(62 days)
This submission is for Etest® Tobramycin for MIC determinations across 0.016-256 ug/ml. and 0.064-1024 ug/mL vith Staphylowouns aureus, Enterbacteriareae and P. aerweinosa.
Etest® is a quantitative technique for determination of antimicrobial susceptibility of both nonfastidious Gram negative and Gram posstive aerobic bacteria such as Enterbacteriateae. Pseudomonas, Staphylococus and Entervocus species and fastidious bacteria, such as anaerobes, N. gonorrhoeae, S. pneumoniae, Streptorocus and Haemophilus species. The system comprises a predefined antibiotic gradient which is used to determine the Minimum Inhibitory Concentration (MIC) in ug/mL of different antimicrobial agents against microorganisms as tested on agar using overnight incubation.
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This document is a 510(k) clearance letter for the Etest Tobramycin, an antimicrobial susceptibility test. It confirms that the device is substantially equivalent to legally marketed predicate devices. However, the letter itself does not contain the detailed acceptance criteria or the study results that prove the device meets those criteria.
To answer the requested questions, one would typically need to refer to the actual 510(k) submission document (K102668), which would include the performance data and the study design. The provided text is only the FDA's clearance letter.
Therefore, many of the questions cannot be fully answered from this document alone. I will indicate where the information is missing.
Here's an attempt to answer based on the provided text and general knowledge about 510(k) submissions for similar devices:
Acceptance Criteria and Device Performance (Based on Inferred Information for AST Devices)
Since this is an Antimicrobial Susceptibility Test (AST), the acceptance criteria typically involve demonstrating substantial equivalence to a predicate device in accurately determining the Minimum Inhibitory Concentration (MIC) of an antibiotic against various microorganisms. This is usually assessed by comparing the agreement rates (Essential Agreement and Category Agreement) between the new device and a reference method (e.g., broth microdilution or agar dilution).
Table of Acceptance Criteria and Reported Device Performance (Inferred)
| Metric | Acceptance Criteria (Typical for AST Devices) | Reported Device Performance (Missing from document, would be in 510k submission) |
|---|---|---|
| Essential Agreement (EA) | ≥ 90% (e.g., within +/- 1 doubling dilution) | Not reported in this clearance letter |
| Category Agreement (CA) | ≥ 90% | Not reported in this clearance letter |
| Major Discrepancies (MD) | ≤ 3% | Not reported in this clearance letter |
| Very Major Discrepancies (VMD) | ≤ 1.5% | Not reported in this clearance letter |
Note: The specific percentages for acceptance criteria can vary slightly based on the drug, organism, and regulatory guidance at the time.
Study Information
Due to the limited information in the clearance letter, many sections will indicate "Not specified in this document."
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Sample size used for the test set and the data provenance:
- Sample Size (Test Set): Not specified in this document. A typical AST submission would involve hundreds to thousands of isolates for each drug/organism combination tested.
- Data Provenance: Not specified in this document, but typically includes various clinical isolates from diverse geographical regions and a collection of challenge isolates. Usually, AST studies are prospective or a combination of retrospective (archived isolates) and prospective.
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Number of experts used to establish the ground truth for the test set and the qualifications of those experts:
- Number of Experts: Not applicable in the traditional sense for AST device ground truth.
- Qualifications of Experts: The "ground truth" for AST devices is generally established by a reference method (e.g., Clinical and Laboratory Standards Institute (CLSI) broth microdilution or agar dilution method) performed by trained microbiologists following standardized protocols. It doesn't rely on expert consensus in the same way an imaging study would.
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Adjudication method for the test set:
- Not applicable as the ground truth is determined by a reference method, not expert adjudication. Discrepancies between the candidate device and the reference method are analyzed, but not adjudicated in the sense of reaching a consensus different from the reference.
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If a multi-reader multi-case (MRMC) comparative effectiveness study was done:
- No. MRMC studies are primarily relevant for imaging interpretation where human readers are assessing cases. For an AST device, the "reading" is the MIC determination, and the performance is measured against a reference method, not against multiple human interpreters of the device itself.
- Effect size of how much human readers improve with AI vs without AI assistance: Not applicable. This device is not an AI-assisted diagnostic tool for human interpretation.
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If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:
- Yes, in essence. The Etest is a standalone test method. The performance evaluation (comparison to the reference method) typically assesses the device's ability to produce an accurate MIC reading independently. While human technicians read the Etest strips, the "algorithm" is the predefined antibiotic gradient and the interpretative breakpoints. The study evaluates the output of this system.
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The type of ground truth used:
- Reference Method (e.g., CLSI Broth Microdilution or Agar Dilution): This is the standard "ground truth" for AST devices. This reference method is considered the gold standard for determining the true MIC of an antimicrobial against a microorganism.
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The sample size for the training set:
- Not applicable in the traditional sense for this type of device. Etest relies on a predefined antibiotic gradient impregnated on a strip. It's not a machine learning model that requires a distinct "training set" to learn parameters. The development of Etest (determining appropriate antibiotic concentrations and strip design) would have involved extensive R&D and optimization, but not a "training set" for an algorithm in the AI sense.
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How the ground truth for the training set was established:
- Not applicable as there is no "training set" in the machine learning context for this device. The physical and chemical properties of the Etest strip, and the interpretation rules, are based on established microbiological principles.
§ 866.1640 Antimicrobial susceptibility test powder.
(a)
Identification. An antimicrobial susceptibility test powder is a device that consists of an antimicrobial drug powder packaged in vials in specified amounts and intended for use in clinical laboratories for determining in vitro susceptibility of bacterial pathogens to these therapeutic agents. Test results are used to determine the antimicrobial agent of choice in the treatment of bacterial diseases.(b)
Classification. Class II (performance standards).