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510(k) Data Aggregation
(206 days)
LIAISON PLEX Gram-Positive Blood Culture Assay
The LIAISON PLEX® Gram-Positive Blood Culture Assay (BCP), performed using the automated, sample-to-result LIAISON PLEX® System, is a qualitative multiplexed in vitro diagnostic test for the simultaneous detection and identification of selected gram-positive pathogens and/or selected genetic determinants associated with antimicrobial resistance in positive blood culture bottles. BCP is performed directly on blood culture media using blood culture bottles identified as positive by a continuous monitoring blood culture system and which contain gram-positive bacteria as determined by Gram stain.
The BCP Assay detects and identifies the following:
Gram Positive Resistance Markers:
- mecA/mecC
- vanA
- vanB
Genera and Species:
- Bacillus spp.
- Enterococcus faecalis
- Enterococcus faecium
- Listeria spp.
- Staphylococcus spp.
- Staphylococcus aureus
- Staphylococcus epidermidis
- Staphylococcus lugdunensis
- Streptococcus spp.
- Streptococcus agalactiae
- Streptococcus anginosus group
- Streptococcus pneumoniae
- Streptococcus pyogenes
Negative results for antimicrobial resistance genes do not indicate bacterial susceptibility as there are multiple mechanisms that can contribute to resistance.
The LIAISON PLEX® BCP Assay contains targets for the detection of genetic determinants associated with resistance to methicillin (mecA/C) and vancomycin (vanA and vanB) to aid in the identification of potentially antimicrobial-resistant organisms in positive blood culture samples. In mixed growth, the LIAISON PLEX BCP Assay does not specifically attribute vanA/vanB-mediated vancomycin resistance to either E. faecalis or E. faecium, or mecA/mecC-mediated methicillin resistance to either Staphylococcus spp., S. aureus, S. epidermidis or S. lugdunensis.
The antimicrobial resistance gene or marker detected may or may not be associated with the agent responsible for disease. Negative results for these select antimicrobial resistance gene and marker assays do not indicate susceptibility, as multiple mechanisms of methicillin and vancomycin resistance exist.
The LIAISON PLEX® BCP Assay is indicated for use in conjunction with other clinical and laboratory findings to aid in the diagnosis of bacterial bloodstream infections (BSI). The LIAISON PLEX® BCP Assay is not intended to monitor these infections. Sub-culturing of positive blood cultures is necessary to recover organisms for antimicrobial susceptibility testing (AST), for identification of organisms not detected by the LIAISON PLEX BCP Assay, to detect mixed infections that may not be detected by the LIAISON PLEX BCP Assay, for association of antimicrobial resistance genes to a specific organism, or for epidemiological typing.
The LIAISON PLEX® Gram-Positive Blood Culture Assay (BCP Assay) is an automated test for the detection and identification of nucleic acid from gram-positive bacteria in a positive blood culture media sample. The BCP Assay is performed directly on blood culture media using blood culture bottles identified as positive by a continuous monitoring blood culture system, and which contain gram-positive bacteria, as determined by a Gram stain.
The LIAISON PLEX® System is a fully automated, bench-top "sample-to-answer" device that performs sample preparation and microarray-based hybridization for the detection of target-specific nucleic acids. The test reagents are supplied as a single, disposable test cartridge. Target amplification is not performed as part of the BCP Assay workflow, as it is a non-amplified, direct detection test performed on the LIAISON PLEX® System.
The provided text describes the acceptance criteria and the study that proves the LIAISON PLEX® Gram-Positive Blood Culture Assay meets those criteria. However, it's important to note that this document is a 510(k) Clearance Letter and 510(k) Summary, which focuses on demonstrating substantial equivalence to a predicate device for regulatory clearance. It is not an academic paper detailing a clinical trial with specific acceptance criteria that would typically be associated with AI/ML diagnostic performance metrics like those in a multi-reader multi-case (MRMC) study or the establishment of ground truth by multiple experts.
The study described here is for an in vitro diagnostic test for the detection of nucleic acid sequences, not for an AI/ML-based diagnostic imaging device. Therefore, many of the requested points (e.g., number of experts for ground truth, adjudication method, MRMC study, human reader improvement with AI assistance) are not applicable to this type of device and study.
I will interpret the provided information in the context of the device described (a multiplex nucleic acid assay) and its verification and validation.
Acceptance Criteria and Device Performance
The acceptance criteria for this device are implicitly derived from the performance goals demonstrated in the analytical and clinical studies, aiming for high sensitivity and specificity in detecting specified microorganisms and resistance markers. The reported performance is presented in several tables throughout the document.
Table 1: Acceptance Criteria (Implicit) and Reported Device Performance
Performance Metric Category | Specific Metric (Implicit Acceptance Criteria) | Reported Device Performance | Reference Table(s) in Document |
---|---|---|---|
Analytical Performance | |||
Precision/Reproducibility | High site-to-site reproducibility across multiple operators and sites (e.g., >95% agreement) | 99.7% overall reproducibility (95% CI: 99.3% - 99.9%) across 3 external sites and 1 internal site. | Table 1 (Site-to-Site Reproducibility) |
High within-laboratory precision/repeatability (e.g., >95% agreement) | 100% within-laboratory precision/repeatability (95% CI: 97.9% - 100%) | Table 2 (Within-Laboratory Precision/Repeatability) | |
High lot-to-lot reproducibility (e.g., >95% agreement) | 100% lot-to-lot reproducibility (95% CI: 92.1% - 100%) | Table 3 (Lot-to-Lot Reproducibility) | |
Growth & Detection | 100% detection of target organisms at ring positivity and 8 hours post-ring positivity | 100% positivity for target positive samples | Table 5 (Growth & Detection Results) |
Analytical Reactivity | High inclusivity for diverse strains of target organisms (e.g., 100% detection) | Generally 100% detection across tested strains (some minor exceptions noted for specific strains/targets, e.g. S. mutans, E. faecium FP) | Table 6 (Microorganism Markers Inclusivity), Table 7 (Resistance Markers Inclusivity) |
Analytical Specificity | Low cross-reactivity with off-panel organisms (e.g., no detection) | 97 of 103 off-panel species showed no cross-reactivity; 5 showed cross-reactivity with one reportable target; 1 showed positivity in 1/6 replicates. | Table 9 (Cross Reactivity Summary) |
Interference | No significant interference from co-infections, microbial interference, or interfering substances | 100% positivity for on-panel targets in presence of co-infections/off-panel microbes. 0% for negative samples. 100% target detection with all interfering substances. | Table 12 (Competitive Inhibition), Table 13 (Microbial Interference), Table 14 (Interfering Substances) |
Carry-Over/Cross Contamination | No carry-over or cross-contamination | 100% agreement between expected and observed results, indicating no cross-contamination. | Table 15 (Carry-Over/Cross Contamination) |
Clinical Performance | |||
Sensitivity (PPA) | High PPA for all target organisms and resistance markers | Ranges from 88.9% (Streptococcus anginosus group prospective) to 100% for most targets (Combined Data). | Table 20 (Clinical Performance - Combined Specimens), Table 22 (Contrived Data Set) |
Specificity (NPA) | High NPA for all target organisms and resistance markers | Ranges from 95.7% (mecA/mecC prospective) to 100% for most targets (Combined Data). | Table 20 (Clinical Performance - Combined Specimens), Table 22 (Contrived Data Set) |
2. Sample Sizes and Data Provenance
- Test Set (Clinical Study):
- Prospective Arm (Arm 1): 562 unique specimens enrolled, 509 included in analysis.
- Pre-selected Arm (Arm 2): 163 pre-selected left-over specimens, 162 included in analysis.
- Contrived Arm (Arm 3): 225 contrived specimens.
- Total specimens analyzed for clinical performance: 509 (prospective) + 162 (pre-selected) + 225 (contrived) = 896 unique samples.
- Data Provenance:
- Prospective Arm: Collected between April 2024 and August 2024 from four geographically diverse clinical sites within the United States. Data is prospective.
- Pre-selected Arm: Sourced from ten vendors in the United States and one site in Italy. Data are retrospective (left-over, de-identified specimens).
- Contrived Arm: Specimens were prepared, blinded, randomized, and tested at three external testing sites and one internal testing site between June 2024 to September 2024. These are contrived (synthetic) samples.
3. Number of Experts and Qualifications for Ground Truth
- Not Applicable in the traditional sense for this IVD device. The ground truth for this nucleic acid assay is established through reference methods such as culture with automated microbiological/biochemical identification (VITEK 2), PCR followed by bi-directional sequencing (BDS), or a combination thereof. This is a laboratory-based diagnostic test, not an imaging device requiring human expert interpretation for ground truth.
4. Adjudication Method for the Test Set
- Not Applicable in the traditional sense. The "adjudication" for the gold standard (reference method) involves a hierarchical algorithm (Table 19). If initial VITEK 2 results were insufficient or for specific targets like Bacillus spp. and resistance markers (mecA/mecC, vanA, vanB), PCR followed by bi-directional sequencing was used. This is a technical validation process against established laboratory methods rather than a consensus among clinical experts interpreting an output.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
- Not done. This type of study (MRMC) is typically used for diagnostic imaging devices where human readers interpret images with and without AI assistance. This device is a molecular diagnostic assay that provides direct results, and therefore, an MRMC study is not relevant.
6. Standalone (i.e., algorithm only without human-in-the-loop performance)
- Yes, in essence. The LIAISON PLEX® BCP Assay is an automated, sample-to-result system. Its performance (sensitivity, specificity) is evaluated independently against a reference method. While trained operators are involved in loading samples and running the system, the diagnostic result itself is generated by the "system" (instrument + assay + software algorithm) without human diagnostic interpretation of the raw signal data.
7. The Type of Ground Truth Used
- Laboratory Reference Methods:
- Culture followed by Automated microbiological/biochemical identification using VITEK 2 for most bacterial species.
- PCR followed by bi-directional sequencing (BDS) for Bacillus spp. and resistance markers (mecA/mecC, vanA, vanB). This method was also used to confirm discordant results or for targets with low prevalence in initial testing.
- In some cases, MALDI-ToF assay (Matrix-Assisted Laser Desorption/Ionization-Time Of Flight) was also mentioned as a Standard of Care method in the footnotes for discordant result explanations.
8. The Sample Size for the Training Set
- Not explicitly stated in terms of a "training set" for an AI/ML model. This device is a direct detection assay based on hybridization, not a machine learning model that undergoes a training phase with a distinct dataset. Therefore, the concept of a "training set" in the context of data used to train an AI model is not applicable to this traditional IVD. The development process would involve extensive analytical characterization, probe design, and optimization using various microbial strains and clinical samples, but this is distinct from "training data" for an AI algorithm.
9. How the Ground Truth for the Training Set Was Established
- Not applicable for this type of device. As explained above, this is not an AI/ML device that requires a "training set" with ground truth established in the AI/ML context. The assay's design and optimization would rely on established microbiological methods and genetic sequencing to define target sequences and ensure specificity and inclusivity.
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