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The Healgen® Accurate Oral Fluid Drug Test COT is a lateral flow chromatographic immunoassay for the qualitative detection of COT in oral fluid at the cut-off concentration 30 ng/mL.

This assay provides only a preliminary result. An alternative laboratory test must be used to confirm the results provided by this drug test. Gas chromatography/mass spectrometry (GC/MS) is the preferred method confirmation test.

The Healgen® Accurate Oral Fluid Drug Test is a competitive binding lateral flow immunochromatographic assay for the qualitative and simultaneous detection of Marijuana (THC) and Cotinine in human oral fluid at the cutoff concentrations listed below and their metabolites.

This assay provides only a preliminary analytical test result. A more specific alternate chemical method must be used in order to obtain a confirmed analytical result. Gas chromatography mass spectrometry (GC/MS) and liquid chromatography mass spectrometry (LC/MS) are the preferred confirmatory methods.

The Healgen® Accurate Oral Fluid Drug Test COT is immunochromatographic assay that uses a lateral flow system for the qualitative detection of cotinine in human oral fluid. The Healeen® Accurate Oral Fluid Drug Test immunochromatographic assay for the qualitative and simultaneous detection of Marijuana (THC) and Cotinine in human oral fluid. The tests are the first step in a two-step process. The second step is to send the sample for laboratory testing if preliminary positive results are obtained.

This document describes the performance characteristics and studies for the Healgen® Accurate Oral Fluid Drug Test and Healgen® Accurate Oral Fluid Drug Test COT, which are qualitative immunoassays for detecting Cotinine (COT) and Marijuana (THC) in oral fluid.

Here's an analysis of the acceptance criteria and the study that proves the device meets them:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria are not explicitly stated as numerical targets in the document. However, the "Precision-Reproducibility-Cut-Off" studies implicitly define the expected performance around the cut-off values. The "Comparison Studies" and "Layuser Studies" then demonstrate the agreement of the device with a gold standard (LC/MS/MS).

2. Sample Sizes Used for the Test Set and Data Provenance

• Precision-Reproducibility-Cut-Off (Analytical Performance):

  • For each of the 9 concentration levels and 3 device lots: 50 samples (2 runs per day for 25 days).
  • Total samples = 9 concentrations * 50 samples/concentration * 3 lots = 1350 samples for COT, and 1350 samples for THC.
  • Data Provenance: Samples were "spiked" with cotinine or marijuana in negative oral fluid samples, indicating a controlled laboratory setting. The origin (country/retrospective/prospective) is not specified, but the nature of spiking implies prospective sample preparation for the study.

• Method Comparison Studies (Expert Operator):

  • COT: 427 samples
  • THC: 126 samples
  • Data Provenance: Oral fluid samples. The data provenance (e.g., country of origin, retrospective or prospective collection) is not specified.

• Layuser Studies:

  • COT: 362 samples
  • Data Provenance: Oral fluid samples. The data provenance is not specified.

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

• Ground Truth Establishment: The ground truth for all performance studies (Precision, Method Comparison, Layuser) was established by LC/MS/MS (Liquid Chromatography/Mass Spectrometry/Mass Spectrometry), which is stated as the "preferred method confirmation test."
• Qualifications of Experts: This implies that the ground truth was not established by human experts interpreting images or subjective data, but by highly accurate analytical laboratory equipment and the qualified personnel operating it. The document does not specify the number or qualifications of the lab personnel who performed the LC/MS/MS analysis, as GC/MS and LC/MS/MS are considered an objective gold standard in drug testing.

4. Adjudication Method for the Test Set

• LC/MS/MS serves as the objective ground truth, providing quantitative results against which the device's qualitative results are compared. Therefore, an "adjudication method" in the sense of reconciling disagreements between human readers is not applicable here. Any discrepancies between the device result and LC/MS/MS are reported as "discordant results."

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance

• This is not an AI-assisted diagnostic device, but a rapid diagnostic test (lateral flow immunoassay). Therefore, an MRMC comparative effectiveness study involving human readers with and without AI assistance is not applicable.
• The "Layuser Studies" evaluate the performance of the device in the hands of untrained users, essentially assessing human performance with the device instructions. It shows that layusers can achieve comparable results to expert operators for COT detection.

6. If a Standalone (i.e., algorithm-only without human-in-the-loop performance) Was Done

• This question is not applicable as the device is a lateral flow immunoassay kit, not an algorithm. Its "standalone" performance is inherently demonstrated by the results it produces directly from the oral fluid sample, without further human-in-the-loop interpretation beyond reading the visual lines on the strip. The "Precision-Reproducibility-Cut-Off" and "Method Comparison Studies" characterize this inherent device performance.

7. The Type of Ground Truth Used

• The ground truth used was analytical confirmation by LC/MS/MS. This is an objective, quantitative laboratory method considered the gold standard for drug detection and quantification in biological samples.

8. The Sample Size for the Training Set

• The document describes performance studies, but it does not mention a "training set" in the context of machine learning. This is a traditional immunoassay device, which does not employ machine learning algorithms that require separate training and test sets. The studies described are for analytical and clinical validation of the device's performance.

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

• As there is no mention of a "training set" for a machine learning model, this question is not applicable.

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