The use of an algorithm to guide testing and treatment vs standard care protocols in patients with staphylococcal bacteremia resulted in a noninferior rate of clinical success, according to results published in JAMA.
Although there was no significant difference in rates of serious adverse events between the 2 groups, the researchers note that the “upper bound of the 95% confidence interval suggests the possibility of a higher rate of adverse events with abbreviated therapy.”
Treatment with prolonged antibiotic therapy in patients with uncomplicated staphylococcal bacteremia leads to antibiotic overuse and increases the likelihood for adverse events, whereas suboptimal in patients with complicated infections raises the risk for relapse, morbidity, and mortality. A standardized strategy to classify patients so they could be treated appropriately would improve patient care. In this trial, the efficacy and safety of an algorithm defining treatment for staphylococcal bacteremia based on clinical characteristics was evaluated.
The cohort included 509 patients who were randomly assigned to either algorithm-based therapy (n=255) or usual practice (n=254). Clinical success was observed in 209 patients in the algorithm group and in 207 who received usual care (82.0% vs 81.5%; difference, 0.5%; 1-sided 97.5% CI, −6.2% to ∞). Serious adverse events were similar between the 2 groups, at 32.5% of the algorithm-based therapy cohort vs 28.3% in usual care (difference, 4.2%; 95% CI, −3.8% to 12.2%). A secondary outcome noted that the mean duration of therapy among patients with uncomplicated infections was 4.4 days for algorithm-based therapy vs 6.2 days for usual practice (difference, −1.8 days; 95% CI, −3.1 to −0.6 days). In addition, with the exclusion from analysis of patients with simple coagulase-negative staphylococcal bacteremia who were not administered antibiotics, the duration of antibiotic treatment was significantly shorter for patients in the algorithm group (5.8 vs 7.7 days; difference, −1.9; 95% CI, −3.4 to −0.5).
“Further research is needed to assess the utility of the algorithm,” the researchers concluded.