A clinically relevant reinterpretation of disk approximation testing for inducible AmpC in Pseudomonas aeruginosa
Arturo Reyes-Gualito1, Luis Raúl Rivera-Garay1, Azyadeh Cobo-Alva1
1Microbiology Laboratory, Clinical Analysis of León, HRAEB Unit, León, Guanajuato, México.
Introduction:
Current antimicrobial susceptibility methods fail to capture the variability of AmpC induction pathways in Pseudomonas aeruginosa. This leads to preventable errors in ceftazidime susceptibility reporting. We introduce a reinterpretation for the disk approximation test, based on the categorical change in ceftazidime susceptibility upon imipenem exposure.
Materials And Methods:
A total of 73 ceftazidime-susceptible P. aeruginosa isolates were evaluated. Automated broth microdilution test was the reference standard. AmpC inducibility was conventionally defined as a ≥5 mm flattening of the ceftazidime inhibition zone adjacent to imipenem. Our novel criterion for inducibility was a change in ceftazidime category from susceptible to nonsusceptible. The probability of error in ceftazidime reporting was evaluated with three parameters. ROC curve, comparative and regression analyses were performed.
Results:
The reference method showed an overall error probability of 35.6%. The conventional 5 mm cutoff interpretation reduced this rate to 5.4%, but generated a significant proportion of false positives and negatives. Regression analyses showed that the flattening effect is a strong predictor of the categorical change. No association was found between basal ceftazidime susceptibility and AmpC inducibility.
Conclusion:
Our reinterpretation criterion for disk approximation test turns a phenotypic assay into a clinically relevant diagnostic tool to avoid errors in ceftazidime susceptibility reports. Moreover, this interpretation is readily applicable in routine microbiology laboratories, and has the potential to be directly useful for antimicrobial stewardship efforts.
Insights
A new interpretation of the disk approximation test improves accuracy in reporting ceftazidime susceptibility for Pseudomonas aeruginosa. This method helps prevent errors and supports antimicrobial stewardship.
Area of Science:
- Clinical microbiology
- Antimicrobial resistance
- Diagnostic test development
Background:
- Current antimicrobial susceptibility testing methods inadequately assess AmpC induction in *Pseudomonas aeruginosa*, leading to errors in ceftazidime reporting.
- Variability in AmpC induction pathways poses a challenge for accurate susceptibility testing.
- This study addresses the need for improved methods to detect inducible AmpC production.
Purpose of the Study:
- To introduce and validate a novel interpretation criterion for the disk approximation test to improve ceftazidime susceptibility reporting in *P. aeruginosa*.
- To evaluate the clinical relevance and diagnostic accuracy of a reinterpreted disk approximation test.
- To reduce preventable errors in antimicrobial susceptibility reports.
Main Methods:
- Evaluated 73 ceftazidime-susceptible *P. aeruginosa* isolates using automated broth microdilution as the reference standard.
- Compared conventional AmpC inducibility definition (≥5 mm zone flattening) with a novel criterion based on categorical change in ceftazidime susceptibility after imipenem exposure.
- Utilized ROC curve, comparative, and regression analyses to assess error probability and predictive value.
Main Results:
- The reference method exhibited a 35.6% overall error probability.
- The conventional 5 mm cutoff interpretation reduced errors to 5.4% but yielded significant false positives/negatives.
- The novel criterion, based on categorical change, demonstrated strong predictive value for AmpC inducibility and reduced reporting errors.
Conclusions:
- Reinterpreting the disk approximation test transforms it into a clinically relevant tool for accurate ceftazidime susceptibility reporting.
- This readily applicable method in routine laboratories aids in avoiding reporting errors.
- The findings support enhanced antimicrobial stewardship by providing more reliable susceptibility data.
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