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The BD Phoenix Automated Microbiology System is intended for the in vitro rapid identification (ID) and quantitative determination of antimicrobial susceptibility by minimal inhibitory concentration (MIC) of Gram Negative aerobic and facultative anaerobic bacteria belonging to the family Enterobacteriaceae and non-Enterobacteriaceae.

BD Phoenix CPO detect is a qualitative confirmatory test that uses a growth-based algorithm intended to phenotypically detect carbapenemase-production in Enterobacteriaceae, Pseudomonas aeruginosa, and Acinetobacter baumannii on Gram-negative ID/AST or AST only Phoenix panels. The test also provides the Ambler classification (Class B and Class D) of the carbapenemase produced. One of three test configurations are available per panel for carbapenemase detection with/without Ambler classification for the target organism groups. BD Phoenix CPO detect does not report multiple classes of carbapenemases from a single isolate.

The BD Phoenix Automated Microbiology System (Phoenix System) is an automated system for the rapid identification (ID) and antimicrobial susceptibility testing (AST) of clinically relevant bacterial isolates. The system includes the following components:

• BD Phoenix instrument and software.
• BD Phoenix panels containing biochemicals for organism ID testing and antimicrobial agents for AST determinations.
• BD Phoenix ID Broth used for performing ID tests and preparing AST Broth inoculum.
• BD Phoenix AST Broth used for performing AST tests only.
• BD Phoenix AST Indicator solution added to the AST Broth to aid in bacterial growth determination.

The Phoenix panel is a sealed and self-inoculating molded polystyrene tray with 136 micro-wells containing dried reagents. Organisms for susceptibility testing must be a pure culture and preliminarily identified as a Gram-negative or Gram-positive isolate. Phoenix panels are inoculated with a specified organism density and placed into the instrument. Inoculum for use with the Phoenix system may be prepared either manually or may be automated using the BD Phoenix™ AP System.

The Phoenix AST method is a broth based microdilution test. The Phoenix System utilizes a redox indicator for the detection of organism growth in the presence of an antimicrobial agent. Measurements of changes to the indicator as well as bacterial turbidity are used in the determination of bacterial growth. Each AST panel configuration contains several antimicrobial agents with a wide range of two-fold doubling dilution concentrations.

The instrument houses the panels where they are continuously incubated at a nominal temperature of 35° ± 1°C. The instrument takes readings of the panels every 20 minutes. The readings are interpreted to give an identification of the isolate, minimum inhibitory concentration (MIC) values and category interpretations, S, I, R or N (susceptible, intermediate, resistant or not susceptible.

The provided document describes the acceptance criteria and the study that proves the device, BD Phoenix™ CPO detect - GN, meets these criteria.

Here's a breakdown of the requested information:

1. Table of Acceptance Criteria and Reported Device Performance

The document doesn't explicitly state "acceptance criteria" as a separate, defined list of numerical targets before presenting performance. However, typical acceptance criteria for such devices focus on high sensitivity (Positive Percent Agreement - PPA) and specificity (Negative Percent Agreement - NPA) for detection, and accuracy for classification. The reported performance is summarized below from the "Performance of BD Phoenix™ Automated Microbiology System for Gram-negative Organisms" and "BD Phoenix™ CPO detect: Carbapenemase Classification" tables.

Acceptance Criteria (Implied by Performance Expectations for Medical Devices) and Reported Device Performance:

Note: The "Unclassified isolates in either the Phoenix or reference system are not included in these calculations" represents a more ideal or 'clean' performance, while "All isolates are included in these performance calculations" provides a more comprehensive view, including instances where the device could not provide a classification or provided an incorrect one.

2. Sample size used for the test set and the data provenance

• Test Set Sample Size:
  • Detection of carbapenemase: 1452 isolates (Total)
  • Carbapenemase Classification (9-Well Configuration):
    • N=1357 (when unclassified isolates are excluded)
    • N=1452 (when all isolates are included)
  • Carbapenemase Classification (6-Well Configuration):
    • N=1039 (when unclassified isolates are excluded)
    • N=1099 (when all isolates are included)
• Data Provenance: The study used "Clinical fresh and stock isolates" tested across "multiple sites" and "Challenge isolates obtained from domestic and international sources." This indicates a mix of prospective (fresh clinical isolates) and retrospective (stock isolates, challenge isolates) data, collected from various geographical locations (domestic and international).

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

The document does not specify the number of experts or their qualifications for establishing the ground truth. It refers to a "composite reference method" and "Phenotypic testing" and "Genotypic testing," which suggests laboratory-based methods rather than human expert reads of images, as might be typical for AI in imaging.

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

Not applicable in the context described. The ground truth was established by laboratory methods (phenotypic and genotypic testing), not by multiple human readers requiring adjudication.

5. 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, an MRMC comparative effectiveness study was not done. This device is an automated microbiology system for detecting carbapenemase production and classification, not an AI for assisting human readers in interpreting medical images. Therefore, the concept of human readers improving with AI assistance does not apply here.

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

Yes, the study describes the standalone performance of the BD Phoenix™ CPO detect system. The performance metrics (PPA, NPA) are presented for the device against the established ground truth, indicating its ability to detect and classify carbapenemase production without direct human intervention in the interpretation of the results from the system itself.

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

The ground truth was a composite reference method combining:

• Phenotypic testing: CLSI-recommended modified Carbapenem Inactivation Method (mCIM) assay and carbapenem MIC results.
• Genotypic testing: Multiplex PCR for detection of genes to assign Ambler classification (Class A, B, D).

8. The sample size for the training set

The document does not specify the sample size for a training set. Given that this is a "growth-based algorithm" for an automated microbiology system and not necessarily a machine learning model trained on a large dataset of prior test results or images, the concept of a distinct 'training set' for an AI algorithm might not apply in the conventional sense of deep learning. The system's "algorithm" is likely based on established microbiological principles and a decision tree derived from growth patterns and biochemical reactions rather than iterative training on labeled data in the way modern AI models are.

9. How the ground truth for the training set was established

As the concept of a distinct 'training set' for an AI algorithm is not explicitly detailed or conventionally applied here for this type of device, the method for establishing ground truth for a training set is not described in the document. The description focuses on the validation of the device's performance against reference methods.

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