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The BBI-Biotech B. burgdorferi IgM Western blot kit is intended to provide supportive evidence of infection with B. burgdorferi by determining the specific protein reactivities of human serum specimens previously found to be reactive on enzyme immunoassay or indirect immunofluorescence screening assays. The kits will be made available to clinical laboratory professionals in public health laboratories and clinical laboratories.

The device is a collection of cGMP manufactured critical components needed to perform a Western blot test that will detect B. burgdorferi IgM antibody in naturally infected humans. It includes nitrocellulose strips upon which sodium dodecyl sulfate solubilized and polyacrylamide separated B. burgdorferi proteins have been transferred, an IgM Positive Control, a Negative Control, an anti-IgM alkaline phosphatase concentrate, a buffer concentrate, diluent powder, an NBT/BCIP substrate, Blot Reading Guide, Package Insert, and Results Record Forms.

This document describes a 510(k) submission for the BBI-Biotech B. burgdorferi IgM Western blot kit. The document lacks detailed acceptance criteria and a dedicated study section with specific performance metrics for the device. Instead, it makes a general claim of "substantial equivalence" based on comparisons with a predicate device.

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Acceptance Criteria and Reported Device Performance

The document does not explicitly state specific numerical acceptance criteria for the device's performance. Instead, it concludes the device is "substantially equivalent" to a predicate device.

Study Information

The document describes performance comparisons rather than a standalone study with defined endpoints.

1. Sample size used for the test set and the data provenance:

   • Sample Size: Not explicitly stated. The document mentions "first physician visit, verified infected patient samples," "randomly selected enzyme immunoassay positive patient samples," "blood samples from random blood donors," and "patients with syphilis antibody, rheumatoid arthritis, and systemic lupus erythematosus." However, the exact number of samples in each category is not quantified.
   • Data Provenance: Not explicitly stated (e.g., country of origin). The data appears to be retrospective, as it refers to "verified infected patient samples" and "previously found to be reactive" samples.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • Not mentioned. The document refers to "verified infected patient samples" but does not specify how this verification was performed or by whom.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not mentioned.

4. If a multi-reader multi-case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No. This device is an in-vitro diagnostic (IVD) kit for laboratory use, not an AI-assisted diagnostic tool that would typically involve human readers in this context.

5. If a standalone (i.e. algorithm only without human-in-the loop performance) was done:

   • This is an IVD kit, which inherently operates as a "standalone" test performed in a lab setting, where a technician interprets the Western blot bands according to a provided "Blot Reading Guide" and "positive interpretation criterion." The document does not describe a performance study in the manner typically presented for software algorithms.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • The ground truth for "verified infected patient samples" is implied but not explicitly defined. For other samples, the ground truth is based on clinical diagnoses (syphilis antibody, rheumatoid arthritis, systemic lupus erythematosus) or donor status (random blood donors). The "first physician visit, verified infected patient samples" suggests a clinical diagnosis of infection.

7. The sample size for the training set:

   • Not mentioned. The document describes a performance comparison study, not a machine learning model requiring a distinct training set.

8. How the ground truth for the training set was established:

   • Not applicable, as no training set for a machine learning model is described.

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