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Immunoassay for the qualitative detection of methamphetamine, opiates, cocaine metabolite, THC metabolite, phencyclidine, benzodiazepines, barbiturates, tricyclic antidepressants, methadone, and amphetamine in human urine to assist in screening of abuse samples. The detecting cut-off concentrations are as follows:

This assay provides only a preliminary analytical test result. A more specific alternate chemical method m ust be used in order to obtain a confirmed analytical result. Gas chromatography/mass spectrometry (GC/ MS)/High performance liquid chromatography (HPLC, for TCA) are the preferred confirmatory methods. Cl inical consideration and professional judgment should be applied to any drug of abuse test result, particula rly when preliminary positive results are obtained.

The AccuSign® RCDOA 10 test device is a simple immuno-chromatographic test for the rapid, qualitative detection of methamphetamine, opiates, cocaine, THC, phencyclidine, benzodiazepines, barbiturates, tricyclic antidepressants, methadone, amphetamine and/or their metabolites in human urine. The test result can be read visually or with DXpress reader (K050955).

Here's an analysis of the provided 510(k) summary, detailing the acceptance criteria and the study information.

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for this device are implicitly tied to demonstrating substantial equivalence to its predicate device (K983501: AccuSign® DOA10). Since the new device (AccuSign® RC-DOA 10) is stated to be "identical and use the same formula and manufacturing processes with the same reagents" as the predicate, and the key difference is the addition of a reader-compatible option, the acceptance criteria are effectively that its performance should be commensurate with the established performance of the predicate device.

The document directly states the detection cut-off concentrations for each substance as both the intended use and the "Detection Cutoff" in the substantial equivalence comparison table. This indicates that the device must accurately detect these substances at or above these specified cut-off levels.

Note on Reported Device Performance: The provided 510(k) summary does not contain specific performance metrics (e.g., sensitivity, specificity, accuracy) from a separate clinical study for the new device. Instead, the claim of substantial equivalence relies on the new device being "identical" to the predicate in its core biochemical function, with the only change being an additional reading method. Therefore, the "reported device performance" is essentially that it achieves the same detection capabilities as the legally marketed predicate device at the specified cut-off concentrations.

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

The provided 510(k) summary does not explicitly detail a separate test set size or its data provenance (e.g., country of origin, retrospective/prospective). The submission relies heavily on the claim that the new device is "identical" to the predicate device in terms of its chemical components and manufacturing process. Therefore, the performance data from the predicate device's original clearance would be presumed to apply.

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

The 510(k) summary does not mention the use of experts for establishing ground truth for a test set for this specific submission. This is because the device is a diagnostic test kit for drugs of abuse, and the "ground truth" for such tests typically comes from validated analytical methods (like GC/MS). Expert consensus is usually more relevant for image-based diagnostic devices or complex clinical scenarios where subjective interpretation is involved.

4. Adjudication Method for the Test Set

No adjudication method is described, as no specific test set or study requiring adjudication is detailed in this 510(k) summary.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and Effect Size

No MRMC comparative effectiveness study was mentioned or performed for this submission. MRMC studies are typically used for devices where human readers interpret diagnostic images or data, and the AI system is intended to assist or replace human interpretation. This device is a rapid immunoassay test where results are either visually read or read by a simple optical reader (DXpress). The 510(k) focuses on the "Reader reading compatible" aspect, implying it's an alternative to visual reading, not an AI assistance for human interpretive tasks.

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

Yes, in a sense, a standalone performance is implied. The device, whether read visually or by the DXpress reader, functions as a standalone diagnostic tool for detecting the presence of drugs of abuse. The performance is based on its ability to react to specific concentrations of analytes, independent of human interpretive faculties beyond simply observing a line or reading a digital output. The "algorithm" here is the chemical reaction and optical detection mechanism. However, no specific separate standalone clinical study with new data is presented in this summary.

7. The Type of Ground Truth Used

The ground truth for this type of immunoassay is based on analytical chemical methods, specifically the concentration of the target drug or metabolite in urine samples. The document explicitly states that the test provides "only a preliminary analytical result" and that "a more specific alternative chemical method must be used to obtain a confirmed analytical result. GC/MS is the preferred confirmatory method." This indicates that Gas Chromatography/Mass Spectrometry (GC/MS) (and for TCA, HPLC) is the gold standard used to establish definitive ground truth for drug presence and concentration.

8. The Sample Size for the Training Set

The 510(k) summary does not mention a training set size. This is because the device is an immunoassay kit built on established chemical principles and reagents. It does not involve machine learning algorithms that require a training set in the conventional sense. The "training" in this context would refer to the development and optimization of the chemical formulations and reaction conditions, which were already established for the predicate device.

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

As there is no conventional training set for a machine learning algorithm, the concept of establishing ground truth for it does not apply here. The fundamental "ground truth" for the device's design and operation, derived from the predicate, would have been established through a combination of:

• Analytical validation: Testing the device with known concentrations of drug standards and interferences.
• Clinical correlation: Comparing test results with confirmed results from definitive analytical methods (like GC/MS) on patient samples during the development and validation of the predicate device.

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