Search Results

The Amedica Drug Screen MDMA-BAR-BZO-MTD-TCA Test is an in vitro diagnostic test for the rapid detection of 3,4 methylenedioxymethamphetamine, secobarbital, oxazepam, methadone and nortriptyline in human urine at the following cut-off concentration.

This test kit is used to obtain a visual, qualitative result and is intended for professional use. It is not intended for over the counter sale.

Membrane based one-step, lateral flow, competitive immunoassay use colloidal gold for visual detection of 3,4 methylenedioxymethamphetamine, secobarbital, oxazepam, methadone and nortriptyline.

Here's an analysis of the provided text regarding the Amedica Drug Screen MDMA-BAR-BZO-MTD-TCA Test, focusing on acceptance criteria and the supporting study:

Acceptance Criteria and Device Performance

Note: The document only provides a single summary performance metric ("> 94% agreement") for the entire panel of drugs when compared to GC/MS. It does not break down the performance for each individual drug.

Study Details

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

   • Sample Size: The document does not specify the exact sample size for the "blind-labeled specimens" used in the correlation study.
   • Data Provenance: The data provenance is not explicitly stated (e.g., country of origin). The specimens were "blind-labeled," implying they were collected prior to the study. This suggests a retrospective data collection approach for this part of the study. Separately, a "clinical site study" was performed at a "certified laboratory," suggesting a prospective clinical evaluation, but details are not provided.

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

   • The ground truth was established by GC/MS (Gas Chromatography/Mass Spectrometry), which is an analytical laboratory method, not human experts. Therefore, the concept of "number of experts" or their "qualifications" doesn't directly apply in the way it would for image interpretation or subjective medical assessments.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not applicable. As the ground truth was established by GC/MS, there was no human adjudication process involved for resolving discrepancies between multiple expert readings.

4. 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:

   • No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly described.
   • The device is a qualitative immunoassay for drug detection, where the reading is visual and interpreted by a single professional. It's not an AI-assisted diagnostic tool that would typically involve human readers interpreting complex data.
   • Therefore, the concept of an "effect size of how much human readers improve with AI vs without AI assistance" does not apply here.

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

   • Yes, a standalone performance assessment was effectively done. The "correlation study using blind-labeled specimens that have been measured by GC/MS" and stating "> 94% agreement with GC/MS results" represents the standalone performance of the device's ability to detect the target substances. The "clinical site study" further validated its use by professionals, implying that the device's output (visual lines) is directly interpreted.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The primary ground truth used was GC/MS (Gas Chromatography/Mass Spectrometry), which is a gold standard analytical method for confirming drug presence and concentration in urine samples.

7. The sample size for the training set:

   • The document does not explicitly mention a "training set" or its size, as this device is a competitive immunoassay, not a machine learning algorithm that typically requires a distinct training phase. Its design and performance are based on chemical and immunological principles.

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

   • Not applicable, as no explicit training set for a machine learning algorithm was described. The performance of the immunoassay is inherent to its biochemical design.

Ask a specific question about this device