Detection of Mycobacterium chimaera in medical device water samples by customised real time PCR using a InGenius platform

Mycobacterium chimaera, belonging to the Mycobacterium avium complex, is an opportunistic environmental mycobacterium which has been isolated from medical device water samples such as Heater Cooler Units (HCU). Laboratories currently use culture-based diagnostic methods to detect M. chimaera, but these take a long time to obtain results. The aim of this study is to test and define the Limit of Detection (LoD) of a Real-Time Polymerase Chain Reaction test (RT-PCR) specific for M. chimaera, using a sample-to-result InGenius platform, performed on medical device water samples collected at the referral centre for the detection of mycobacteria from environmental specimens of Bologna, Italy. A total of 285 water samples were included in this study. The sensitivity and specificity of RT-PCR compared to culture were 60.5% and 98.8% respectively, with an overall agreement of 82.1% and a positive predictive value of 97.4%. The LoD calculated was approximately 2900 CFU/ml. In conclusion, this study confirmed that detection of M. chimaera with RT-PCR could support culture-based methods in reducing the time necessary to identify highly colonised HCUs, with high positive predictive values. Therefore, we suggest performing this customised RT-PCR on concentrated decontaminated water samples, shutting down and thoroughly disinfecting positive HCUs, to reduce the risk of patient infection.

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Publication Details

Journal
Scientific Reports
Published
2024-12-28
DOI
https://doi.org/10.1038/s41598-024-82440-5
Citations
4
Primary Topic
Mycobacterium research and diagnosis
Type
article
Field-Weighted Citation Impact
1.55
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article

Detection of Mycobacterium chimaera in medical device water samples by customised real time PCR using a InGenius platform

Alessandra Primavera, Paola Dal Monte, Maurizio Faccio, Cristina Maria Crovara Pesce et al.
4 citations
Scientific Reports
Mycobacterium research and diagnosis
1.55
article

Detection of Mycobacterium chimaera in medical device water samples by customised real time PCR using a InGenius platform

Alessandra Primavera, Paola Dal Monte, Maurizio Faccio, Cristina Maria Crovara Pesce, Francesco Bisognin, Federica Sorella, Michele Borghi, V. C. A. Ferraro
article en
4 citations

Abstract

Mycobacterium chimaera, belonging to the Mycobacterium avium complex, is an opportunistic environmental mycobacterium which has been isolated from medical device water samples such as Heater Cooler Units (HCU). Laboratories currently use culture-based diagnostic methods to detect M. chimaera, but these take a long time to obtain results. The aim of this study is to test and define the Limit of Detection (LoD) of a Real-Time Polymerase Chain Reaction test (RT-PCR) specific for M. chimaera, using a sample-to-result InGenius platform, performed on medical device water samples collected at the referral centre for the detection of mycobacteria from environmental specimens of Bologna, Italy. A total of 285 water samples were included in this study. The sensitivity and specificity of RT-PCR compared to culture were 60.5% and 98.8% respectively, with an overall agreement of 82.1% and a positive predictive value of 97.4%. The LoD calculated was approximately 2900 CFU/ml. In conclusion, this study confirmed that detection of M. chimaera with RT-PCR could support culture-based methods in reducing the time necessary to identify highly colonised HCUs, with high positive predictive values. Therefore, we suggest performing this customised RT-PCR on concentrated decontaminated water samples, shutting down and thoroughly disinfecting positive HCUs, to reduce the risk of patient infection.

Scientific ReportsVol. 14(1)
Azienda USL di Bologna (IT), University of Bologna (IT)
Clean water and sanitation
Openalex Percentile: Top 15%
Mycobacterium research and diagnosis
1.55
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Detection of Mycobacterium chimaera in medical device water samples by customised real time PCR using a InGenius platform — Alessandra Primavera, Paola Dal Monte, et al. · Scientific Reports (2024) | TGRS Research Map | TGRS