Search Results

The Preciset DAT THC calibrators are designed for the calibration of the Roche assays for cannabinoids in human urine on automated clinical chemistry analyzers.
The Preciset DAT THC 20 calibrators are designed for the calibration of the Roche assays for cannabinoids in human urine on automated clinical chemistry analyzers.

Roche Preciset DAT THC calibrators contain 6 levels of cannabinoids, prepared by the quantitative addition of △'-THC-COOH to drug-free human urine. Drug concentrations are verified by GC/MS. The calibrator set contains six levels of cannabinoids in bottles 1-6. Bottle 1 is negative (drug free) human urine, followed by bottles 2-6 containing increasing amounts of cannabinoids. The respective target concentrations of cannabinoids included is as follows:
Δ -THC-COOH: 0, 20, 50, 100, 200, 300 ng/ml
Roche Preciset DAT THC 20 calibrators contain 5 levels of cannabinoids, prepared by the quantitative addition of A -THC-COOH to drug-free human urine. Drug concentrations are verified by GC/MS. The calibrator set contains five levels of cannabinoids in bottles 1-5. Bottle 1 is negative (drug free) human urine, followed by bottles 2-5 containing increasing amounts of cannabinoids. The respective target concentrations of cannabinoids included is as follows:
△3-THC-COOH: 0, 10, 20, 40, 100 ng/ml

The provided document is a 510(k) summary for calibrators, not a study describing the performance of an AI or medical device with acceptance criteria. Therefore, most of the requested information regarding acceptance criteria, study design, sample sizes, expert involvement, and ground truth cannot be extracted from this document.

The document describes the Preciset DAT THC and Preciset DAT THC 20 Calibrators, which are used to calibrate Roche assays for cannabinoids in human urine on automated clinical chemistry analyzers. The focus is on demonstrating substantial equivalence to a predicate device (Abuscreen OnLine THC Calibration Pack 20), not on proving performance against specific acceptance criteria in the way an AI or diagnostic device would typically be evaluated.

Here's what can be extracted based on the document:

1. A table of acceptance criteria and the reported device performance:

This document does not contain a table of acceptance criteria or reported device performance in the context of an AI or diagnostic study. The "performance" described is the chemical composition and intended use of the calibrators, and their verification by GC/MS.

2. Sample size used for the test set and the data provenance:

Not applicable. This is a description of calibrator products, not a study involving a test set of patient data. The calibrators themselves are prepared by adding known concentrations of Δ⁹-THC-COOH to drug-free human urine.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

Not applicable. Ground truth for the calibrators is established by the quantitative addition of Δ⁹-THC-COOH and verified by GC/MS, which is a chemical analytical method, not expert interpretation.

4. Adjudication method for the test set:

Not applicable. No test set adjudication is described.

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 document is not about an AI device or a comparative effectiveness study involving human readers.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

Not applicable. This is not an algorithm or AI device.

7. The type of ground truth used:

For the calibrators, the "ground truth" for the concentration of Δ⁹-THC-COOH is established by quantitative addition of the substance to drug-free human urine and verified by GC/MS (Gas Chromatography/Mass Spectrometry). This is an objective chemical measurement.

8. The sample size for the training set:

Not applicable. This document does not describe a training set for an algorithm.

9. How the ground truth for the training set was established:

Not applicable. This document does not describe a training set.

Ask a specific question about this device