Comprehensive and innovative post-market surveillance system for atypical respiratory pathogens detecting qPCR panel.

Abstract

Atypical respiratory pathogens such as Mycoplasma pneumoniae, Chlamydophila pneumoniae, Legionella pneumophila, and Bordetella pertussis are significant contributors to global morbidity and mortality from respiratory infections, and their prevalence has increased in recent years. Their detection is complicated by unique biological features and genetic variability. This study presents a comprehensive post-market surveillance (PMS) framework for the QIAstat-Dx® Respiratory SARS-CoV-2 Panel, integrating bioinformatic workflows and an AI-powered literature review developed by QIAGEN to monitor assay performance over the last years. Inclusivity and cross-reactivity protocols were applied to assess the impact of genetic mutations on assay sensitivity and specificity. The analysis revealed high inclusivity and specificity of the panel, with only a single potentially critical mutation detected in the transposon-targeted gene at low frequency and expected cross-reactivity among Bordetella species. The AI-driven tool enhanced the surveillance process, especially for pathogens with limited sequence data. The findings support the continued reliability of the QIAstat-Dx® Respiratory SARS-CoV-2 Panel for diagnosing atypical respiratory bacterial infections and highlight the importance of ongoing molecular surveillance using advanced bioinformatics and AI technologies.