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MTS (MC Test Strip) Ampicilin-sulbactarn 0.016/0.08 - 256/128 ug/mL is a quantitative method intended for the in vitro determination of antimicrobial susceptbility of bacteria. MTS consists of specialized paper impregnated with a pre-defined concentration gradient of an antimicrobial agent, which is used to determine the minimum inhibitory concentration (MC) in ugimL of animicrobial agents as tested on agar media using overnight incubation and manual reading procedures. MTS Ampicillin-sulbactam at concentrations of 0.016/0.008 - 256/128 ug/mL should be interpreted at 16-20 hours of incubation.

Ampicillin-sulbactam has been shown to be active both clinically and in viro against these bacterial species according to the FDA drug approved label:

Gram-negative bacteria Enterobacter asburiae Enterobacter cloacae Escherichia coli Klebsiella aerogenes Klebsiella oxytoca Klebsiella pneumoniae Proteus mirabilis Acinetobacter baumannii/Acinetobacter calcoaceticus complex

Ampicillin'sulbactam has been shown to be active in viro only against the non-fastidious bacteria listed below according to the FDA drug approved label:

Gram-negative bacteria Morganella morganii Proteus vulgaris Providencia rettgeri Providencia stuartii

Device Description

AI/ML Overview

The provided document is a 510(k) clearance letter from the FDA for a medical device called "MTS Ampicillin-Sulbactam 0.016/0.008 - 256/128 ug/mL." This device is an antimicrobial susceptibility test (AST) system. It is important to note that this is NOT an AI-powered device, nor is it an imaging device. Therefore, many of the requested details about acceptance criteria for an AI-powered imaging device (such as multi-reader multi-case studies, expert adjudication, and ground truth for training sets) are not applicable to the information provided in this document.

However, I can extract the relevant information regarding acceptance criteria and performance as it relates to this specific type of device.

Device Description:
The MTS (MC Test Strip) Ampicillin-sulbactam is a quantitative method for in vitro determination of antimicrobial susceptibility of bacteria. It consists of specialized paper impregnated with a pre-defined concentration gradient of an antimicrobial agent to determine the minimum inhibitory concentration (MIC) in µg/mL.

Acceptance Criteria and Reported Device Performance (based on typical AST device clearance)

While the document does not explicitly state a table of "acceptance criteria" in the format typically used for AI/imaging devices, we can infer the performance validation based on the purpose of the device and information commonly required for AST device clearance. For AST devices, the primary acceptance criteria revolve around the accuracy of MIC determination when compared to a reference method.

Note: The provided document is the 510(k) clearance letter, which summarizes the FDA's decision but does not contain the full study report with detailed performance tables. To provide a complete performance table, one would typically need access to the full 510(k) submission or a summary of safety and effectiveness. However, I can infer the general categories of performance metrics considered for such devices.

Inferred Acceptance Criteria Categories for Antimicrobial Susceptibility Tests:

Acceptance Criteria Category	Typical Acceptance Metrics (Examples)	Reported Device Performance (Inferred from Clearance)
Essential Agreement (EA)	% of isolates where the MIC result is within +/- one doubling dilution of the reference method's MIC.	Implicitly met for FDA clearance. The device is cleared as "substantially equivalent," meaning its performance in determining MICs for the specified organisms and concentrations is considered acceptable and comparable to existing cleared devices. Specific EA percentages are not provided in this clearance letter.
Category Agreement (CA)	% of isolates where the interpretive category (Susceptible, Intermediate, Resistant) matches the reference method's category.	Implicitly met for FDA clearance. Clearance indicates that the device reliably assigns interpretive categories (S/I/R) based on its MIC results. Specific CA percentages are not provided in this clearance letter.
Major Discrepancies (MD)	% of isolates where the device classifies as Susceptible and the reference classifies as Resistant.	Must be within acceptable limits (typically very low, e.g., <3%). Not explicitly stated but assumed to be within FDA's acceptable range for clearance.
Very Major Discrepancies (VMD)	% of isolates where the device classifies as Resistant and the reference classifies as Susceptible.	Must be within acceptable limits (typically very low, e.g., <1.5%). Not explicitly stated but assumed to be within FDA's acceptable range for clearance.
Reproducibility	Consistency of results when tested multiple times under the same conditions.	Assumed to be met.
Growth/Viability	Ability to support growth of tested organisms and obtain measurable results.	Assumed to be met.
Stability	Performance over the product's shelf life.	Assumed to be met.

Study Details (as inferable for an AST device)

Given the nature of the device (an AST strip), the following details are based on standard practices for such submissions, rather than direct statements from this specific 510(k) letter which is a summary.

2. Sample Size and Data Provenance:

Sample Size for Test Set: Typically, for AST devices, a large number of clinical isolates (hundreds to thousands) across a diverse range of bacterial species (listed in the "Indications for Use") are tested. These would include common strains, as well as strains with varying resistance mechanisms.
Data Provenance: Studies for AST devices are generally prospective or involve retrospectively collected, well-characterized clinical isolates. Data would typically originate from multiple clinical microbiology laboratories, often in the United States, to ensure representativeness of prevalent strains and resistance patterns.

3. Number of Experts and Qualifications for Ground Truth:

Not applicable in the context of human expert review for image interpretation. For AST devices, "ground truth" is established through a reference method (e.g., broth microdilution or agar dilution according to CLSI guidelines). The "experts" involved are highly trained microbiologists or laboratory technicians who meticulously perform and interpret these reference methods. The "number of experts" isn't a direct metric as it would be for consensus reading of medical images. The quality of the reference method execution is paramount.

4. Adjudication Method for the Test Set:

Not applicable in the context of human expert review for image interpretation. Discordant results between the device and the reference method would undergo further investigation, potentially involving retesting or testing with an alternative reference method, but this is a technical reconciliation, not an expert adjudication process in an AI-imaging sense.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

No, not applicable. This device is for in vitro determination of antimicrobial susceptibility, read manually. There is no "human reader" in the context of interpreting complex images with or without AI assistance. The interpretation is comparing a measured MIC value to a clinical breakpoint.

6. Standalone (Algorithm Only) Performance:

Yes, in essence. The "standalone" performance for this device is its ability to accurately determine the MIC and the interpretive category (S/I/R) when compared directly to the reference method. The device is designed to be read manually by a trained laboratory professional who observes the ellipse of inhibition. The "performance" of the device itself determines the MIC. There's no AI algorithm here.

7. Type of Ground Truth Used:

Reference Method (e.g., CLSI-compliant Broth Microdilution or Agar Dilution): This is the gold standard for determining the MIC of an antimicrobial against a bacterial isolate. The MIC values derived from these methods, coupled with a defined set of clinical breakpoints (established by organizations like CLSI or FDA), form the ground truth for interpretive categorization (Susceptible, Intermediate, Resistant).

8. Sample Size for the Training Set:

Not applicable. This is not an AI/machine learning device that requires a "training set" in the computational sense. The "training" for such a device occurs during its development and optimization phases, where the chemical composition of the strip, the concentration gradient, and the manufacturing process are refined to ensure accurate performance. This is a chemical/biological/manufacturing optimization, not a data-driven model training.

9. How the Ground Truth for the Training Set Was Established:

Not applicable for AI training. As explained above, for device development and validation, the "ground truth" for ensuring the device's accuracy would involve extensive internal testing against established reference methods using characterized strains.

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