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The Nano-Check ™AMI 3 IN 1 Test is a rapid immunoassay for the qualitative determination of Cardiac Troponin I (cTnl), Creatine Kinase MB (CK-MB), and Myoglobin in human serum and plasma specimens at cutoff concentrations of 0.5 ng/ml, 5.0 ng/ml, and 80 ng/ml, respectively, as an aid in the diagnosis of Acute Myocardial Infarction (AMI).

The Nano-Check™ AMI 3 IN 1 Test is a qualitative assay, which can not monitor the rise and fall of cTnl, CK-MB, and Myoglobin in single testing. Single testing is not recommended for AMI monitoring. Test results should be interpreted by the physician in conjunction with other laboratory test results and patient clinical findings.

The Nano-Check ™ AMI 3 IN 1 Test is a one-step lateral flow immunochromatography assay for the qualitative determination of three cardiac markers simultaneously in serum and heparin plasma.

The test is a single-use, visually read, cassette device in a plastic housing. Membrane strip inside the plastic housing contains immobilized molecules at three test lines and one control line; CK-MB antibody, Myoglobin antibody, streptavidine and goat anti-mouse antibody. Dye pad at the end of the membrane strip contains biotinylated cTnl antibody and gold colloidal particles coupled with CK-MM, cTnl and Myoqlobin antibodies. Cutoff level of each marker is 0.5 ng/ml, 5 ng/ml and 80 ng/ml for cTnl. CK-MB and Myoglobin respectively.

Device is sealed in pouch with desiccant and provided with instructions for use and disposable sample dropper.

The provided document is a 510(k) summary for the Nano-Check™ AMI 3 IN 1 Test, which is a qualitative immunochromatography assay for cardiac markers. This type of regulatory submission focuses on demonstrating substantial equivalence to a predicate device rather than providing detailed clinical study results with specific acceptance criteria and performance metrics typically found in a clinical trial report for AI/CADe devices.

Therefore, much of the requested information (like specific acceptance criteria values, sample sizes for test sets, number/qualifications of experts, adjudication methods, MRMC studies, standalone performance with metrics like sensitivity/specificity/AUC, detailed ground truth establishment for training, and training set size) is not present in this document. This submission primarily relies on "analytical performance" and "method comparison" studies, not complex clinical effectiveness studies with human readers or large-scale AI validation.

Here's a summary of what can be extracted or inferred:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" as clear numerical thresholds for performance metrics. Instead, it refers to "overall performance and characteristics" and "analytical performance" being addressed to support substantial equivalence. The "performance" is demonstrated by addressing analytical characteristics and comparing them to a predicate device.

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

• Sample Size: Not specified in the provided summary. The document mentions "Method Comparison with Predicate Device" and "Analytical Performance" studies, but does not provide the number of samples used in these non-clinical tests.
• Data Provenance: Not specified. Given it's a 510(k) for an IVD, these stability and analytical studies are typically conducted at the manufacturer's site or contracted labs. Country of origin for data is not mentioned.
• Retrospective/Prospective: Not specified, but analytical and method comparison studies are often conducted using banked samples (retrospective) or spiked samples.

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

• Not Applicable. This device is a diagnostic assay (an IVD) run on a sample (serum/plasma), not an imaging AI device that relies on expert interpretation for ground truth. The "ground truth" for such assays is established through reference methods (e.g., highly accurate laboratory analyzers) and spiked samples with known concentrations. The summary does not involve human readers interpreting images.

4. Adjudication Method for the Test Set:

• Not Applicable. See point 3. This is an in-vitro diagnostic device, not an AI/CADe system requiring human adjudication of interpretations.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was Done:

• No. An MRMC study is not mentioned or implied because this is an in-vitro diagnostic test. These studies are relevant for imaging devices where human readers interpret medical images with and without AI assistance.

6. If a Standalone (algorithm only without human-in-the-loop performance) was Done:

• Yes, implicitly. The entire device is the "algorithm only" in the context of its function as an IVD. It's a qualitative test that produces a visual result (red bands) indicating the presence or absence of cardiac markers above a cutoff. Its performance is evaluated through analytical studies (precision, accuracy relative to reference, detection limit, specificity, etc.) which collectively represent its standalone performance characteristics. However, detailed results of these studies (e.g., sensitivity, specificity derived from analytical studies) are not provided in this summary.

7. The Type of Ground Truth Used:

• For analytical performance studies (Detection Limit, Analytical Specificity, Assay Cut-off), the ground truth would typically be established using:
  • Known concentrations: Samples (serum/plasma) spiked with known, precise concentrations of cTnl, CK-MB, and Myoglobin.
  • Reference methods: Comparison against established, high-accuracy laboratory reference assays for these cardiac markers.
  • Clinical correlation: While not a direct "ground truth" for the device's output, the overall utility is "as an aid in the diagnosis of Acute Myocardial Infarction (AMI)," implying that the presence of these markers above the cutoff correlates with AMI, which would be pathology-confirmed or clinically adjudicated. However, the study supporting this 510(k) focused on analytical performance and comparison to a predicate, not clinical outcomes directly.

8. The Sample Size for the Training Set:

• Not Applicable/Not Specified. This device is a lateral-flow immunochromatographic assay, not a machine learning or AI model that requires a distinct "training set" in the conventional sense. Its "training" is inherent in the chemical and manufacturing process design to ensure appropriate binding and visual signaling at the defined cutoffs.

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

• Not Applicable/No training set in the conventional sense. As explained in point 8, this device doesn't have a "training set" like an AI algorithm. The assay's "truth" (i.e., its ability to correctly identify positive/negative samples) is built into its biochemical design and validated through analytical studies, as outlined in section 7a.

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