Researchers develop new tool to fight antibiotic resistance

July 28 (UPI) -- Antibiotic resistance is a problem that has plagued researchers for years, but now researchers have developed a tool to combat antibiotic resistance.

According to the Centers for Disease Control and Prevention, antibiotic resistance is responsible for at least 2 million infections and 23,000 deaths each year in the United States.

Researchers at the University of Rochester Medical Center have created a new tool to help doctors and healthcare providers prescribe antibiotics to patients who really need them and avoid prescribing to patients who don't.

The study, published July 26 in Scientific Reports, identified 11 genetic markers in blood that correctly distinguished between viral and bacterial infections.

"It's extremely difficult to interpret what's causing a respiratory tract infection, especially in very ill patients who come to the hospital with a high fever, cough, shortness of breath and other concerning symptoms," Dr. Ann R. Falsey, professor and interim chief of the Infectious Diseases Division at UR Medicine's Strong Memorial Hospital, said in a press release.

"My goal is to develop a tool that physicians can use to rule out a bacterial infection with enough certainty that they are comfortable, and their patients are comfortable, foregoing an antibiotic."

A more accurate method to identify the difference between bacterial or viral infections will allow physicians to better know when to prescribe antibiotics or not.

Researchers analyzed clinical data from 94 adults hospitalized with a lower respiratory tract infection and used complex genetic and statistical analysis to identify markers in the blood that accurately classified patients with bacterial or viral infections.

The process was correct 80 to 90 percent of the time, according to researchers.

"Our genes react differently to a virus than they do to bacteria," said Mariani, a member of the Respiratory Pathogens Research Center. "Rather than trying to detect the specific organism that's making an individual sick, we're using genetic data to help us determine what's affecting the patient and when an antibiotic is appropriate or not."