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MRSA/SA ELITe MGB® is a qualitative in vitro diagnostic test for the direct detection of Staphylococcus aureus (SA) and methicillin-resistant Staphylococcus aureus (MRSA) using DNA purified from nasal swabs. MRSA/SA ELITe MGB® is intended to aid in the prevention and control of MRSA infections in healthcare settings. It is not intended to diagnose, guide or monitor MRSA infections, or provide results of susceptibility to oxacillin/methicilliin. A negative result does not preclude MRSA/SA (Staphylococcus aureus) nasal colonization. Concomitant cultures are necessary to recover organisms for epidemiological typing or for further susceptibility testing.

Special conditions for use statement(s): Prescription Use Only.

MRSA/SA ELITe MGB® is a real-time, multiplex polymerase chain reaction (PCR) assay for the in vitro qualitative detection of MRSA and SA DNA extracted from human nasal swab samples. In this system, sample preparation and amplification/real-time detection are completed on separate instruments. Sample processing is completed on the bioMérieux NucliSENS® easyMAG® instrument with bioMérieux NucliSENS Nucleic Acid Extraction Reagents according to the manufacturer's instructions. Following processing, the extracted sample is placed in the well of a 96 well plate to which "monoreagent" is added. The monoreagent contains the primers and probes for the genes of interest and the internal control combined with master mix. The assay is performed on an Applied Biosystems 7500 FAST Dx System that consists of the 7500 FAST Dx instrument, a personal computer, 96-well plates and seals. The total system run time is 150 minutes consisting of 60 minutes for sample processing and about 90 minutes for the real time amplification and detection steps. The instrument never comes into contact with any fluids within the 96-well plate. Each disposable plate is intended to test up to 96 samples, controls or any mixture thereof. The 96-well plates are not re-usable and are specific to the system. The kit contains enough reagents for 100 reactions. One positive and one negative control are required for each PCR run; a Negative Processing Control and a Positive Processing Control are recommended to be run in each extraction run. The design of the assay includes systems to identify both the gene responsible for methicillin resistance and for a conserved portion of a gene unique to S. aureus. Thus, for a true "MRSA," both targets will be identified in roughly equal proportions. Results are determined by using an algorithm that compares output. Cq, from the cycler (called Ct in the output from the cvcler.) The algorithm is implemented for automatic results determination by analyzing the output Cq with ELITe MGB® software.

The provided text describes the acceptance criteria and the study that proves the performance of the MRSA/SA ELITe MGB® Software, which is a software component of the overall MRSA/SA ELITe MGB® test system. It's important to note that this 510(k) submission (K132468) is specifically for the software that automates the calling algorithm, not the entire diagnostic test kit, which was previously cleared under K112937. Therefore, most performance studies (analytical sensitivity, reactivity, detection limit, reproducibility, carry-over/cross-contamination, clinical studies) are referenced back to the original K112937 submission as they are not affected by the software change.

Here's a breakdown of the requested information based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

For this specific 510(k) (K132468), the primary acceptance criterion is the concordance of results generated by the new automated software with the results generated by the previously cleared manual calling algorithm.

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

The document states, "In accordance with guidance received from FDA in Q120176, the original data from K112937 was recalculated using ELITe MGB software."

• Sample Size for Test Set: The specific sample size used for the recalculation is not explicitly stated in this document but is referred to as "the original data from K112937." To determine the exact sample size, one would need to review the K112937 submission.
• Data Provenance: The data is "original data from K112937," implying it was generated during the studies for the initial clearance of the MRSA/SA ELITe MGB® assay. The document doesn't specify the country of origin of the data or whether it was retrospective or prospective, though diagnostic assay validation studies typically involve prospective collection of samples or a combination of prospective and banked (retrospective) samples.

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

This specific submission (K132468) is evaluating the concordance of software interpretation with a manual interpretation algorithm from K112937, rather than establishing a new ground truth against a clinical "gold standard." Therefore, the concept of "experts establishing ground truth" in the traditional sense doesn't directly apply here. The manual calling algorithm itself represents the established interpretation logic from the previous clearance.

4. Adjudication Method for the Test Set

Not applicable for this type of software validation study. The study involved a direct comparison of algorithmic output with the output of a previously defined manual algorithm. There was no "adjudication" between different human interpretations or human and AI interpretations in this specific study.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done for this software submission. The purpose of this submission was to validate the automated software's agreement with the manual algorithm, not to compare human performance with or without AI assistance.

6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

Yes, this study is inherently a standalone performance evaluation of the algorithm. The software (algorithm) processes the raw data and determines results automatically. The evaluation compares these automated results directly against the results that would have been obtained by applying the manual algorithm from the predicate device's labeling to the same raw data. There is no human "in the loop" performing interpretation for this part of the study; the software automates the interpretation step.

7. The Type of Ground Truth Used

The "ground truth" for this software validation study is the results derived from the manual calling algorithm as described in the labeling of the predicate device (K112937). It's a comparison to an established interpretation method, not directly to pathology, outcomes data, or expert consensus in the typical sense.

8. The Sample Size for the Training Set

The document states, "The development of the software is in compliance with the requirements of the Guidance. The performance of the software has been validated." However, it does not explicitly mention a separate "training set" size for the ELITe MGB® software development. Software for diagnostic devices generally undergoes rigorous development and verification, which might involve internal testing with various data, but the specific size of such an internal training set is not provided here. The critical performance evaluation (concordance) was done on the original data from K112937.

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

Given that a specific "training set" size is not detailed for this software validation, the method for establishing its ground truth is also not elaborated. For the underlying MRSA/SA ELITe MGB® assay (K112937), the ground truth for clinical performance would have been established through methods like confirmatory microbiology cultures, potentially with additional molecular or phenotypic characterization for MRSA distinction, which are standard for such diagnostic tests. The software's "training" (development) would have been guided by the established rules of the manual calling algorithm.

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