Emergency department referrals for CT imaging of extremity soft tissue infection: before and during the COVID-19 pandemic.

Objectives: To evaluate the incidence and spectrum of findings in patients referred for CT imaging of extremity soft tissue infection in the adult emergency department (ED) setting before and during the COVID-19 pandemic.

Methods: Two hundred thirteen CT exams in the pre-COVID cohort (February 1, 2018-January 31, 2020) and 383 CT exams in the COVID cohort (February 1, 2020-January 31, 2022) were evaluated in this multicentre, retrospective study. Demographic information and clinical histories were collected, along with regional data on COVID-19 hospitalizations and deaths.

Results: Comparable age and sex distribution was found in the pre-COVID (average age of 53.5 years; male: female ratio of 71:29) and COVID (average age of 54.6 years; male: female ratio of 69:31) cohorts. The frequency of reported clinical risk factors (diabetes mellitus, injected drug use, prior surgery, animal bite) was not significantly different between the two cohorts. Findings of simultaneous involvement of both superficial and deep soft tissue infection on CT imaging were significantly higher in the COVID cohort (53.4%) than in the pre-COVID cohort (33.7%). CT findings of phlegmon (49.1% vs 22.1%), ulcers (48.8% vs 30%), osteomyelitis (21.7% vs 13.1%), as well as localized (18.8% vs 11.7%) and extensive (3.7% vs 2.3%) soft tissue gas were significantly more common in the COVID cohort than in the pre-COVID cohort.

Conclusions: During the COVID-19 pandemic, the number of ED CT exams for the evaluation of extremity soft tissue infection increased, with this imaging also showing more advanced disease. Pandemic-related modifications to human behaviour and re-distribution of healthcare resources may underlie these observed changes.

Advances in knowledge: This multi-centre study shows an increase in extremity soft tissue infection presenting to the ED during the pandemic. This finding is important for future pandemic preparations, as it can aid in the decision-making process around resource allocation.