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Abstract

Development of a Customized TaqMan® Array Card for Simultaneous Detection of 32 Respiratory Pathogens

Background: Syndromic testing with a rapid and complete diagnostic panel would be extremely useful for routine respiratory testing.

Objective: We developed and validated a real-time PCR-based Taqman array card (TAC) including several pathogens specific for immuno-compromised patients, using sequences designed and supported by the manufacturer.

Study design: Analytical validation was performed in 2 phases. Phase 1 testing was performed in 96-well plates and included efficiency, reactivity and sensitivity testing. The assays selected after phase 1 were validated in TAC format in phase 2 which included analytical sensitivity (LoD), reactivity, specificity and reproducibility testing. Clinical validation was performed in phase 3 by testing respiratory samples that were sent to the lab between December 2016 and May 2017. Results: In total, 90 assays were tested in phase 1 of which 43 were retained for further validation in TAC format. Seven of the 43 assays did not meet the predefined criterion of efficiency ≥ 80%, but were accepted for further testing in phase 2 and 3 due to lack of alternatives. All 43 targets together detected 89% (481/539) of positives included in the reactivity testing in phase 1 and 98% (246/252) of positives in phase 2. All tested assays showed excellent analytical sensitivity, with LoD ranging from 1 to 100 copies/μL. An overall specificity of 99.96% was found. Reproducibility ranged from 76%-100%, with a mean of 91%. For the clinical validation, a total number of 428 samples were tested, with an overall positivity rate of 56.3% and a co-infection rate of 15.9%. 15 results (4% of total number of positives) were not confirmed and considered false positives. One result (0.2%) was considered false negative.

Conclusion: This syndromic panel was analytically and clinically validated and will be implemented for routine respiratory testing in the Erasme University Hospital in high risk patient populations.


Author(s): Deborah Steensels, Marie-Luce Delforge, Katrien Lagrou, Kurt Beuselinck and Isabel Montesinos

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