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510(k) Data Aggregation
(125 days)
The CS-400™ Coagulation Analyzer is a multipurpose system for in vitro coagulation studies consisting of one automated instrument and its associated reagents and controls. The system is used to perform a series of coagulation studies and coagulation factor assays.
The Amelung CS-400™ Coagulation Analyzer is an automated random access multipurpose analyzer. The CS-400™ Coagulation Analyzer can be used for the detection of fibrin formation utilizing either mechanical principles (ball method) or photo-optical principles to perform clot based tests such as prothrombin time (PT), activated partial thromboplastin time (APTT), fibrinogen, factor assays, and other clotting tests. In addition, the CS-400™ Coagulation Analyzer can be used for chromogenic assays such as antithrombin III (AT III).
The provided text describes the 510(k) summary for the Sigma Diagnostics Inc. CS-400™ Coagulation Analyzer. The acceptance criteria and the study proving the device meets them are detailed as follows:
1. Table of Acceptance Criteria and Reported Device Performance:
The document lists performance characteristics from comparison studies and precision studies. The comparison studies establish the device's correlation with a predicate device, while precision studies demonstrate its reproducibility.
| Test (Method) | Acceptance Criteria (from comparison study with Amelung AMAX CS-190™) | Reported Device Performance (r-value) | Reported Device Performance (Regression Equation) | Acceptance Criteria (from precision study) | Reported Device Performance (Within Run CV) | Reported Device Performance (Total CV) |
|---|---|---|---|---|---|---|
| PT (optical) | N/A (regression statistics provided to show substantial equivalence) | r = 0.921 | y = 1.061x + 0.6 | ≤ (implied acceptable precision) | <2.2% | <4.5% |
| PT (mechanical) | N/A | r = 0.924 | y = 1.038x - 0.5 | ≤ (implied acceptable precision) | <3.2% | <6.5% |
| APTT (optical) | N/A | r = 0.964 | y = 1.072x - 0.5 | ≤ (implied acceptable precision) | <2.5% | <3.5% |
| APTT (mechanical) | N/A | r = 0.972 | y = 0.938x + 1.0 | ≤ (implied acceptable precision) | <2.3% | <3.5% |
| Factor IX (optical) | N/A | r = 0.945 | y = 0.943x + 4.6 | ≤ (implied acceptable precision) | <5.3% | <7.3% |
| Factor IX (mechanical) | N/A | r = 0.924 | y = 0.977x + 3.7 | ≤ (implied acceptable precision) | <6.3% | <9.5% |
| Factor X (optical) | N/A | r = 0.966 | y = 0.920x + 9.5 | ≤ (implied acceptable precision) | <5.7% | <7.8% |
| Factor X (mechanical) | N/A | r = 0.974 | y = 0.898x + 8.7 | ≤ (implied acceptable precision) | <3.8% | <7.0% |
| Fibrinogen (optical) | N/A | r = 0.967 | y = 1.064x - 11.3 | ≤ (implied acceptable precision) | <5.1% | <8.1% |
| Fibrinogen (mechanical) | N/A | r = 0.977 | y = 1.074x - 2.2 | ≤ (implied acceptable precision) | <5.9% | <9.0% |
| AT III (chromogenic) | N/A | r = 0.972 | y = 0.920x + 11.7 | ≤ (implied acceptable precision) | <5.9% | <9.3% |
Note: The document states "The safety and effectiveness of the CS-400™ Coagulation Analyzer is demonstrated by its substantial equivalency to the predicate devices." This implies that the acceptance criteria for the comparison studies were that the regression statistics (r-value and regression equation) were similar enough to the predicate device to establish substantial equivalence. For precision, the "less than" symbols indicate that the reported %CV values met the acceptance criteria for precision.
2. Sample size used for the test set and the data provenance:
The document does not explicitly state the sample size used for the comparison or precision studies. It only refers to "comparison studies of assays" and "precision studies." The data provenance (e.g., country of origin, retrospective or prospective) is also not specified.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
Not applicable. This device is an in vitro diagnostic (IVD) instrument, and its performance is evaluated against a predicate device (for comparison) and through its own precision/reproducibility (for precision). The "ground truth" for such devices is typically established through direct measurement against a reference method or validated calibrators, not through expert consensus in the way image-based diagnostic aids might be.
4. Adjudication method for the test set:
Not applicable for an in vitro diagnostic device assessing analytical performance.
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:
Not applicable. This is an automated coagulation analyzer, not an AI-assisted diagnostic tool requiring human reader interpretation studies.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:
The studies described are standalone performance studies of the device itself (CS-400™ Coagulation Analyzer) compared to a predicate device (Amelung AMAX CS-190™ Coagulation Analyzer) and its own reproducibility. There is no mention of an "algorithm" in the context of AI, but rather the performance of an analytical instrument.
7. The type of ground truth used:
- For comparison studies: The "ground truth" was established by the measurements obtained from the predicate device, the Amelung AMAX CS-190™ Coagulation Analyzer. The CS-400™ device's results were compared against these.
- For precision studies: The "ground truth" for precision is the expected result of a measurement and the inherent variability of the analytical process. This is assessed by repeatedly measuring samples and calculating the coefficient of variation.
8. The sample size for the training set:
Not applicable. This device is an analytical instrument, not an AI/machine learning model that requires a training set in the conventional sense. Its design and operational parameters are established through engineering and analytical chemistry principles.
9. How the ground truth for the training set was established:
Not applicable, as there is no training set in the context of AI/machine learning for this type of device.
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