One of the challenges of treating patients with staph bacteria in their bloodstreams, a potentially deadly infection, is to figure out the “sweet spot.”
Too little antibiotics, and the drugs won’t get the job done, said Dr. Mark Rupp, professor and chief of the University of Nebraska Medical Center’s infectious diseases division. Too much, and they can not only cause side effects but also drive antibiotic resistance.
So researchers, including a team at UNMC, tested a clinical algorithm that helps doctors sort patients by the complexity of their infections and determine what course of drugs they need. Rupp described the algorithm as a kind of road map to help guide clinicians down the treatment pathway.
The optimal treatment for blood infections with staph — or staphylococcus — isn’t known. As a result, there’s considerable variation in how it’s treated.
“It’s a significant and medically important problem,” Rupp said. “But despite that, clinicians don’t have good evidence-based information on the best way to treat these patients.”
In the study, published in the Journal of the American Medical Association, patients with simple infections received two days’ less IV antibiotics when treated according to the algorithm than those who got the usual treatment.
“It shortened the course in the uncomplicated cases and identified those who needed a longer course of therapy,” said Rupp, a co-author of the study.
The algorithm used in the study, he said, would be particularly useful in largely rural states like Nebraska where infectious disease specialists might not be readily available.
“This type of approach,” he said, “really helps those clinicians do a better job with the management of their patients.”
The trial, led by researchers at Duke University Medical Center, enrolled about 500 patients at 15 hospitals in the United States and one in Spain between 2011 and 2017. UNMC enrolled 32 patients.
In the study, patients were randomly assigned to receive the algorithm-guided therapy or treatment based on usual practice. In usual practice cases, the treating physician determined the antibiotic and the length of treatment. Under the algorithm, the drug and duration were predefined, with clinical criteria including blood and heart tests used to determine the complexity of the infection.
The success rate was similar among the two groups. But treatment for the simpler types of infection — those that hadn’t spread to other parts of the body — was two days shorter for the algorithm patients.
That’s important, because when antibiotics are overprescribed, bacteria sometimes develop resistance to antibiotics that were once commonly used to treat them.
Resistance concerns continue to grow. The federal government recently launched a yearlong challenge to accelerate the fight against it across the globe.
An editorial accompanying the staph study — while noting several limitations — called the algorithm “an elegant addition” to the evidence of how best to manage the condition that likely will influence the next set of guidelines for treating staph blood infections.
The authors also noted that such algorithms “have the potential to enhance care for individual patients and improve public health more broadly.”