Once or twice-daily, algorithm-based intravenous cephazolin for home-based cellulitis treatment

Abstract

Objective: Cellulitis is a common presentation to the ED and a significant cause of hospitalization that can be managed in hospital-in-the-home programmes. Current clinical-practice guidelines recommend once or twice-daily i.v. antibiotics; however, there is an absence of data describing the impact of these guidelines in real-world practice-based settings. This study aims to describe the safety and effectiveness of home-based cellulitis treatment according to an online treatment algorithm.

Methods: Over 12 months, 301 patients with a diagnosis of uncomplicated cellulitis requiring i.v. antibiotics and eligible for home-based therapy completed once-daily (cephazolin plus probenecid) or twice-daily (cephazolin alone) treatment, according to the treatment algorithm. Time (days) until non-progression of cellulitis was the primary outcome measure. Length of stay and treatment-related side-effects were also recorded.

Results: The mean time until non-progression was 2.11 (95% confidence interval [CI] 1.98-2.23) days versus 2.13 (95% CI 1.81-2.45) days for the once-daily (n = 213) and twice-daily (n = 88) regimens, respectively (P = 0.92, difference in means 0.02 [95% CI -0.36-0.33]). The corresponding mean length of stay was 6.55 (95% CI 5.96-7.15) days versus 7.67 (95% CI 6.69-8.65) days (P = 0.06, difference in means 1.12 [CI 0.03-1.23]). Treatment-related side-effects were reported in 15.5% (33/213 [95% CI 10.6-20.3]) of patients receiving the once-daily regimen compared with 9.1% (8/88 [95% CI 3.1-15.1]) treated twice-daily. Application of the once-daily strategy increased hospital-in-the-home cellulitis-related treatment capacity by 52% (1396/2688 [95% CI 50-54]).

Conclusions: An online decision support algorithm can support the effective use of a once or twice-daily treatment regimen for uncomplicated cellulitis. This approach can increase the efficiency and capacity of home-based therapy, resulting in better alignment of treatment options with clinicians and patients' preferences.