Validation and Implementation of a Diagnostic Algorithm for DNA Detection of Bordetella pertussis, B. parapertussis, and B. holmesii in a Pediatric Referral Hospital in Barcelona, Spain.
Por:
Valero-Rello A, Henares-Bonilla D, Acosta L, Jane M, Jordán-García I, Godoy P and Munoz-Almagro C
Publicada:
2 ene 2019
Ahead of Print:
2 ene 2019
Categoría:
Microbiology (medical)
Resumen:
This study aimed to validate a comprehensive diagnostic protocol based on real-time PCR for the rapid detection and identification of Bordetella pertussis, Bordetella parapertussis, and Bordetella holmesii, as well as its implementation in the diagnostic routine of a reference children's hospital. The new algorithm included a triplex quantitative PCR (qPCR) targeting IS481 gene (in B. pertussis, B. holmesii, and some Bordetella bronchiseptica strains), pIS1001 (B. parapertussis-specific) and rnase P as the human internal control. Two confirmatory singleplex tests for B. pertussis (ptxA-Pr) and B. holmesii (hIS1001) were performed if IS481 was positive. Analytical validation included determination of linear range, linearity, efficiency, precision, sensitivity, and a reference panel with clinical samples. Once validated, the new algorithm was prospectively implemented in children with clinical suspicion of whooping cough presenting to Hospital Sant Joan de Deu (Barcelona, Spain) over 12 months. Lower limits of detection obtained were 4.4, 13.9, and 27.3 genomic equivalents/ml of sample for IS481 (on B. pertussis), pIS1001 and hIS1001, and 777.9 for ptxA-Pr. qPCR efficiencies ranged from 86.0% to 96.9%. Intra- and interassay variabilities were <3% and <5%, respectively. Among 566 samples analyzed, B. pertussis, B. holmesii, and B. parapertussis were detected in 11.1%, 0.9% (only in females >4 years old), and 0.2% of samples, respectively. The new algorithm proved to be a useful microbiological diagnostic tool for whooping cough, demonstrating a low rate of other non-pertussisBordetella species in our surveilled area.
Filiaciones:
Valero-Rello A:
Institut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu, Spain
Henares-Bonilla D:
Institut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu, Spain
Network of Epidemiology and Public Health, CIBERESP, Spain
Acosta L:
Department of Statistics and Operations Research, Universitat Politecnica de Catalunya/BARCELONATECH, Spain
Subdirecció General de Vigilància i Resposta a Alertas de Salut Pública (ASPCAT), Spain
Jane M:
Network of Epidemiology and Public Health, CIBERESP, Spain
Subdirecció General de Vigilància i Resposta a Alertas de Salut Pública (ASPCAT), Spain
Jordán-García I:
Institut de Recerca Sant Joan de Déu, Hospital Sant Joan de Déu, Spain
Network of Epidemiology and Public Health, CIBERESP, Spain
Pediatric Intensive Care Department, Hospital Sant Joan de Déu, Universitat de Barcelona, Spain
Godoy P:
Network of Epidemiology and Public Health, CIBERESP, Spain
Institut de Recerca Biomèdica de Lleida, Lleida, Spain
Munoz-Almagro C:
Network of Epidemiology and Public Health, CIBERESP, Spain
School of Medicine, Universitat Internacional de Catalunya, Spain
Green Submitted, hybrid
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