Secondary Infection Surveillance with Metagenomic Next-Generation Sequencing in COVID-19 Patients: A Cross-Sectional Study.

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is a promising tool for improving antimicrobial therapy and infection control decision-making in complex infections. Secondary infection surveillance using mNGS in COVID-19 patients has rarely been reported.

METHODS

Respiratory pathogen and antibiotic resistance prediction were evaluated by BALF mNGS for 192 hospitalized COVID-19 patients between December 2022 and February 2023.

RESULTS

Secondary infection was confirmed in 83.3% (160/192) of the COVID-19 patients, with bacterial infections (45%, 72/160) predominating, followed by mixed bacterial and fungal infections (20%, 32/160), and fungal infections (17.5%, 28/160). The incidence of bacterial or viral secondary infection was significantly higher in patients who were admitted to the ICU, received mechanical ventilation, or developed severe pneumonia (all p<0.05). (n=30, 8.4%) was the most prevalent pathogen associated with secondary infection followed by (n=29, 8.1%), (n=29, 8.1%), (n=27, 7.6%), (n=23, 6.4%), (n=20, 5.6%) and (n=14, 3.9%). The overall concordance between the resistance genes detected by mNGS and the reported phenotypic resistance in 69 samples containing five clinically important pathogens (ie, and ) that caused secondary infection was 85.5% (59/69).

CONCLUSION

mNGS can detect pathogens causing secondary infection and predict antimicrobial resistance for COVID19 patients. This is crucial for initiating targeted treatment and rapidly detect unsuspected spread of multidrug-resistant pathogens.