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Immunoassay for the qualitative detection of cocaine metabolite, benzoylecgonine, at the cut-off of 300 ng/mL in urine to assist in screening of abuse samples. For In vitro Diagnostic Use
Immunoassay for the qualitative detection of cocaine metabolite, benzoylecgonine, at the cut-off of 300 ng/mL in urine to assist in screening of abuse at home. For In vitro Diagnostic Use

LifeSign Home Drug Test (COC) is simple one step immunochromatographic test for the rapid, qualitative detection of cocaine.
Status Stik" COC is simple one step immunochromatographic test for the rapid, qualitative detection of cocaine.

The provided text describes two separate 510(k) submissions, 14060 and 1601-1067, for devices intended for cocaine detection. Since this request specifically asks for an analysis of a "single study," and the text for 14060 contains a "Consumer Study" while 1601-1067 does not, I will focus on the information relevant to the study mentioned for LifeSign®Home Drug Test (COC) (associated with 510(k) number 14060).

Here's an analysis of the acceptance criteria and the study that proves the device meets them, based on the provided input:

1. Table of Acceptance Criteria and Reported Device Performance:

The "acceptance criteria" appear to be implicit rather than explicitly stated as numerical thresholds. The study primarily focuses on demonstrating substantial equivalence to a predicate device and overall accuracy.

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

• Sample Size for Substantial Equivalence Comparison: 100 specimens (50 negative and 50 positive).
• Sample Size for Consumer Study: Not explicitly stated, beyond stating "over 96% overall accuracy."
• Data Provenance: Not explicitly stated (e.g., country of origin). The studies appear to be retrospective, using existing "specimens" for the substantial equivalence comparison, and implying a user-based "consumer study," but details are scarce.

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

This information is not provided in the given text. The text does not detail how the ground truth for the 100 specimens (used for substantial equivalence) or the consumer study samples was established, nor does it mention any experts involved in this process.

4. Adjudication Method for the Test Set:

This information is not provided in the given text.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not mentioned. The studies described are focused on the device's performance against known samples or in consumer use, not on comparing human readers with and without AI assistance.

6. Standalone Performance Study:

Yes, a standalone study (algorithm/device only without human-in-the-loop performance) was conducted. The "Consumer Study" and the "Substantial Equivalence" comparison both assess the device's performance directly (e.g., "LifeSign® Home Drug Test (COC) showed over 96% overall accuracy"). While the "Consumer Study" involves users, it's evaluating the device's ability to produce an accurate result when used by consumers, rather than the consumers' interpretation with or without AI assistance.

7. Type of Ground Truth Used:

The type of ground truth is implicitly based on known positive and negative specimens. For the "Substantial Equivalence" comparison, 50 negative and 50 positive specimens were used, implying their true status was already established. For the "Consumer Study," the "overall accuracy" suggests a comparison against an established gold standard, but the nature of this standard is not explicitly detailed (e.g., laboratory confirmation, expert consensus).

8. Sample Size for the Training Set:

The text does not provide any information about a training set since these are immunoassay devices, which typically do not involve machine learning models that require explicit training sets in the same way AI algorithms do. The "Substantial Equivalence" study and "Consumer Study" are performance validation studies.

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

This information is not applicable/provided as there is no mention of a training set for an AI/algorithm-based device.

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