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510(k) Data Aggregation
(66 days)
GNR
The ViraSTAT® FITC-Labeled Anti-Influenza test panel is intended for the qualitative detection and confirmation of influenza A and B virus isolates from infected cell cultures through the use of the ViraSTAT® FITC-Labeled Anti-Influenza Pool and the identification and confirmation of influenza A and B by typing with separate ViraSTAT® FITC-Labeled Anti-Influenza type A or B, monoclonal antibodies, respectively. Performance characteristics have not been established for direct specimen staining.
The ViraSTAT® FITC-Labeled Anti-Influenza A and B monoclonal antibodies are fluorescently-labeled antibodies for use in culture confirmation of influenza A and B infections, respectively, in standard cell culture. The virus to be detected is grown in the appropriate cell culture system, fixed on a slide or coverslip and then the cell preparation is stained with the fluorescently-labeled monoclonal antibody. The stained sample is then viewed under a fluorescent microscope for a positive or negative identification. A positive sample is determined when cells displaying typical apple-green fluorescence are observed. Fluorescence may be present in the nucleus alone, in the nucleus and the cytoplasm, or in the cytoplasm alone. A negative sample is determined when slide wells or coverslips show no specific apple-green fluorescence in the cells and have at least 50 intact red counterstaining cells per well or 50% of the monolayer remaining on the coverslips or slides that are counterstained red.
Here's a breakdown of the acceptance criteria and study details for the ViraSTAT® FITC-Labeled Anti-Influenza A and B Monoclonal Antibodies:
1. Acceptance Criteria and Reported Device Performance
The documentation doesn't explicitly state quantitative acceptance criteria (e.g., "Sensitivity must be > 95%"). Instead, it states the performance of the ViraSTAT® device should be "equivalent to" the predicate devices. The reported performance details indicate that this equivalence was achieved:
Acceptance Criteria (Implicit) | Reported Device Performance (ViraSTAT®) |
---|---|
Sensitivity for Influenza A | |
(compared to reference antibodies) | 100% (all 363 influenza A specimens identified by reference antibodies were positive with ViraSTAT®) |
Sensitivity for Influenza B | |
(compared to reference antibodies) | 100% (all 99 influenza B specimens identified by reference antibodies were positive with ViraSTAT®) |
Specificity for Influenza A and B | |
(compared to reference antibodies) | 100% (all 500 influenza-negative specimens identified by reference antibodies were negative with ViraSTAT®) |
Cross-reactivity | No cross-reactivity observed between Anti-Influenza A and Anti-Influenza B antibodies. No reaction with other non-influenza viruses. |
Interpretation: The ViraSTAT® device demonstrated 100% agreement with the reference monoclonal antibodies for both positive and negative influenza A and B samples, and showed no cross-reactivity, thus meeting the implicit acceptance criterion of "equivalence."
2. Sample Size and Data Provenance
- Test Set Sample Size: 962 culture isolates.
- 363 identified as influenza A
- 99 identified as influenza B
- 500 identified as influenza-negative
- Data Provenance: The majority (944) were culture isolates from fresh throat swab specimens. The rest were from frozen isolates. No country of origin is specified, but the submission is to the FDA in the USA. The study appears to be retrospective, using collected culture isolates. Four test sites were involved.
3. Number of Experts and Qualifications for Ground Truth
The document does not explicitly state the number or specific qualifications of experts used to establish the ground truth for the test set. The ground truth was established by "commercially available 510(k) marketing-cleared monoclonal antibodies" from Bartels' Viral Respiratory Screening and Identification Kit and Dako's Imagen Influenza A and B Kit. It is implied that these reference methods were interpreted by trained laboratory personnel.
4. Adjudication Method
The document does not describe an adjudication method for the test set. The performance was directly compared against the results from the predicate (reference) antibodies.
5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study
No MRMC comparative effectiveness study was done. This study focuses on the standalone performance of the diagnostic antibodies against established reference antibodies, not on reader performance with or without AI assistance.
6. Standalone (Algorithm Only) Performance
Yes, a standalone study was performed. The "device" in this context refers to the antibody reagents. The performance data presented (sensitivity and specificity) are a direct comparison of how well the ViraSTAT® antibodies perform on culture isolates compared to the reference antibodies, without human-in-the-loop assistance influencing the antibody reaction. Human interpretation of the stained cells under a fluorescent microscope is still required, but the performance of the reagent itself is what's being evaluated as standalone.
7. Type of Ground Truth Used
The ground truth used was established by reference methods/predicate devices, specifically "commercially available 510(k) marketing-cleared monoclonal antibodies" (Bartels' Viral Respiratory Screening and Identification Kit and Dako's Imagen Influenza A and B Kit) used on cell culture isolates. This could be considered a form of expert consensus or established laboratory standard as these predicate devices themselves would have undergone validation.
8. Sample Size for Training Set
The document does not mention a separate "training set" or its sample size. This type of device (monoclonal antibodies) typically doesn't involve machine learning models that require training sets in the same way modern AI algorithms do. The "development" of the antibodies would involve laboratory work to select and validate clones, but this is distinct from how an AI training set is generally discussed. The 962 culture isolates would be considered the clinical performance validation set.
9. How Ground Truth for Training Set Was Established
As there is no explicit training set in the context of AI/machine learning, this question is not directly applicable. The "ground truth" for the development of the antibodies (e.g., confirming their binding specificity) would have been established through standard immunological and virological laboratory techniques using known influenza A and B strains and other non-influenza viruses.
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