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510(k) Data Aggregation
(107 days)
ACL AcuStar: Automated immunoassay analyzer designed specifically for in vitro diagnostic use in a clinical laboratory. The assay analysis is based on chemiluminescent technology. The system provides results for both direct measurements and calculated parameters.
HemosIL AcuStar D-Dimer: Fully automated chemiluminescent immunoassay for the quantitative determination of D-Dimer in human citrated plasma on the ACL AcuStar as an aid in the diagnosis of venous thromboembolism (VTE) [deep vein thrombosis (DVT) and pulmonary embolism (PE)].
HemosIL AcuStar D-Dimer Controls: For the quality control of D-Dimer assay performed on the ACL AcuStar.
ACL AcuStar: The AcuStar is an automated, bench-top system for lab use that measures the analyte amount in blood samples by: Subjecting the blood sample to reagents that cause a reaction with an antigen or antibody in the sample. Placing the cuvettes in a controlled environment to allow the reactants to bind into a complex. Separating out the complex from unused reactants. Treating this complex with a chemical that produces light in proportion to the analyte concentration. Measuring the light output to determine the amount of antibodies or antigens that were in the sample.
HemosIL AcuStar D-Dimer: The HemosIL AcuStar D-Dimer assay is a two-step immunoassay to quantify D-Dimer in human citrated plasma using magnetic particles as solid phase and a chemiluminescent detection system. In the first step, sample, anti-D-Dimer antibody coated magnetic particles, and assay buffer are combined, and the fibrin soluble derivatives containing the D-Dimer domain present in the sample bind to the anti-D-Dimer antibody coated magnetic particles. After magnetic separation and washing, an anti-XDP antibody labeled with isoluminol is added and incubated in a second step. After a new magnetic separation and washing, two triggers are added and the resulting chemiluminescent reaction is measured as relative light units (RLUs) by the ACL AcuStar optical system. The RLUs are directly proportional to the D-Dimer concentration in the sample. The ACL AcuStar D-Dimer assay utilizes a 4 Parameter Logistic Curve (4PLC) fit data reduction method to generate a Master Curve. The Master Curve is predefined lot dependent, and is stored in the instrument through the cartridge barcode. With the measurement of calibrators, the predefined Master Curve is transformed to a new, instrument specific 4PLC Working Curve. The concentration values of the calibrators are included in the calibrator plastic tube barcodes.
HemosIL AcuStar D-Dimer Controls: The Low, High, and Very High D-Dimer Controls are prepared by means of a dedicated process and contain different concentrations of partially purified D-Dimer obtained by digestion of Factor XIIIa cross-linked human fibrin with human plasmin.
Here's a breakdown of the acceptance criteria and the study details for the ACL™ AcuStar™ HemosIL™ AcuStar™ D-Dimer, based on the provided 510(k) summary:
Acceptance Criteria and Reported Device Performance
| Acceptance Criteria Category | Specific Metric | Acceptance Criterion (Implicit) | Reported Device Performance |
|---|---|---|---|
| Precision | Coefficient of Variation (CV%) for D-Dimer Controls and Calibrator 1 | The document does not explicitly state numerical acceptance criteria for precision (e.g., CV% < X%). However, good precision is generally expected for diagnostic assays. The reported CV% values demonstrate the reproducibility and reliability of the assay across different D-Dimer concentrations. | Low D-Dimer Control:- Within run CV%: 4.0%- Total CV%: 6.8%High D-Dimer Control:- Within run CV%: 2.3%- Total CV%: 4.9%Very High D-Dimer Control:- Within run CV%: 2.5%- Total CV%: 5.6%Calibrator 1:- Within run CV%: 2.7%- Total CV%: 5.4% |
| Method Comparison | Correlation (r) and Slope when compared to predicate device (VIDAS) | Not explicitly stated as a numerical threshold in the document. However, a strong correlation (r close to 1) and a slope close to 1 (or a consistent proportionality) are generally expected to demonstrate substantial equivalence to the predicate device. | Slope: 1.16r (correlation coefficient): 0.888 |
| Clinical Performance | Sensitivity for VTE diagnosis | For a D-Dimer assay used as an aid in diagnosis and for ruling out VTE, high sensitivity is crucial to minimize false negatives. While no explicit numerical threshold is stated, 100% sensitivity is a highly desirable outcome for an exclusion assay, indicating that no true positive VTE cases were missed. | Sensitivity: 100% (95% CI: 96.3%-100.0%) |
| Specificity for VTE diagnosis | While not as critical as sensitivity for exclusion assays, reasonable specificity helps reduce unnecessary further testing. No explicit numerical threshold is provided, but the reported specificity provides insight into the assay's ability to correctly identify true negatives. | Specificity: 55.5% (95% CI: 49.0%-61.8%) | |
| Negative Predictive Value (NPV) for VTE diagnosis | High NPV is paramount for an exclusion assay, as it indicates the probability that a patient truly does not have the condition if the test result is negative. Similar to sensitivity, 100% NPV is an ideal outcome for an exclusion assay. | NPV: 100% (95% CI: 97.3%-100.0%) | |
| Detection Limit | Lower limit of D-Dimer concentration that can be reliably detected | The detection limit is an inherent performance characteristic. A lower detection limit can offer more sensitive assessment. The document compares this to predicate devices. | 6.51 ng/mL |
| Linear Range | Range of D-Dimer concentrations over which the assay provides accurate | This defines the measurable range of the assay. A wide linear range with auto-rerun capability is advantageous. The document compares this to predicate devices. | 54.3 - 1110000 ng/mL with Auto Rerun |
Study Information
2. Sample size used for the test set and the data provenance:
- Test Set Sample Size (Clinical Management Study): 344 frozen citrated plasma samples.
- Data Provenance: From patients admitted to an emergency unit with suspected PE or DVT. The country of origin is not explicitly stated, but the context generally implies a clinical setting in a developed country (e.g., US or EU) for regulatory submissions of this type. The samples were retrospective, as they were "frozen citrated plasmas from patients."
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- The document does not explicitly state the number of experts or their qualifications.
- Ground Truth Establishment: "97 were confirmed as VTE positive (64 PE and 33 DVT) by standard objective tests and the remaining 247 were confirmed as negative." The "standard objective tests" would typically be interpreted and confirmed by medical specialists (e.g., radiologists for imaging, clinical physicians for diagnosis confirmation), but this is not detailed.
4. Adjudication method for the test set:
- The document does not specify an explicit adjudication method (e.g., 2+1, 3+1). The ground truth was established by "standard objective tests" and clinical confirmation.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
- No, an MRMC comparative effectiveness study was not done. This submission focuses on the performance of a diagnostic instrument and assay (ACL AcuStar D-Dimer) as a standalone test, and its clinical utility for exclusion of VTE, rather than human reader improvement with AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
- Yes, the performance data presented is for the standalone device (ACL AcuStar D-Dimer assay and instrument) without human-in-the-loop assistance in its interpretation. The results (sensitivity, specificity, NPV) directly reflect the device's diagnostic capability.
7. The type of ground truth used:
- The ground truth was established by outcomes data and expert diagnosis based on standard objective tests:
- VTE positive cases (PE and DVT) were "confirmed ... by standard objective tests." These typically include imaging studies (e.g., CT pulmonary angiography for PE, ultrasound for DVT) and clinical assessment.
- VTE negative cases were "confirmed as negative" also presumably by the absence of findings on standard objective tests and clinical follow-up.
8. The sample size for the training set:
- The document does not specify a separate "training set" in the context of machine learning. This is a traditional in-vitro diagnostic device submission for an immunoassay. The concept of a training set for an algorithm is not directly applicable here. The "training" in this context refers to the development and optimization of the assay and its reagents during product development, which is typically done with various in-house samples and analytical studies.
9. How the ground truth for the training set was established:
- As noted above, the concept of a separate "training set" with ground truth in the machine learning sense is not explicitly present. For an immunoassay, the "ground truth" during development (analogous to training) would involve using characterized samples with known D-Dimer concentrations or clinical status, and optimizing the assay's reagents and calibration curve to achieve accurate measurements and clinical cut-offs. This development process for assays does not typically involve the formal "ground truth establishment" and "adjudication" methods seen in AI/ML validation studies.
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