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The Sensititre® Haemophilus influenza/Streptococcus pneumoniae (HP) MIC susceptibility plates and Justone are in vitro diagnostic products for quantitatively and or qualitative susceptibility testing of isolated colonies of Haemophilus influenzae, Streptococcus pneumoniae and Streptococcus species from clinical specimens.

Plates can either be read manually or automatically on the Sensititre Autoreader and/or ARIS with Streptococcus pneumoniae and Streptococcus species and manually with H. influenzae. The JustOne® strip can only be read manually.

This 510(k) is for the addition of Tigecycline in the dilution range of 0.004 - 8 µg/ml for testing Streptococcus pneumoniae isolates on the Sensititre® (HP) MIC susceptibility system. The additional approved primary "Indications for Use" and clinical significance of Tigecycline is for:

Aerobic facultative Gram-positive microorganisms Streptococcus pneumoniae (Penicillin susceptible stains only)

Not Found

The information provided is a 510(k) premarket notification letter from the FDA, approving the Sensititre® Haemophilus influenza/Streptococcus pneumoniae (HP) MIC susceptibility plates, Tigecycline (0.004 - 8ug/mL). This document primarily contains the regulatory approval status and indications for use. Key information about the device's performance study and acceptance criteria is not explicitly detailed in the provided text.

Specifically, the document states:

• The device is an in vitro diagnostic product for susceptibility testing.
• The 510(k) is for the addition of Tigecycline in the dilution range of 0.004 - 8 µg/ml for testing Streptococcus pneumoniae isolates.
• The additional approved primary "Indications for Use" and clinical significance of Tigecycline is for Streptococcus pneumoniae (Penicillin susceptible stains only).

To address your request, I will outline the typical information that would be found in a study report for such a device, and explicitly state what is missing from this FDA letter.

Missing Information:

The provided text does not contain any details about the acceptance criteria, the specific study conducted, sample sizes, data provenance, ground truth establishment, or any comparative effectiveness studies. These details would typically be found in the 510(k) submission itself or a separate study report, which is not included here.

Therefore, the following sections will indicate where the requested information would normally be found or what typical approaches are used for such devices, and will explicitly state that the specific details are not available in the provided document.

Acceptance Criteria and Reported Device Performance

Specific data for acceptance criteria and reported device performance are NOT available in the provided text.

For an antimicrobial susceptibility test (AST) device like the Sensititre® plates, the acceptance criteria would typically focus on agreement rates with a predicate method (e.g., broth microdilution) for categorical agreement (Sensitive, Intermediate, Resistant) and essential agreement (within +/- 1 dilution).

A hypothetical table showing typical acceptance criteria and what would be reported for an AST device:

Study Details (Information NOT in provided document)

Since the specific study details are not in the provided 510(k) letter, I will indicate typical practices for such studies.

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

   • Sample Size: For an AST device for a specific drug/organism combination (like Tigecycline for S. pneumoniae), the test set would typically involve a minimum of 200-300 isolates of the target organism, with a sufficient distribution across susceptible, intermediate, and resistant categories (if applicable for the drug). This would include both challenge strains (well-characterized strains with known resistance mechanisms) and clinical isolates.
   • Data Provenance: The isolates would typically come from multiple clinical laboratories within the United States (and potentially other countries like Canada or Europe) to ensure diversity. The data would be prospective or retrospective clinical isolates collected and tested according to a predefined protocol.

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

   • Number of Experts: For AST devices, "experts" in the traditional sense of clinicians or radiologists is less applicable for ground truth determination. Instead, the "ground truth" (reference method) is established by following standardized, well-accepted laboratory procedures (e.g., CLSI broth microdilution or agar dilution methods). The personnel performing these reference tests would be highly trained microbiologists or laboratory technicians with extensive experience in antimicrobial susceptibility testing, often adhering to Good Laboratory Practices (GLP). Sometimes, a single expert or supervisor might oversee the reference testing.
   • Qualifications of Experts: Clinical microbiologists or laboratory scientists with 5+ years of experience in antimicrobial susceptibility testing according to CLSI or ISO standards.

3. Adjudication method for the test set:

   • Adjudication Method: For AST devices, adjudication is typically not done through multiple human readers in the same way it would be for imaging studies. Instead, discrepancies between the investigational device and the reference method are investigated by repeat testing or by using an alternative reference method. If a discrepancy persists, the isolate might be retested on both systems, or a third, highly reliable method might be used to confirm its true susceptibility profile.

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:

   • MRMC Study: Highly unlikely for this type of device. MRMC studies are primarily relevant for imaging diagnostics where human interpretation plays a significant role and AI is often used as an aid for readers. This device is an in vitro diagnostic for automated or manual reading of microbial growth, not for human interpretation of complex images. Therefore, the concept of "improving human readers with AI assistance" is not applicable here.

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

   • Standalone Performance: Yes, in a way. The performance of the Sensititre® plates, whether read manually or automatically (Sensititre Autoreader and/or ARIS), is assessed against the reference method. The "algorithm" here refers to the system's ability to accurately determine MICs and categorize susceptibility based on microbial growth, independent of human interpretive bias. The study focuses on the accuracy of the device itself to produce the correct susceptibility result.

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

   • Ground Truth: For AST devices, the ground truth is established by a conventional, well-established reference method, most commonly the Clinical and Laboratory Standards Institute (CLSI) broth microdilution method or agar dilution method. This is considered the "gold standard" for determining bacterial susceptibility to antimicrobials in vitro. It is not expert consensus, pathology, or outcomes data.

7. The sample size for the training set:

   • Training Set Sample Size: Not applicable in the typical sense for this specific device. The Sensititre® plates are a phenotypic test system, not an AI or machine learning algorithm that requires a "training set" of data to learn patterns. The "development" of the plate involves extensive in-house testing to ensure accurate dilution ranges, media composition, and stable drug concentrations, but this isn't a "training set" like in deep learning. If the auto-reader component were using AI/ML, then a training set would be relevant for that specific aspect, but the primary device (the plate itself) doesn't use one.

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

   • Ground Truth for Training Set: Not applicable as there is no "training set" for the Sensititre® plates themselves in the machine learning sense. The reference method would be used during the validation of the full system (plate + reader) and during the initial development phases to ensure the plate's inherent accuracy.

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