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510(k) Data Aggregation
(68 days)
The SYNCHRON® Systems DAT Low and High Urine Calibrators II, in conjunction with SYNCHRON Reagents, are intended for use on SYNCHRON Systems for the calibrations of Barbiturates, Benzodiazepine, Methadone, Opiate 300 ng, Methaqualone, and Propoxyphene enzyme immunoassays.
The SYNCHRON® Systems DAT Low and High Urine Calibrators II are used for calibration of Drugs of Abuse reagents in the clinical laboratory. This product contains a 5 mL bottle of the Low Urine Calibrator II and a 5 mL bottle of the High Urine Calibrator 11. The storage temperature for the calibrators is +2℃ to +8℃.
The provided text describes the SYNCHRON® Systems DAT Low and High Urine Calibrators II
device. It does not contain information about acceptance criteria or a study that specifically proves the device meets such criteria in terms of performance metrics like sensitivity, specificity, accuracy, or reader improvement with AI. Instead, it focuses on demonstrating substantial equivalence to a predicate device.
Here's a breakdown of the information that is available, and what is missing:
The document states:
"The data in the Premarket Notification on safety and effectiveness supports a finding of substantial equivalence to toxicology calibrators already in commercial distribution. Stress stability studies of the DAT Low and High Urine Calibrators II support the Beckman stability claim of 12 months."
This indicates that a study was performed to assess stability, and the overall data supported substantial equivalence. However, specific acceptance criteria for performance and the detailed results of such a study are not provided in the given text.
Therefore, many of the requested sections regarding acceptance criteria, study details, ground truth, and expert involvement cannot be populated from the provided document.
1. A table of acceptance criteria and the reported device performance
Acceptance Criteria | Reported Device Performance |
---|---|
Not provided in the document. The document primarily focuses on demonstrating substantial equivalence to a predicate device and stability. Specific performance metrics like accuracy, precision, sensitivity, or specificity with defined acceptance thresholds are not detailed. | The device's "safety and effectiveness supports a finding of substantial equivalence to toxicology calibrators already in commercial distribution." Stress stability studies support a 12-month stability claim. |
2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample size for test set: Not provided.
- Data provenance: Not provided (e.g., country of origin, retrospective/prospective).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
This information is not applicable as the device is a calibrator for laboratory assays, not an imaging device requiring expert interpretation for ground truth. Ground truth for calibrators would typically be established by known concentrations of analytes.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not applicable for a calibrator device.
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
This information is not applicable as the device is a calibrator and not an AI-powered diagnostic tool, and there is no human-in-the-loop performance described.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
This information is not applicable as the device is a calibrator, not an algorithm.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
The "ground truth" for a calibrator like this would be the known, precisely manufactured concentrations of the substances (Barbiturates, Benzodiazepine, Methadone, Opiate 300 ng, Methaqualone, and Propoxyphene) within the calibrator solutions. The document does not explicitly state how these concentrations were verified, but it is an inherent characteristic of a calibrator.
8. The sample size for the training set
This information is not applicable as the device is a calibrator, not a machine learning algorithm that requires a "training set."
9. How the ground truth for the training set was established
This information is not applicable as the device is a calibrator, not a machine learning algorithm that requires a "training set."
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