Factors Predicting Bacterial Coinfection in Hospitalized COVID-19 Patients

ABSTRACT

Background. Despite multiple studies indicating a low prevalence of bacterial coinfection in coronavirus disease 2019 (COVID-19) patients, the majority of hospitalized COVID-19 patients receive one or more antibiotics. Patients with coinfection usually have multiple risk factors and poor clinical outcomes. Methods. A retrospective case control study was conducted comparing clinical characteristics and antimicrobial use in hospitalized adult COVID-19 patients with bacterial co-infections vs. randomly selected patients without co-infections (matched on month of admission). The study was conducted at three hospitals within the Montefiore Medical Center, Bronx, NY between March 1, 2020 and October 31, 2020. A multivariable logistic regression model was developed to assess the relationship of each predictor variable with coinfection status. Secondary outcomes included hospital mortality, antibiotic days of therapy (DOT), and C. difficile infection. Results. A total of 150 patients with coinfection and 150 patients without coinfection were included in the analysis. Table 1 summarized baseline characteristics and risk factors. The multivariable logistic regression model indicated that presence of a central line (OR=5.4, 95% CI 2.7-11.1), prior antibiotic exposure within 30 days (OR=5.3, 95% CI 2.8-10.0), prior ICU admission (OR=3.6, 95% CI 1.7-7.6), steroid use (OR=2.7, 95% CI 1.4-4.9), and any comorbid condition (OR=2.7, 95% CI 1.4-5.2) were significantly associated with the development of coinfection (table 2). Mortality was higher in patients with coinfection (56% vs. 11%, p < 0.0001) (table 3). Average antibiotic DOT was 10.5 in coinfected patients compared to 4 in noncoinfected patients, (p < 0.0001). Forty-one percent of coinfected patients had a multidrug resistant organism isolated. C. difficile rate was higher in coinfected patients (4% vs. 0%, p=0.03). Conclusion. As the healthcare community contends with a 3rd year of COVID-19 pandemic, understanding risk factors most predictive of bacterial coinfection can guide empiric antimicrobial therapy and targeted stewardship interventions. Ideally, co-infection risk scores are developed which may be useful for future inpatient surges.