for each sample. The results are then printed out.

The acceptance criteria and study proving the device meets them are outlined below:

1. Table of Acceptance Criteria and Reported Device Performance:

The document doesn't explicitly state quantitative acceptance criteria for each metric (Sensitivity, Specificity, Negative Predictive Value) prior to presenting results. Instead, it demonstrates the performance of the new DD2 Assay in comparison to the predicate DD Assay. The implicit acceptance criteria appear to be substantial equivalence or improvement over the predicate device.

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

• Sample Size: 93 samples were used for the correlation study between DD2 and DD assays. The specific sample sizes for the clinical sensitivity, specificity, and negative predictive value studies are not explicitly stated, but the "All VTE Suspects" results imply a combined population. The confidence intervals (e.g., 95% CI, 95.0-100) are typically derived from the sample size of the specific population being analyzed.
• Data Provenance: The samples were "Real plasma samples" or "spiked samples" when necessary to achieve higher D-Dimer concentrations. The document does not specify the country of origin of the data or whether it was retrospective or prospective. It mentions "The study conducted at the outside facility," indicating external validation, but no further details on provenance.

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

The document does not provide any information about experts used to establish ground truth or their qualifications. The "ground truth" for deep venous thrombosis (DVT) and pulmonary embolism (PE) diagnosis is typically established through a combination of clinical assessments, imaging studies (e.g., ultrasound, CT pulmonary angiography), and follow-up, which is implied by the clinical context of D-Dimer testing but not detailed regarding expert involvement in this submission.

4. Adjudication Method for the Test Set:

The document does not describe any adjudication method used for the test set.

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

No MRMC comparative effectiveness study was mentioned. This device is an automated in vitro diagnostic assay, not a medical imaging or interpretation device that typically involves human readers. Therefore, the concept of human readers improving with AI assistance is not directly applicable here.

6. Standalone (Algorithm Only) Performance:

Yes, the performance data presented (Sensitivity, Specificity, Negative Predictive Value) is for the standalone algorithm performance of the VIDAS D-Dimer New (DD2) Assay. The results are reported as the assay's ability to detect FbDP and its correlation with clinical outcomes related to DVT and PE.

7. Type of Ground Truth Used:

The ground truth implicitly used for assessing the Sensitivity, Specificity, and Negative Predictive Value of the D-Dimer assay would be the clinical diagnosis of Deep Venous Thrombosis (DVT) and Pulmonary Embolism (PE). This diagnosis is typically established through a combination of clinical assessment, objective imaging studies (e.g., ultrasound for DVT, CT Pulmonary Angiography for PE), and potentially the patient's clinical outcome. The document does not explicitly detail the specific methods for establishing this clinical ground truth.

8. Sample Size for the Training Set:

The document presents performance data for the VIDAS D-Dimer New (DD2) Assay and compares it to the VIDAS D-Dimer (DD) Assay. It does not specify a separate "training set" as commonly understood in machine learning contexts. This is a traditional in vitro diagnostic device, and its development would likely involve internal validation during design and development, rather than a distinct machine learning training set. The values for calibration curves are established, but the size of the dataset used to build these is not specified.

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

As mentioned above, the concept of a "training set" with ground truth in the machine learning sense is not directly applicable to this traditional in vitro diagnostic device submission. The assay relies on established immunoenzymatic principles. The "ground truth" for establishing the calibration curves (which are analogous to training for algorithm-based devices) would involve using known concentrations of FbDP standards. The document states that the instrument calculates results "in relation to two calibration curves stored in memory," indicating these curves were pre-established, likely using reference materials with known D-Dimer concentrations.

Ask a specific question about this device