Critical respiratory failure due to pregnancy complicated by COVID-19 and bacterial coinfection: A case report

BACKGROUND: In the past 3 years, the global pandemic of coronavirus disease 2019 (COVID-19) has posed a great threat to human life and safety. Among the causes of death in COVID-19 patients, combined or secondary bacterial infection is an important factor. As a special group, pregnant women experience varying degrees of change in their immune status, cardiopulmonary function, and anatomical structure during pregnancy, which puts them at higher risk of contracting COVID-19. COVID-19 infection during pregnancy is associated with increased adverse events such as hospitalisation, admission to the intensive care unit, and mechanical ventilation. Therefore, pregnancy combined with coinfection of COVID-19 and bacteria often leads to critical respiratory failure, posing severe challenges in the diagnosis and treatment process. CASE SUMMARY: We report a case of COVID-19 complicated with Staphylococcus aureus (S. aureus) coinfection in a pregnant woman at 34 wk of gestation. Her rapid progression of pulmonary lesions caused severe respiratory failure, and she received non-invasive ventilator-assisted respiratory treatment. Subsequently, we delivered a foetus via emergency caesarean section after accelerating the maturity of the foetal pulmonary system, and the respiratory condition of the puerperant woman significantly improved after the delivery of the foetus. Lavage fluid was taken under tracheoscopy to quickly search for pathogens by the metagenomic next-generation sequencing (mNGS), and both COVID-19 and S. aureus were detected. After targeted anti-infective treatment, the maternal condition gradually improved, and the patient was discharged from the hospital. CONCLUSION: The coinfection of pregnancy with COVID-19 and bacteria often leads to critical respiratory failure, which is a great challenge in the process of diagnosis and treatment. It is crucial to choose the right time to deliver the foetus and to quickly find pathogens by mNGS.