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Published on: February 22, 2019
Missed pertussis diagnosis during co-infection with Bordetella holmesii
Mikaël de Lorenzi-Tognon1,2, Yannick Charretier3, Anne Iten4
1Division of Infectious Diseases, Department of Medicine, Geneva University Hospitals, Geneva, Switzerland. mikael.tognon@me.com.
Abstract:
The purpose of this study is to identify predictive factors associated with missed diagnosis of B. pertussis-B. holmesii co-infection by assessing the analytical performance of a commercially available multiplexed PCR assay and by building a prediction model based on clinical signs and symptoms for detecting co-infections. This is a retrospective study on the electronic health records of all clinical samples that tested positive to either B. pertussis or B. holmesii from January 2015 to January 2018 at Geneva University Hospitals. Multivariate logistic regression was used to build a model for co-infection prediction based on the electronic health record chart review. Limit of detection was determined for all targets of the commercial multiplexed PCR assay used on respiratory samples. A regression model, developed from clinical symptoms and signs, predicted B. pertussis and B. holmesii co-infection with an accuracy of 82.9% (95% CI 67.9-92.8%, p value = .012), for respiratory samples positive with any of the two tested Bordetella species. We found that the LOD of the PCR reaction targeting ptxS1 is higher than that reported by the manufacturer by a factor 10. The current testing strategy misses B. pertussis and B. holmesii co-infections by reporting only B. holmesii infections. Thus, we advocate to perform serological testing for detecting a response against pertussis toxin whenever a sample is found positive for B. holmesii. These findings are important, both from a clinical and epidemiological point of view, as the former impacts the choice of antimicrobial drugs and the latter biases surveillance data, by underestimating B. pertussis infections during co-infections.
Insights
Missed diagnoses of Bordetella pertussis-Bordetella holmesii co-infections occur due to limitations in current PCR testing. A new model using clinical signs predicts co-infections with 82.9% accuracy, improving surveillance and treatment.
Area of Science:
- Clinical Microbiology
- Infectious Diseases
- Epidemiology
Background:
- Bordetella pertussis and Bordetella holmesii are significant respiratory pathogens.
- Co-infections with B. pertussis and B. holmesii can be challenging to diagnose using standard PCR assays.
- Current diagnostic strategies may underestimate the prevalence of these co-infections.
Purpose of the Study:
- To identify predictive factors for missed B. pertussis-B. holmesii co-infections.
- To evaluate the analytical performance of a commercial multiplexed PCR assay.
- To develop a clinical prediction model for detecting B. pertussis-B. holmesii co-infections.
Main Methods:
- Retrospective analysis of electronic health records for positive B. pertussis or B. holmesii samples (Jan 2015-Jan 2018).
- Multivariate logistic regression used to build a co-infection prediction model based on clinical data.
- Determination of the limit of detection (LOD) for targets of a commercial multiplexed PCR assay on respiratory samples.
Main Results:
- A regression model based on clinical signs and symptoms predicted B. pertussis and B. holmesii co-infection with 82.9% accuracy.
- The LOD for the ptxS1 PCR target was 10 times higher than manufacturer specifications.
- Current testing strategies miss co-infections, reporting only B. holmesii when both are present.
Conclusions:
- Clinical prediction models can aid in identifying B. pertussis-B. holmesii co-infections.
- Serological testing for pertussis toxin response is recommended when B. holmesii is detected.
- Accurate co-infection diagnosis is crucial for appropriate antimicrobial therapy and reliable epidemiological surveillance.
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